Franck Cappello is an expert in HPC with more than 20 years of experience. He initiated the SZ lossy compressor software at ANL. The SZ compressor is one of the most effective existing lossy compressors for scientific datasets. SZ can be used to compress scientific data from simulations and instruments. SZ is integrated into the main I/O libraries (HDF5, netCDF, ADIOS). Franck is involved in several projects of the Exascale Computing Project. He leads the EZ software technology project on lossy compression. He leads the data reduction topic of the CODAR co-design project. He co-leads the data analytics topic of the "Computing the Sky at Extreme Scale" application project where he focuses particularly on lossy compression of N-body datasets. He contributed to several Exascale road-mapping efforts (IESP and EESI). Franck is fellow of the IEEE and recipient of the 2018 IEEE TCPP Outstanding Service Award. He is associate editor of IEEE Transactions on Computers.

Peter Lindstrom is a Computer Scientist in the Center for Applied Scientific Computing at Lawrence Livermore National Laboratory. His primary research areas include data compression, scientific visualization, and scientific computing. Peter has developed numerous lossy and lossless open source compressors for floating-point and mesh-based scientific data, including zfp, fpzip, and hzip, and has published more than two dozen papers on data compression over the past 15 years in top venues such as ACM SIGGRAPH, IEEE VIS, ACM/IEEE SC, and the IEEE Data Compression Conference. He leads the zfp data compression effort as part of the US DOE's Exascale Computing Project. His zfp software has been adopted by HPC I/O libraries and tools like HDF5, ADIOS, Intel IPP, and VTK-m. Peter previously served as Editor in Chief for Graphical Models, Associate Editor for IEEE Transactions on Visualization and Computer Graphics, and Papers Chair for IEEE VIS. He is a Senior Member of IEEE.

Sheng Di received his Ph.D. from the University of Hong Kong in 2011 (certificated in 2012). He was a postdoctoral fellow at INRIA, where he worked on workload/hostload prediction for Google data centers and optimization of resource allocation. He is now a computer scientist in the mathematics and computer science (MCS) division of Argonne National Laboratory. His current research interest includes lossy compression for scientific datasets, high performance computing, scalable computing, and fault tolerance. He is a senior member of IEEE and institute fellow of NAISE. He is also the scientist at Large through the Consortium for Advanced Science and Engineering (CASE) at the University of Chicago. He is the recipient of 2018 IEEE-Chicago Distinguished Mentoring Award and 2019 IEEE-Chicago Distinguished R&D Award.

Bernd Mohr started to design and develop tools for performance analysis of parallel programs already with his diploma thesis (1987) at the University of Erlangen in Germany, and continued this in his Ph.D. work (1987 to 1992). During a three year postdoc position at the University of Oregon, he designed and implemented the original TAU performance analysis framework. Since 1996 he has been a senior scientist at Forschungszentrum Jülich. Since 2000, he has been the team leader of the group ''Programming Environments and Performance Analysis''. Besides being responsible for user support and training in regard to performance tools at the Jülich Supercomputing Centre (JSC), he is leading the Scalasca performance tools efforts in collaboration with Prof. Felix Wolf of TU Darmstadt. Since 2007, he also serves as deputy head for the JSC division ''Application support''. He was an active member in the International Exascale Software Project (IESP/BDEC) and work package leader in the European (EESI2) and Jülich (EIC, ECL) Exascale efforts. For the SC and ISC Conference series, he served on the Steering Committee. He is the author of several dozen conference and journal articles about performance analysis and tuning of parallel programs.

Bernd Mohr started to design and develop tools for performance analysis of parallel programs already with his diploma thesis (1987) at the University of Erlangen in Germany, and continued this in his Ph.D. work (1987 to 1992). During a three year postdoc position at the University of Oregon, he designed and implemented the original TAU performance analysis framework. Since 1996 he has been a senior scientist at Forschungszentrum Jülich. Since 2000, he has been the team leader of the group ''Programming Environments and Performance Analysis''. Besides being responsible for user support and training in regard to performance tools at the Jülich Supercomputing Centre (JSC), he is leading the Scalasca performance tools efforts in collaboration with Prof. Felix Wolf of TU Darmstadt. Since 2007, he also serves as deputy head for the JSC division ''Application support''. He was an active member in the International Exascale Software Project (IESP/BDEC) and work package leader in the European (EESI2) and Jülich (EIC, ECL) Exascale efforts. For the SC and ISC Conference series, he served on the Steering Committee. He is the author of several dozen conference and journal articles about performance analysis and tuning of parallel programs.

Dr. Kindratenko is a Senior Research Scientist at the National Center for Supercomputing Applications, an Adjunct Associate Professor in the Department of Electrical and Computer Engineering and a Research Associate Professor in the Department of Computer Science at the University of Illinois. He received D.Sc. degree from the University of Antwerp, Belgium, in 1997 and prior to that graduated from the State Pedagogical University, Kirovograd, Ukraine, in 1993. Dr. Kindratenko’s research interests include high-performance computing, special-purpose computing architectures, and cloud computing. He serves as a department editor of IEEE Computing in Science and Engineering magazine and an associate editor of the International Journal of Reconfigurable Computing. Dr. Kindratenko’s work has been funded by NSF, NASA, ONR, and industry. He has published over 60 papers in refereed scientific journals and conference proceedings and holds 4 US patents. He is a Senior Member of IEEE and ACM.

Dr.-Ing. Andreas Lintermann is a researcher at the Jülich Supercomputing Centre (JSC) at Forschungszentrum Jülich, where he is heading the Simulation and Data Lab Engineering as part of the Jülich Aachen Research Alliance Center for Simulation and Data Science (JARA-CSD). Dr.-Ing. Lintermann received his diploma in Computer Science from RWTH Aachen University in 2009. From 2009 to 2014, he was a P.hD. student at the Institute of Aerodynamics and Chair of Fluid Mechanics, RWTH Aachen University. In his thesis, he investigated the flow in the human nasal cavity and developed a massively parallel grid generator. His research focuses on respiratory flows, lattice-Boltzmann methods, Lagrangian particle methods, fluid-structure interaction, meshing methods, and high-performance computing. Lintermann published 30 articles in peer-reviewed journals and conference proceedings, and magazines, and is reviewer for several renowned journals.

Dr Charalambos Chrysostomou is an Associate Research Scientist at The Cyprus Institute, applying advanced machine learning on data-driven applications, including computational fluid dynamics, medical imaging and computational physics. Charalambos received his BA in Computer Science, from the University of Nicosia, Cyprus, in 2006, his Master in Computational Intelligence and Robotics, and PhD in Bioinformatics from De Montfort University, United Kingdom, in 2007 and 2012, respectively. He was the University of Leicester as a postdoctoral fellow until 2016.

Ashley Scillitoe is a Research Associate within the Data-Centric Engineering group at the Alan Turing Institute. His research focuses on the quantification of aleatory and epistemic uncertainties in CFD simulations, with machine learning techniques employed to make use of high-fidelity data from Large Eddy Simulations. Ashley completed his PhD at the University of Cambridge in 2017, where his work involved the development of more reliable Large Eddy Simulation techniques for application to Gas-Turbine compressor flows. Prior to his PhD, Ashley obtained a Meng (Hons) in Aerospace Engineering from the University of Manchester.

Eloisa Bentivegna is a Research Staff Member in Daresbury, UK. She holds a PhD in Physics, with a minor in High Performance Computing, from Penn State University, and has served as a postdoctoral scholar at the Center for Computational and Technology (USA), a Marie Curie Fellow at the Max Planck Institute for Gravitational Physics (Germany), as well as a National Montalcini Fellow and faculty member of the Physics Department at the University of Catania (Italy) before joining IBM. She has vast experience in the application of computational techniques to the frontiers of theoretical physics, most notably strong gravity and high-energy quantum fields. She currently works on building computational models of fluid-dynamical systems and developing an infrastructure for verifying and streamlining these models using cognitive technologies. Her broader expertise involves multiscale phenomena and coarse graining, relativistic optics, and nonlinear elliptic problems.

Jiahuan Cui is an assistant professor at ZJU-UIUC institute, Zhejiang University. He is leading a group working on the high-fidelity simulation using high performance computers and the turbulence modelling using data driven methods. Jiahuan Cui received his Ph.D from the University of Cambridge in 2016, where his research focused on the high-fidelity simulation for the turbulent flow in turbomachinery. After receiving his PH.D, he worked as a research associate from 2016 to 2017 at the University of Cambridge on a fan modelling project sponsored by Rolls Royce and Innovate UK.

George Karniadakis received his S.M. (1984) and Ph.D. (1987) from Massachusetts Institute of Technology. He was appointed Lecturer in the Department of Mechanical Engineering at MIT in 1987 and subsequently he joined the Center for Turbulence Research at Stanford/NASA Ames. He joined Princeton University as Assistant Professor in the Department of Mechanical and Aerospace Engineering and as Associate Faculty in the Program of Applied and Computational Mathematics. He was a Visiting Professor at Caltech (1993) in the Aeronautics Department. He joined Brown University as Associate Professor of Applied Mathematics in the Center for Fluid Mechanics on January 1, 1994. He became a full professor on July 1, 1996. He has been a Visiting Professor and Senior Lecturer of Ocean/Mechanical Engineering at MIT since September 1, 2000. He was Visiting Professor at Peking University (Fall 2007 & 2013). He is a Fellow of the Society for Industrial and Applied Mathematics (SIAM, 2010-), Fellow of the American Physical Society (APS, 2004-), Fellow of the American Society of Mechanical Engineers (ASME, 2003-) and Associate Fellow of the American Institute of Aeronautics and Astronautics (AIAA, 2006-). He received the Ralf E Kleinman award from SIAM (2015), the J. Tinsley Oden Medal (2013), and the CFD award (2007) by the US Association in Computational Mechanics. His h-index is 73 and he has been cited over 26,000 times.

Kazuto Ando is a senior technical staff in the Operations and Computer Technologies Division and Complex Phenomena Unified Simulation Research Team at RIKEN Center for Computational Science (R-CCS), Kobe, Japan. His research interests are High-Performance Computing (specifically computational performance optimization on HPC systems), Computational Fluid Dynamics, and Artificial Intelligence. He had also worked in the application area of earthquake and tsunami simulation at JAMSTEC. He received his BS and MS degree in Physics from Tokyo Metropolitan University, Japan.

Mario Rüttgers joined the Institute of Aerodynamics and the Jülich Supercomputing Centre as a researcher in February 2019. His research focuses on an improved treatment in rhinology by combining numerical flow simulations with machine learning techniques. Since February 2019 he is also a PhD student at RWTH Aachen University. Before starting the PhD program, he completed a Master's degree program in mechanical engineering at the Pohang University of Science and Technology in South Korea, specializing in fluid mechanics and machine learning techniques.

Michael Gauding is research scientist at the French research institute CORIA and at the University of Rouen. He received his PhD from RWTH Aachen University in 2014 and is an expert in turbulence modeling, combustion and high-performance computing. He performed simulations of turbulence with more than 230 Billion grid points to analyze strong turbulent bursts at smallest scales. To tackle the complex statistics of these bursts, he developed data-driven methods based on super- resolution networks.

Mario Bedrunka is research assistant at the University of Siegen, Germany and Bonn-Rhein-Sieg University of Applied Sciences. He holds a M. Eng. degree in mechanical engineering from the Bonn-Rhein-Sieg University of Applied Sciences. Now he pursues a Ph.D. on machine learning in the lattice Boltzmann methods and the modeling and simulation of hydrogen storages.

Felipe de Castro Teixeira Carvalho is a Ph.D. student in Mechanical Engineering at the University of Campinas and master in Mechanical Engineering from the University of Campinas. He has experience in signal processing, mechanical vibration and multiphase flows. Currently, he has a keen interest in dynamical systems modelling and machine learning applied to dynamical systems and dimensionality reduction

Dr. Jinhui Yan is an assistant professor in civil and environmental engineering at the University of Illinois at Urbana-Champaign. His research interests lie in computation mechanics, CFD, fluid-structure interaction, and their applications to wind, tidal energy, and additive manufacturing. He won ASME Robert M. and Mary Haythornthwaite Young Investigator Award in 2018. He currently serves as the vice-chair for both the CFD and FSI thrust of the US Association for Computational Mechanics and computational fluid-structure interaction committee of ASME.

Thomas Brown obtained his PhD in Mathematics from the University of Delaware in 2018. He is a numerical analyst interested in Galerkin methods for models in continuum mechanics, optimization and optimal control problems, and scientific computing. His research focuses on analysis and implementation of novel numerical methods for different problems of interest. The analysis includes well-posedness, stability, and approximation properties of the methods. Recently he has also been investigating the use of machine learning techniques to solve systems of ODEs and PDEs. He is a co-author of the textbook: Variational Techniques for Elliptic Partial Differential Equations: Theoretical Tools and Advanced Applications.

Sarath Radhakrishnan is a PhD student in the Computer Applications in Science and Engineering department of the Barcelona Supercomputing Center. His research is on wall modeling in Large Eddy Simulation.

Yaning Wang is studying for his PH.D degree in Computational Fluids Dynamics (CFD) at Zhejiang University. He graduated from Xi’an JiaoTong University in 2019 with a Bachelor's Degree in Mechanical Engineering. His research interest is using machine learning techniques for CFD application. Currently, his work focuses on using machine learning technology to predict the film cooling performance for high pressure turbines.

Dr. Shirui Luo is a research scientist in the Industrial Application Domains group at the National Center for Supercomputing Applications (NCSA). Dr. Luo is experienced in multi-physics and multiscale computational modeling and machine learning. He has carried out large-scale simulations and performance profiling on a diverse range of supercomputers in the private sector and government-funded research projects.

Dr. Kunkel is a Lecturer at the Computer Science Department at the University of Reading. Previously, he worked as postdoc in the research department of the German Climate Computing Center (DKRZ) that partners with the Scientific Computing group at the Universität Hamburg. He manages several research projects revolving around High-Performance Computing and particularly high-performance storage. Julian became interested in the topic of HPC storage in 2003, during his studies of computer science. Besides his main goal to provide efficient and performance-portable I/O, his HPC-related interests are: data reduction techniques, performance analysis of parallel applications and parallel I/O, management of cluster systems, cost-efficiency considerations, and the software engineering of scientific software.

Dr. Jay Lofstead is a Principal Member of Technical Staff at Sandia National Laboratories in Albuquerque, New Mexico. Since 2010, Jay has been working on HPC simulation workflows focusing on data management issues and as well as general I/O and storage issues for HPC. His prior work includes the R&D100 Award winning ADIOS I/O componentization framework in use in more than 30 production scientific simulations. He is a member of several conference and workshop program committees.

Jean-Thomas has obtained his Ph.D in 2000 from CEA, DAM (French Atomic Commission, Military Dept.) and University of Versailles (France). After spending 2 years at Intel Compiler group in Santa Clara, he joined the University of Versailles as a Research Engineer, and afterward joined CEA (civilian department) still as a Research Engineer. Jean-Thomas was one of the founding members of the Exascale Research Centre, a joint lab between Intel, CEA and UVSQ, where he took the head of the performance group. He’s now actively participating in the development of DDN’s newly set Advanced Technology Center in France. Jean-Thomas is chairing two workshops focused on parallel file systems and performance scalability of file systems. He has authored or co-authored around 20 international publications.

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Tom Vierjahn is a Professor of Computer Science at the Westphalian University of Applied Sciences, Germany. There, he is working on visualization, rendering, and virtual reality. During his postdoc stay at RWTH Aachen University, Germany, he researched analysis and visualization of performance data acquired from massively parallel application runs on supercomputers. Furthermore, he applied in situ visualization to parallel simulations stemming from neuroscience research. Tom received his Diploma and Master's degree from Dusseldorf University of Applied Sciences, Germany. He received his PhD in computer science from the University of Münster, Germany, for his work on online surface reconstruction from unorganized point clouds with integrated texture mapping.

Thomas Theussl is currently a Visualization Scientist in the KAUST Visualization Core Lab. He received his M.S. in Computer Science from the Vienna University of Technology in 2000.

Steffen Frey is a is an Assistant Professor at the University of Groningen. His research interests are in visual analysis techniques for large and complex spatio-temporal data, with a particular focus on performance-related aspects and the expressive visual representations of dynamic processes.

Dr. Kenneth Moreland is a principal member of technical staff at Sandia National Laboratories. He received BS degrees in computer science and in electrical engineering from the New Mexico Institute of Mining and Technology in 1997. He received MS and Ph.D. degrees in computer science from the University of New Mexico in 2000 and 2004, respectively. Dr. Moreland specializes in large-scale visualization and graphics and has played an active role in the development of several HPC products including ParaView, VTK, IceT, Catalyst, Dax, and VTK-m. His current interests include the design and development of visualization algorithms and systems to run on multi-core, many-core, and future-generation computer hardware.

Dr. Guido Reina is senior lecturer and research associate at the Visualization Research Center of the University of Stuttgart. He received his diploma in Software Engineering and his Doctoral degree in Visualization from the University of Stuttgart. His research interests include large data visualization, parallel and in situ methods especially for particle data, focusing on molecular data sets. He is the MegaMol development team leader and interested in visualization system design and engineering as well as in long-term software sustainability issues.

Andy is a Research Mechanical Engineer at the United States Army Corps of Engineers. He works primarily on developing algorithms and interfaces for software that numerically discretizes partial differential equations (PDE). His focus has been on the finite element method (FEM) for spatial discretizations of the PDE using adaptive techniques and parallel computing to ensure efficient use of available computing resources. Previously, Andy was a Staff R&D Engineer at Kitware where he has worked on the Visualization Toolkit (vtk.org) and ParaView (paraview.org) open source projects focusing on ParaView Catalyst.

Dr. Stahlberg is director of Biomedical Informatics and Data Science (BIDS) at the Frederick National Laboratory for Cancer Research, spanning explorations from the molecular level to clinical trials. He has been instrumental in the laboratory's high-performance computing initiative and in assembling scientific teams across multiple, complex organizations to advance predictive oncology. Stahlberg has played a leadership role in establishing a collaboration between the NCI and the Department of Energy (DOE) to accelerate progress in precision oncology and computing. The Joint Design of Advanced Computing Systems for Cancer (JDACS4C) collaboration is rooted in three national initiatives and undertakes exploring predictive oncology and exascale computing in fundamental RAS biology, predicting tumor response, developing patient level health trajectories, and uses of AI to accelerate drug discovery. Dr. Stahlberg holds a Ph.D. in computational chemistry from The Ohio State University.

Thomas Steinke (organizer) heads the Supercomputing Dept. at the Zuse Institute Berlin (ZIB) and is responsible for the HPC research, consulting and operation His research interest is in high performance computing, heterogeneous systems for scientific and data analytics applications, and parallel simulation methods. Thomas leads the Intel Parallel Computing Center at ZIB since 2013. He received his Doctorate in Natural Sciences (Dr. rer. nat.) in chemistry from the Humboldt University of Berlin.

As Head of the Registry Informatics department at the Cancer Registry, responsibility include modernization and digitalisation of the Cancer Registry, including the development and deployment of an IKT-framework for cancer registries with electronic cancer reporting using the Norwegian Health Network, establishing the IT-system for the pilot project for Colorectal screening programme, modernization of the cervical cancer screening programme, and the insourcing the ICT-systems of the National Mammography programme. He is a board member of the CERTUS SFI, as well as serving on several reference and steering committees.

Marco Berghoff received the diploma degree in mathematics from the University of Paderborn, Germany, with a focus on microlocal analysis, numerics, and physics. He received the PhD degree in computational materials science from the Institute for Applied Materials. He has been a member of the Karlsruhe Institute of Technology, at the Institute for Applied Materials. He has years of experience in multiscale modeling and high-performance optimization, and with the scale-bridging of the atomistic phase-field crystal model to the mesoscopic phase-field method. As a postdoctoral researcher in the Simulation Laboratory “NanoMicro”, he has introduced the framework NAStJA, and currently leads the developments. He is involved in several activities within this project, in particular in the development of large-scale simulations for biological or material science research topics. The NAStJA Framework is used to simulate the growth and treatment of cancerous tumor with a cell geometric resolution.

Sunita Chandrasekaran is assistant professor in the Computer and Information Sciences Department at the University of Delaware. Her research interests include exploring the suitability of high-level programming models and runtime systems for HPC and embedded platforms, and migrating scientific applications to heterogeneous computing systems. Dr. Chandrasekaran was a post-doctoral fellow at the University of Houston and holds a Ph.D. from Nanyang Technological University, Singapore. She is a member of OpenACC, OpenMP, MCA and SPEC HPG. She has served on the program committees of various conferences and workshops including SC, ISC, ICPP, CCGrid, Cluster, and PACT, and has co-chaired parallel programming workshops co-located with SC, ISC, IPDPS, and SIAM.

Petrina Hollingsworth serves as an engagement manager for NCI-DOE collaborations at Frederick National Laboratory for Cancer Research.

Andreas Deutsch is head of the department of Innovative Methods of Computing at the Centre for Information Services and High Performance Computing (Dresden University of Technology). His research is focused on mathematical biology, especially cellular automata and agent-based modeling, cancer invasion and collective phenomena in the life sciences.

Emmanuelle Saillard is a tenured research scientist at Inria Bordeaux Sud-Ouest. She received her PhD in Computer science from the University of Bordeaux in 2015. From October 2015 to October 2016, she was employed as a postdoctoral researcher at the University of California Berkeley (USA). During this time, she developed dynamic program analyses for communication and synchronization optimizations in large scientific codes. From December 2016 to September 2017, she worked on the European project HPC4E. Her goal was to optimize kernels of some applications developed in the project with a metaprogramming language. In October 2017, she joined the STORM team at Inria Bordeaux. Her research interests focus on compiler/runtime interaction and code optimization. She has expertise in compiler technology, debugging and validation methods as well as parallel languages and codes.

Julien Jaeger is a research scientist at CEA. He received his PhD in Computer Science from the University of Versailles in 2012. After its PhD focusing on parallel code optimisation, he was hired at CEA to work on MPC, a framework combining an MPI, an OpenMP and a Pthread implementation on top of a user-level thread scheduler. Since 2019, he is the head of the MPC team. In addition to his position at CEA, Julien Jaeger teaches parallel programming and parallel optimisations in several schools. He participates actively to the MPI Forum. His main research interest is runtime stacking, with a focus on MPI implementations (collective algorithms and asynchronous progression) and their interactions with other parallel runtimes, along with compiler transformations for parallelism.

Dr. Baxter has been involved with computing since 1966, initially in hardware working with relay, discrete transistor logic and early Diode-Transistor Logic ICs. He learned to program with IBM 1401 (Autocoder), 1620 (Fortran) and 360 systems (BAL, PL/1, APL). He implemented one of the first commercial minicomputer timesharing systems on a Data General Nova in 1970, before receiving his B.S. in Computer Science (1973). During a brief stint in the numerical controls business, he designed and implemented a complete 16 bit virtual memory minicomputer, its OS and development tools for automated milling systems. In 1976, he started Software Dynamics, a systems software house, where he designed compilers, time-sharing and distributed network operating systems. The similarity in concepts and dissimilarity in implementation of the various OSes suggested that managing designs was key to managing long-lived software systems, and turned Ira's interests towards deeper software engineering research. In 1990, he received a Ph.D. in Computer Science from the University of California at Irvine, where he studied Software Engineering, focusing on design reuse using transformational methods. Dr. Baxter spent several years with Schlumberger, working on a PDE-solver generator for CM-5 supercomputers (Sinapse). He was consulting Research Scientist for Rockwell International, focusing on industrial control automation software engineering tools for several years.

Tim Jammer is a PhD candidate at the Institute for Scientific Computing at Technical University of Darmstadt. He received his Bachelor and Master degree from the University of Hamburg, while also working as a student research assistant at the DKRZ. His research interests are mainly in parallel and high performance computing with a particular focus on compiler-based analysis and rewriting tools for the efficient use of MPI. He is one of the authors and main contributors of the MPI correctness benchmark suite MPI-CorrBench, as well as other MPI-related tools that can be found at https://github.com/tudasc. In addition to his research position, he is a staff member at the Hessian Competence Center for High Performance Computing (www.hkhlr.de), providing user support and regular training courses for Hessian HPC users.

Julia Lawall is a senior research at Inria-Paris. Previously, she was on the faculty of the University of Copenhagen. She received her PhD in 1994 from Indiana University, USA. She has been program chair of GPCE, ICFP, and ASE, a member of the SIGPLAN Executive Committee, and is on the editorial board of Science of Computer Programming. Her research is at the crossroads of programming languages, software engineering, and operating systems. She is particularly interested in the design of tools that address problems in the maintenance of large software. She is the primary developer of the open-source Coccinelle program transformation system and has over 2000 patches in the Linux kernel based on her research.

Michael Blesel is a doctoral candidate at the Otto von Guericke University Magdeburg in the Parallel Computing and I/O group. His main research is in the field of compiler-assisted correctness checks for SPMD applications in the context of high-performance computing. During his time as a student at the University of Hamburg he has worked for the Scientific Computing group as a research and teaching assistant for their high-performance computing related courses. His interests include compiler-based tools, high-performance computing in general and performance optimizations for parallel applications.

Reed Milewicz is a senior member of technical staff in the Department of Software Engineering and Research within the Center for Computing Research at Sandia National Laboratories. He does research in the areas of software engineering, formal verification, and compilers. He believes that the quality of our lives depends upon the quality of our software, and that’s why he focuses on developing better practices, processes, and tools to target all phases of the software development lifecycle. This is a course of research that straddles the line between systems and human factors, and it’s carried out in close coordination with the communities he supports. Since joining Sandia in late 2016, his focus has been on the scientific software development community.

Dr. Dhabaleswar K. (DK) Panda is a Professor of Computer Science and Engineering at the Ohio State University. His research interests include parallel computer architecture, high-performance networking, InfiniBand, Exascale computing, Big Data, programming models, GPUs and accelerators, high-performance file systems and storage, virtualization, deep learning and cloud computing. He has published over 400 papers in major journals and international conferences related to these research areas. Dr. Panda and his research group members have been doing extensive research on modern networking technologies including InfiniBand, High-Speed Ethernet and RDMA over Converged Enhanced Ethernet (RoCE). Recently, Dr. Panda and his team have also developed high-performance RDMA-enabled Apache Hadoop and Memcached to accelerate Big Data applications. He is an IEEE Fellow and a member of ACM. More details about Prof. Panda are available at http://www.cse.ohio-state.edu/~panda.

Dr. Hari Subramoni received the Ph.D. degree in Computer Science from The Ohio State University, Columbus, OH, in 2013. He is a research scientist in the Department of Computer Science and Engineering at the Ohio State University, USA, since September 2015. His current research interests include high performance interconnects and protocols, parallel computer architecture, network-based computing, exascale computing, network topology aware computing, QoS, power-aware LAN-WAN communication, fault tolerance, virtualization, big data and cloud computing. He has published over 50 papers in international journals and conferences related to these research areas. Recently, Dr. Subramoni is doing research and working on the design and development of MVAPICH2, MVAPICH2-GDR, and MVAPICH2-X software packages. He is a member of IEEE. More details about Dr. Subramoni are available from http://www.cse.ohio-state.edu/~subramon.

Aamir is currently a Research Scientist in the Dept. of Computer Science & Engineering at the Ohio State University. He works as part of the Network-Based Computing Lab led by Dr. Dhabaleswar K. Panda. Aamir was an Associate Professor at FAST National University of Computing and Emerging Sciences in Lahore, Pakistan. Prior to joining FAST-NUCES, Aamir was at Imam Abdulrahman Bin Faisal University. Before that, he was affiliated with SEECS, NUST where he taught CS courses including Operating Systems and Parallel Computing. Aamir conducts research in the area of Parallel Computing, Multicore Computing, Data Center Computing, and Software-Defined Networking. In the academic year 2011, Dr Aamir Shafi was a visiting scholar at MIT where he worked with Professor Charles Leiserson on the Cilk technology.

Satoshi Matsuoka from April 2018 has become the director of Riken CCS, the top-tier HPC center that represents HPC in Japan, developing and hosting Japan’s tier-one ‘Fugaku’ supercomputer which has become the fastest supercomputer in the world in all four major supercomputer rankings, along with multitudes of ongoing cutting edge HPC research being conducted, including investigating Post-Moore era computing. He had been a Full Professor at the Global Scientific Information and Computing Center (GSIC), the Tokyo Institute of Technology since 2000, and the director of the joint AIST- Tokyo Tech. Real World Big Data Computing Open Innovation Laboratory (RWBC- OIL) since 2017, and became a Specially Appointed Professor at Tokyo Tech in 2018 along with his directorship at R-CCS. He has been the leader of the TSUBAME series of supercomputers that have won many accolades such as world #1 in power-efficient computing. He also leads various major supercomputing research projects in areas such as parallel algorithms and programming, resilience, green computing, and convergence of big data/AI with HPC. He has written over 500 articles according to Google Scholar, and chaired numerous ACM/IEEE conferences, including the Program Chair at the ACM/IEEE Supercomputing Conference (SC13) in 2013. He is a Fellow of the ACM and European ISC, and has won many awards, including the JSPS Prize from the Japan Society for Promotion of Science in 2006, presented by his Highness Prince Akishino; the ACM Gordon Bell Prize in 2011; the Commendation for Science and Technology by the Minister of Education, Culture, Sports, Science and Technology in 2012; the 2014 IEEE-CS Sidney Fernbach Memorial Award, the highest prestige in the field of HPC; HPDC 2018 Achievement Award from ACM; and recently SC Asia 2019 HPC Leadership Award.

Gilad Shainer serves as senior vice-president of marketing for Mellanox networking at NVIDIA, focusing on high- performance computing, artificial intelligence and the InfiniBand technology. Mr. Shainer joined Mellanox in 2001 as a design engineer and later served in senior marketing management roles since 2005. Mr. Shainer serves as the chairman of the HPC-AI Advisory Council organization, the president of UCF and CCIX consortiums, a member of IBTA and a contributor to the PCISIG PCI-X and PCIe specifications. Mr. Shainer holds multiple patents in the field of high-speed networking. He is a recipient of 2015 R&D100 award for his contribution to the CORE-Direct In-Network Computing technology and the 2019 R&D100 award for his contribution to the Unified Communication X (UCX) technology. Gilad Shainer holds a MSc degree and a BSc degree in Electrical Engineering from the Technion Institute of Technology in Israel.

Duncan Roweth is a Distinguished Technologist in the HPC and Mission Critical Business Unit CTO office at HPE. He joined HPE in Jan 2020 with the acquisition of Cray. While at Cray he worked on three generations of HPC network. He has been in a leading figure in the Slingshot program since its inception. He is currently working on design of 2nd and 3rd generation Slingshot products for future HPE systems. Duncan holds a Ph.D. from the University of Edinburgh.

As CEO of Cornelis Networks, Phil is responsible for the overall management and strategic direction of the company. Prior to co-founding Cornelis Networks, Phil served as a director at Intel Corporation, responsible for fabric platform planning and architecture, product positioning, and business development support. Prior to that role, Phil served as vice president of engineering and vice president of HPC technology within QLogic’s Network Solutions Group, responsible for the design, development, and evangelizing of all high-performance computing products, as well as all storage area network switching products. Before joining QLogic, Phil was vice president of engineering at SilverStorm Technologies, which he co-founded in 2000 and which was acquired by QLogic in 2006. SilverStorm’s core focus was on providing complete network solutions for high performance computing clusters. Prior to co-founding SilverStorm, Phil served as director of engineering at Unisys Corporation and was responsible for all I/O development across the company’s diverse product lines. Phil holds a BS in Mathematics from St. Joseph’s University and an MS in Computer and Information Science from the University of Pennsylvania.

Hemal Shah is a Distinguished Engineer and Systems/Software/Standards architect in the Data Center Solutions Group (DCSG) division at Broadcom Inc. He leads and manages a team of architects. Hemal is responsible for the definition of product architecture and software roadmap/architecture of all product lines of Ethernet NICs. Hemal led the architecture definition of several generations of NetXtreme E-Series/NetXtreme I server product lines and NetXtreme I client product lines. Hemal spearheaded the system architecture development of TruFlow technology for vSwitch acceleration/packet processing software frameworks, TruManage technology for system and network management, device security features, virtualization and stateless offloads. Hemal has defined the system architecture of RDMA hardware/software solutions for more than two decades. Before joining Broadcom in 2005, Hemal worked at Intel Corporation where he led the development of system/silicon/software architecture of communication processors, 10 Gigabit Ethernet controllers, TCP/iSCSI/RDMA offloads, and IPsec/SSL/firewall/VPN accelerations. Hemal is the lead technical representative/contributor from Broadcom Inc. in the Open Compute Project (OCP) and Distributed Management Task Force (DMTF). Hemal serves as Senior VP of Technology in the DMTF and a project co-lead of OCP Hardware Management project. Hemal has co-authored several OCP specifications, 70+ DMTF specifications, four IETF RFCs, and 10 plus technical conference/journal papers. Hemal is a named inventor on 40+ patents with several pending patents. Hemal holds Ph. D. (computer engineering) and M.S. (computer science) degrees from Purdue University, M.S.E.E. degree from The University of Arizona, and B.S. (electronics and communication engineering) degree from Gujarat University, India.

Moshe Voloshin is Systems architect in Data Center Solutions Group (DCSG) division at Broadcom Inc. Moshe spearheaded the system architecture development of ROCE and Congestion Control in Broadcom Ethernet NICs, involved in definition of product architecture, modeling, and system simulations. Previously Moshe was a Director, manager, ASIC/HW engineer at Cisco High End router division where he developed and managed the development of Network Processing Unit (NPU), QOS, and fabric ASICs, in products such as GSR and CRS.

Matthew Williams is CTO of Rockport Networks and has 25 years of technical leadership and engineering experience, 14 years as CTO of successful network technology companies and has 21 issued US patents. He is an expert strategist, analyst and visionary who has delivered on transformational product concepts. Matthew is an insightful and energetic communicator who enjoys product evangelization and inspiring global business and technical audiences. Matthew has a B.Sc. in Electrical Engineering with First Class Honours from Queen’s University, Kingston, Canada and is a registered P.Eng.

Sanjay is currently serving as Director Cloud Engineering at Oracle. His focus area is Machine Learning on HPC/GPU, Data Science Platform and Blockchain-As-A-Service on Oracle’s 2nd Generation Bare Metal Cloud Computing Services. His most recent contribution is creating the set of " Validated Solution Guides" for "Architecting Deep Learning on Oracle Cloud IaaS for Autonomous Driving". Sanjay has 28 years of progressive experience in Information Technology related to Security, Cryptography and Infrastructure-as-a-Service. He has the distinction of being the lead architect for Dell Services first ever Private Cloud launched in 2008 and Chief Network Architect for Dell’s vCloud Public Offering in 2010. His past roles also include being field CTO for VCE/EMC’s Managed Cloud Services for Converged Systems and an executive consultant for AWS ProServe Enterprise Advisory Services. Additionally Sanjay has served in advisory boards of companies focusing in Database Load-balancing and advanced trainings for virtualization and AI/ML. Sanjay is an alumnus of FinTech professionals from Oxford Said Business School. Sanjay has successfully completed advanced certificates on Design Thinking from Harvard, , Masters in Systems Design and Advanced courses in AI/ML from MIT and Professional MBA from Boston University. Sanjay is also an alumnus of Amazon Machine Learning University. Additionally he is an adjunct professor with Divergence Academy in Dallas. He has been awarded 5 Patents, so far. He is a regular speaker/presenter at Certified Information Security Conference, Quantum Optics and Computing, Annual Hamburg AIML Startup Conference, Oracle Open World, etc. His upcoming book is being published from Apress. He is a life member of ACM , SIAM, AAAI and Senior Member of IEEE and AMA.

Dr. Nitin Sukhija, is a Director of Center of Cybersecurity and Advanced Computing (C2AC), an assistant professor and one of the XSEDE Campus Champion specializes in the area of high performance data analytics and security. He has been involved in research and management of various projects pertaining to the HPC and software challenges in industry and academia for over a decade. Dr. Sukhija chaired and co-chaired many conferences such as ACM XSEDE16, ACM MEDES18, and IEEE WHPBDC(16, 17) conference and is also serving as an active member of the organizing committees of various esteemed (national and international) ACM and IEEE conferences and workshops, such as, XSEDE,IPDPS, PASA, ICPP, ISPDC, WHPBDC, SC EduHPC, SC18 Early Career Program, SIAM CSE Broader Engagement and others. He currently co-chairs the SIGHPC Education Chapter workshop committee and has been active in the planning and participation in HPC Training Workshops series at the SC, ISC and other conferences since 2015.

Through his position with the Shodor Education Foundation, Inc., Scott Lathrop is the Blue Waters Technical Program Manager for Education. Lathrop has been involved in high performance computing and communications activities since 1986. Lathrop coordinates the community engagement activities for the Blue Waters project. He helps ensure that Blue Waters education, outreach and training activities are meeting the needs of the community. Lathrop has been involved in the SC Conference series since 1989, served as a member of the SC Steering Committee for six years. He served as the Conference Chair for the SC’11 and XSEDE14 Conferences. He helped form the International HPC Training Consortium which was merged into the ACM SIGHPC Education Chapter during 2018, and has been active in the planning and participation in HPC Training Workshops at the SC and ISC Conferences.

Dr. Nia Alexandrova is the Training Manager at Hartree Centre. She was a Training Coordinator at BSC, Barcelona (2011- 16) and was involved in PRACE Projects 1-5, as a PRACE Advanced Training Centre coordinator. She has over 17 years of experience as a PG Studies Coordinator and Research Assistant at the School of Systems Engineering and ACET (Advanced Computing and Emerging Technologies) Centre at the University of Reading, at BSC and now at STFC. Her research is in the area of collaborative learning in technology-rich environments in university education and professional training and developing evaluation methodologies for professional training programs. She co-edited and co-authored the book entitled Technological Advances in Interactive Collaborative Learning as well as authored 30 research papers in journals and peer-reviewed conference proceedings, up to date. She is a co-chair of a number of training and education related workshops on HPC and Computational Science Conferences.

Andrew works on future HPC & AI capabilities for Azure, as part of the corporate engineering & product group. He joined Microsoft in early 2020, after nearly 25 years experience in the supercomputing community. Andrew has been an HPC end-user, researcher, software developer, HPC service manager, and impartial consultant. He has been a trusted voice on HPC strategy, technology evaluation and benchmarking, metrics, cost/value models and more. He has been lucky to have had rare exposure to state-of-practice in a wide range of HPC services/facilities across industry, government and academia around the world. Andrew is active on twitter as @hpcnotes.

Marjut manages NVIDIA’s Deep Learning Institute (DLI) in EMEA. In her role, Marjut is responsible for advising corporations, universities, and governments on the importance of AI and why now is the right time for employees to start developing their skills. Over the past four+ years, she has helped over 5000 organizations educate their staff.

Kevin McFall contributes to the NVIDIA Deep Learning Institute (DLI) as a Master Instructor by teaching workshops and supporting DLI certified instructors in the Europe, Middle East, and Africa region. He applies his prior academic experience as an educator and scholar to making the student experience in DLI workshops engaging and informative. His areas of expertise span computer vision, robotics, and autonomous systems.

Thor has an academic background in computational chemistry and materials science. After obtaining his Ph.D. from Stockholm University in 2011 he worked as a postdoc first at University College London and then the University of Iceland, before returning to a researcher position at Stockholm University. In 2016 Thor jumped over to HPC and worked as an application expert in molecular dynamics at the PDC HPC center at KTH. During this time he became increasingly drawn towards teaching workshops and developing training material, both at PDC and within the CodeRefinery project. Thor is passionate about helping researchers write better and more scalable code with less effort, is helping to build a community of research software engineers in the Nordics through the Nordic-RSE initiative, and enjoys programming in Julia.

Dr Mozhgan Kabiri Chimeh is a GPU developer advocate at NVIDIA helping to bring GPU and HPC to growing user community in Europe and around the world. She is a community builder with a passion for open source software and is actively involved in the HPC and RSE communities. As a Software Sustainability Institute fellow, and Research Software Engineer (RSE) advocate, she is actively promoting reproducible and sustainable software, use of HPC and particularly GPUs through training, seminars, research software consultancy and outreach. Prior to joining Nvidia, Mozhgan was a Research Software Engineer in Massive Scale Complex Systems Simulation with Accelerated Computing at the University of Sheffield, UK. She worked in the area of complex system modelling using emerging high-performance parallel architectures. Mozhgan served as the chair of the women in HPC series of workshops at the International Supercomputing Conference and was on the organizing and program committee of leading conferences in the HPC field. She holds a Ph.D. in computer science and a master's degree in Information Technology from the University of Glasgow, UK.

Weronika Filinger is an HPC Applications Consultant working at EPCC, The University of Edinburgh. She has been deeply involved in the design and development of the first Massive Open Online Course (MOOC) on Supercomputing and facilitated all runs of the course. She is teaching Practical Introduction to HPC – a postgraduate online course offered by the University of Edinburgh. For years Weronika has been a member of the EPCC outreach team, taking HPC related activities to public events. She is serving as the co-chair of the Outreach Committee of the ACM SIGHPC Education Chapter and the publicity chair of the International HPC Certification Program. She is also involved in running the International HPC Summer School. Over the years she has worked on a number of collaborative projects such as CRESTA, ADEPT, APES, SARGASSO and DEEP-EST, and provided consultancy for the Software Sustainability Institute.

Dr. Julie Mullen is a member of the technical staff in the MIT Lincoln Laboratory Supercomputing Center (LLSC), where she assists researchers in maximizing their use of high-performance computing resources in order to minimize their time to solution. As an expert in high-performance computing for computational engineering applications, she focuses on redesigning scientific workflows to streamline processing and improve the performance of computational engineering applications. Dr. Mullen leads the design and creation of online professional education courseware for the LLSC. As part of this effort, she facilitates the development of new tools for the Open edX platform to provide support for online Laboratory courseware. Her research includes learning analytics for adaptive learning design and the integration of hands-on physical construction and experimentation with massive open online course technologies. Her work has been published in both the scientific computing and educational domains.

Ann Backhaus has a passion for lifelong learning. Ann lives this passion, as exampled by her doing a ‘refresher’ Teaching and Learning Graduate Certificate “for fun” before joining Pawsey in 2019, even though she already had previous degrees as well as 25 years of experience in training and talent development in private industry and academia. “I enjoy teaching and learning at all levels and in all forms, from designing programs to developing content across a range of platforms,” says Ann.

Richard Lawrence obtained his Bachelor’s degree from the University of California, Davis in 2012 and his Master’s degree in 2018 from Texas A&M University, both in Physics. He has been a graduate student at Texas A&M University since 2014 pursuing his Ph.D., currently in progress. He works under the supervision of his advisor David Toback on a joint project between the Cryogenic Dark Matter Search collaboration and the Quantum Information Science group at Pacific Northwest National Laboratory, studying cryogenic silicon devices. Richard joined the High Performance Research Computing Group at Texas A&M University in 2020 as a User Support Specialist to assist with software maintenance and training for scientific research. He is interested in high-performance computing technologies including containers and machine learning. In his spare time Richard volunteers for a local Girl Scouts troop.

Janis Keuper is full professor for Data Science and Analytics at the Institute for Machine Learning and Analytics (IMLA), Offenburg University and scientific advisor at the "Large Scale Machine Learning" group at the Fraunhofer Competence Center for High Performance Computing. His current research is focused on scalable machine learning systems, especially Deep Learning. Before joining IMLA in 2019, he was a Group Leader at Fraunhofer ITWM and the Intel Visual Computing Institute (Saarbrücken, Germany). Janis was the chair of the Deep Learning tracs at the ISC Supercomputing 2017 and 2018 conference and member of the organizing committee of the "Machine Learning in HPC" Workshop at the ACM Supercomputing 2018/2019 conferences.

Sunna Torge is a senior researcher in the national AI and Big Data competence center ScaDS.AI Dresden/Leipzig at ZIH (TU Dresden). She obtained a diploma in mathematics (minor physics) from the University of Freiburg and a PhD in computer science with focus on mathematical logic and automated deduction. After working in the research group man-machine-interface at Sony International (Europe) and the machine learning group at University of Freiburg she was a full professor for theoretical computer science at the University of Applied Science Furtwangen. After her move to Dresden Sunna Torge worked in machine learning and data analytics groups within the TU Dresden and Fraunhofer Institute for Transportation and Infrastructure Systems with focus on text data analytics. Her main research topics currently are text and sequence analysis on large data sets.

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PD Dr. Juan José Durillo Barrionuevo (male) received the MSc and PhD degrees in computer science from the University of Málaga in 2006 and 2011. From 2011 to 2017, he worked as Assistant Professor at UIBK (Austria), where he also did his habilitation work focusing on workflow scheduling as the main topic. He has authored more than 50 publications in international journals, conferences and books. As a lecturer, he taught courses on optimisation, operating systems, GPU programming and C++. Since 2018, he has worked as a scientist at the BADW-LRZ. His research interests include automatic tuning of scientific applications, workflow scheduling, multi-criteria optimisation, GPU computing, and artificial intelligence.

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Daniel is an assistant professor and in the Electrical Engineering Department at the Technion, working in the areas of machine learning and neural networks. His recent works focus on resource efficiency and implicit bias in neural networks. He did his post-doc working with Prof. Liam Paninski in the Department of Statistics and the Center for Theoretical Neuroscience at Columbia University, and his Ph.D. in the Electrical Engineering Department at the Technion. He is the recipient of the Gruss Lipper Fellowship, the Taub Fellowship, the Goldberg Award, and Intel's Rising Star Faculty Award.

Nico Hoffmann, young investigator group leader. Nico earned his PhD in 2016 from Technische Universität Dresden in medical image analysis. He developed statistical machine learning methods for analysis of intraoperative neuroimaging data of the exposed human brain. He visited the Laboratory of Mathematics in Imaging of Harvard University from 2018 to 2019. During that time, he developed recurrent convolutional neural networks for reconstruction of nerve fibre bundles of the human brain. He is currently heading a Helmholtz AI Young Investigators Group at Helmholtz-Zentrum Dresden-Rossendorf “AI for Future Photon Sciences” researching Physics-guided Neural Networks for PDE learning as well as inverse problems.

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Ahmed Elnaggar is a Ph.D. candidate at the Technical University of Munich. His main focus of research is self-supervised learning on various modalities (Text, Protein, Source code, Images, and speech) using high-performance computing.

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Sadaf R. Alam is Chief Technology Officer (CTO) at the Swiss National Supercomputing Centre (CSCS) in Lugano, Switzerland. Dr. Alam studied computer science at the University of Edinburgh, UK, where she received her Ph.D. in 2004. Until March 2009, she was a computer scientist at the Oak Ridge National Laboratory, USA. In her role as the CTO, she ensures end-to-end integrity of HPC systems and storage solutions and leads strategic projects at the centre. She has held different roles at CSCS including group lead of future systems, chief architect and head of operations. She is a member of ACM, ACM-W, SIGHPC and Women in HPC.

David Hancock is the director for advanced cyberinfrastructure in IU's Research Technologies division. Hancock is responsible for directing IU's local and national high performance computing (HPC), storage, and cloud resources for research. Hancock is the primary investigator for the Jetstream project funded by the National Science Foundation (NSF). He is also responsible for directing IU system administrators who participate in the NSF XSEDE and Wrangler projects. Hancock is an active member in multiple HPC community organizations and currently a member on the board of the Cray User Group where he has served as president and vice president. Hancock is also an elected member of the XSEDE Advisory Board, and a representative in the XSEDE Service Provider (SP) Forum. Previously he served as the vice president for the IBM HPC User Group (SPXXL) and vice chair of the XSEDE SP Forum.

François Tessier has been a Research Scientist at Inria (Rennes, France) since November 2020. He received a Ph.D in Computer Science in 2015 from University of Bordeaux. His thesis focused on topology and affinity-aware process placement and load balancing algorithms for large-scale applications. From 2016 to 2018, he was a postdoctoral appointee at Argonne National Laboratory, IL, USA, within the LCF division (Leadership Computing Facility) where his research work has been more oriented towards I/O optimization in parallel libraries. Before joining Inria, he was a Computational Scientist at ETH Zürich within CSCS (Swiss National Supercomputing Center) located in Lugano, Switzerland, where he addressed the problem of dynamically provisioning of storage resources for HPC applications and large-scale workflows on supercomputers. At Inria, he is now working on various I/O and storage challenges in a context of HPC/Cloud convergence.

David Hancock is the director for advanced cyberinfrastructure in IU's Research Technologies division. Hancock is responsible for directing IU's local and national high performance computing (HPC), storage, and cloud resources for research. Hancock is the primary investigator for the Jetstream project funded by the National Science Foundation (NSF). He is also responsible for directing IU system administrators who participate in the NSF XSEDE and Wrangler projects. Hancock is an active member in multiple HPC community organizations and currently a member on the board of the Cray User Group where he has served as president and vice president. Hancock is also an elected member of the XSEDE Advisory Board, and a representative in the XSEDE Service Provider (SP) Forum. Previously he served as the vice president for the IBM HPC User Group (SPXXL) and vice chair of the XSEDE SP Forum.

Nic Bellingham joined the Met Office as a graduate in 1992 with a degree in Mathematics & Computer Science.  Most of her career has been in IT-focused roles, from developing mainframe and PC applications to working with the Programme that will deliver the Met Office’s Supercomputing capability through to 2032. In 2012 she moved from software engineering into an IT Service Management role, with responsibility for the delivery of a range of operational services, including forecaster applications and public and commercial web offerings. From 2014 to 2016, Nic was Deputy Head of IT Infrastructure & Operations with day-to-day responsibility for all Met Office IT services.  In late 2016, she became Head of IT Infrastructure & Operations, leading the delivery of the Met Office IT estate and associated services. Since April 2019 Nic has been seconded to the Met Office’s Supercomputing Programme, leading the engagement with the Programme from the organisation’s Technology directorate.

Stig has a background in R&D working for various prominent technology companies, particularly in HPC and software-defined networking. Stig is now CTO for StackHPC, a consultancy specialising in the convergence of cloud, HPC and big data. Stig is also co-chair of the OpenStack Scientific Special Interest Group, a globally-distributed grouping of research institutions using OpenStack for research computing use cases

Andrew leads planning of future capabilities for HPC & AI within Microsoft Azure, as part of the corporate engineering & product group. He joined Microsoft in early 2020, after nearly 25 years experience in the supercomputing community. Andrew has been an HPC end-user, researcher, software developer, HPC service manager, and impartial consultant. He has been a trusted voice on HPC strategy, technology evaluation and benchmarking, metrics, cost/value models and more. He has been lucky to have had rare exposure to state-of-practice in a wide range of HPC services/facilities across industry, government and academia around the world. Andrew is active on twitter as @hpcnotes.

Arjun Shankar is a distinguished staff member and the section head for Advanced Technologies in the National Center for Computational Sciences at Oak Ridge National Laboratory (ORNL). He also directs the Compute and Data Environment for Science (CADES) institutional computing capability at ORNL. Arjun’s research in the national laboratory setting has involved designing large-scale data analysis and modeling systems, sensor networking systems, energy grid monitoring and control frameworks, and deploying middleware to overlay data, computation, and control across systems and infrastructure. His sponsored R&D project outputs have several active users in the federal government as well as in the commercial sector. His research has resulted in over seventy peer-reviewed publications including those that address jointly modeling and simulating systems coupled with observational data, incorporating policy constraints, and creating scalable cross-facility data infrastructures. Arjun received his B.Tech. from the Indian Institute of Technology, Mumbai, and his M.S. and Ph.D. in computer science from the University of Illinois, Urbana. He has served on the DOE ASCAC subcommittee on Scientific and Technical Information, is a member of the AAAS, and a Senior Member of the ACM and the IEEE.

Bjoern Enders joined NERSC in 2019 as a Data Science Workflows Architect in the Data Science Engagement Group where he liaises with various large-scale experimental facilities, engages with the wider scientific workflows community and contributes to NERSC's API efforts. He works towards a future where HPC resources integrate seamlessly and effortlessly into experimental science workflows. Bjoern has a background in software development for experimental sciences with a specialization for computational microscopy at synchrotron light sources. He holds a PhD in Physics from the Technical University of Munich, Germany and a MSc equivalent degree in physics from the University of Goettingen, Germany.

Gabor has decades of experience building, maintaining and debugging large-scale web applications. He started his career at Berkeley Lab in the 1990-s. A few years later, he worked as a back-end and fullstack software engineer for various start-ups and larger companies. After about 20 years in the private sector, he is now working for NERSC and couldn't be more excited to use his experience to make computing for science run smoother. Gabor's recent contributions are Iris, the NERSC banking and account management system, as well as the Superfacility API which allows for programmatic access to NERSC resources.

Christopher Haine earned in 2017 a Ph.D. from the University of Bordeaux, on the topic of loop kernel optimisation and data layout restructuring. Christopher then joined Cray (now HPE) in the HPC/AI EMEA Research Lab, where he focuses on data-aware middleware, data movement in complex memory hierarchies, and optimisation and programmability of scientific applications and workflows.

Florina Ciorba is an Associate Professor of High Performance Computing at the University of Basel, Switzerland. She received her Diploma in Computer Engineering in 2001 from University of Oradea, Romania and her doctoral degree in Computer Engineering in 2008 from National Technical University of Athens, Greece. She has held postdoctoral research associate positions at the Center for Advanced Vehicular Systems at Mississippi State University, Mississippi State, USA (2008 to 2010) and at the Center for Information Services and High Performance Computing at Technische Universität Dresden, Dresden Germany (2010-2015). Her research interests include parallelization, dynamic load balancing, loop scheduling, robustness, resilience, scalability, reproducibility of scientific applications executing on small to large scale parallel computing systems, and system and application monitoring for improving their operations. More information at https://hpc.dmi.unibas.ch/en/people/florina-ciorba/

Daniele Tafani received his PhD in Electronic Engineering from Dublin City University (DCU) in 2012, where he conducted research on analytic modelling and resource optimisation of optical burst switched networks. He worked at the IBM Tivoli Rome Labs as a software engineer, and was a visiting researcher at the University of Ottawa, where he developed algorithms for energy-efficient light paths in computational grids. Daniele spent 8 years as a research scientist in the High-Performance Systems division of the Leibniz Supercomputing Centre (LRZ), focusing his interests on energy efficiency of HPC systems, scalable sensor monitoring and operational data analytics. He is now Technical Product Manager at Fujitsu.

Utz-Uwe Haus is a Senior Research Engineer at CRAY. He studied Mathematics and Computer Science at the TU Berlin. After obtaining a Doctorate in Mathematics at the University of Magdeburg he worked on nonstandard applications of Mathematical Optimization in Chemical Engineering, Material Science and Systems Biology. After 5 years as a Senior Researcher at the Department of Mathematics at ETH Zürich he is now leading the Cray European Research Lab in Basel, developing the Mathematical Optimization and Operations Research group, working on data-dependency driven workflow optimization on future HPC architectures.

Nicolas Lachiche received his PhD in Computer Science from the University of Nancy, France in 1997, where he conducted research on machine learning. After a postdoc at the University of Bristol, he joined the University of Strasbourg as an associate professor. He is the head of the Data Science and Knowledge research group in the ICube laboratory. His research interests are in mining relational or sequential data.

Ann Gentile is the Manager of the HPC Development Department at Sandia National Laboratories. Prior to that, she was a Distinguished Member of Technical Staff and she continues her interests in Resource-Aware Computing in her current role. Ann is a co-author of the R&D 100 award-winning, open source Lightweight Distributed Metric Service (LDMS) which is deployed at large-scale HPC sites within the US national labs and the NSF for monitoring and resource utilization understanding on large-scale HPC systems. HPE/Cray has implemented LDMS in its monitoring solution to be part of every currently announced NNSA exascale machine. Ann serves on investment area teams determining priorities for Sandia’s Computational CoDesign and Trusted AI Research and on evaluation teams of extreme-scale architectures for the US national labs. Ann is also a co-founder of the Workshop on Monitoring and Analysis for High Performance Computing Systems Plus Applications (HPCMASPA), now in its 9th year held in conjunction with IEEE Cluster. She earned her Ph.D. in Chemical Physics and M.S. in Chemistry from UIUC and her B.S. in Physics from Carnegie-Mellon University.

Natalie Bates has led the Energy Efficient High Performance Computing Working Group (EE HPC WG) since its inception in 2010. The purpose of the WG is to drive implementation of energy efficient design in HPC. Today, there are ~800 members from 25+ countries. Natalie has been the technical and executive leader for this ‘open source’ working group that disseminates best practices, shares information (peer to peer exchange), and takes collective action. The EE HPC WG has collaborated and negotiated with industry standards committees and major HPC organizations as well as influenced HPC system development. Prior to leading the EE HPC WG, Natalie's career spanned twenty years with Intel Corporation where she was a senior manager of highly complex programs taking new products to market, delivering multi-component and multi-partner platforms, and negotiating strategic technical industry initiatives.

Torsten is a system architect for Exascale monitoring and system power and energy management at Hewlett Packard Enterprise (HPE). His research activities are related to high volume, high frequency data collection and analytics for improved IT operations as well as dynamic power management. He is the lead architect for HPE's Exascale monitoring framework developed as part of the ECP funded PathForward project. Torsten is part of the leadership team of the Energy Efficient High Performance Computing Working Group (EE HPC WG) and currently serves as the Workshop and Conferences Co-Chair. Torsten received his MSc in parallel and scientific computation from the University of Liverpool, UK, and a MSc in Computer Engineering from the University of Applied Sciences in Berlin, Germany. He received his Dr. rer. nat. degree ​in computer science from the Technical University of Munich, Germany, in 2018.

Ales Zamuda received his B.Sc., M.Sc., and Ph.D. degrees in computer science from University of Maribor, Slovenia, in 2006, 2008, and 2012, respectively. As an affiliate of Faculty of Electrical Engineering and Computer Science at the University of Maribor he acts within research group Computer Architecture and Languages Laboratory and programme-funded unit Computer Systems, Methodologies, and Intelligent Services. His areas of interest include evolutionary algorithms, multicriterion optimization, artificial life, and computer animation. He has written over 50 scientific papers and among them several journal papers ranked in first quarter of computer science category such as Applied Soft Computing and Information Sciences and received several citations of his scientific works.

Martin Molan is a PhD student of data science and computation at University of Bologna. He has received BA in mathematics at University of Ljubljana and MA in ICT at JSI institute. As a student he has collaborated with CERN openlab, UCL center for AI, UNESCO International Research Center On Artificial Intelligence, and CINECA.

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Michael Alexander holds degrees in electrical engineering (TGM), business administration (University of Southern California) and economics (University of Vienna). He is currently performing large data analytics for multiple domains and the architecting of clusters. His professional experience includes education and product management at IBM, and Alcatel. Prior he was a HPC Specialist at TU Wien and a Product Line Manager for Alcatel ADSL and Optical Access Networks. He is the author of a textbook on networks and network security published by Hüthig/Verlagsgruppe Süddeutsche, and editor of a special issue on mathematical methods in network management of the Wiley International Journal of Network Management. For the last sixteen years, he has served as the Program Committee Chair for VHPC, Workshop on Virtualization in High-Performance Cloud Computing. His current research interests include content centric networking, distributed databases, virtualization system-network management.

With over 12 years of experience in Virtualization technologies, Anastassios Nanos is currently working on the lower-level parts of the stack to attack issues related to performance, scalability, power-efficiency, and security in hypervisors. Previously, he was a post-doc at CSLab, NTUA, working on bridging the gap between common HPC practices and virtualization. His research interests include I/O Virtualization, systems software for high-performance I/O in virtualized environments, systems support for heterogeneous platforms, communication architectures for clusters, and scalable storage architectures based on clusters. He holds a Diploma in Engineering (2006) from ECE, NTUA and a PhD in Computer Engineering (2013) from NTUA. He has been involved in EU-funded projects, conducting research in emerging, power-efficient micro-server architectures on scalable network and storage I/O, and energy-driven resource management in cloud architectures.

With over 12 years of experience in Virtualization technologies, Anastassios Nanos is currently working on the lower-level parts of the stack to attack issues related to performance, scalability, power-efficiency, and security in hypervisors. Previously, he was a post-doc at CSLab, NTUA, working on bridging the gap between common HPC practices and virtualization. His research interests include I/O Virtualization, systems software for high-performance I/O in virtualized environments, systems support for heterogeneous platforms, communication architectures for clusters, and scalable storage architectures based on clusters. He holds a Diploma in Engineering (2006) from ECE, NTUA and a PhD in Computer Engineering (2013) from NTUA. He has been involved in EU-funded projects, conducting research in emerging, power-efficient micro-server architectures on scalable network and storage I/O, and energy-driven resource management in cloud architectures.

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Valeriu Codreanu studied Electrical Engineering and got his MSc at the Polytechnic University of Bucharest. He followed-up with a PhD in Computer Architecture at the same institute, graduating in 2011. Valeriu continued as a researcher at Eindhoven University of Technology and University of Groningen, working on GPU computing, computer vision, and embedded systems. In 2014, he joined SURFsara as an HPC consultant, and in 2016 he became the PI of an Intel Parallel Computing Center project on ‘Scaling up deep learning’. Valeriu is currently leading the High-Performance Machine Learning group at SURFsara, and is focused on applying deep learning techniques to real-world applications from various scientific fields.

Dr. Ian Foster is the Director of Argonne’s Data Science and Learning Division, Argonne Senior Scientist and Distinguished Fellow and the Arthur Holly Compton Distinguished Service Professor of Computer Science at the University of Chicago. Foster’s research contributions span high-performance computing, distributed systems, and data-driven discovery. He has published hundreds of scientific papers and eight books on these and other topics. Methods and software developed under his leadership underpin many large national and international cyberinfrastructures. Foster received a BSc (Hons I) degree from the University of Canterbury, New Zealand, and a PhD from Imperial College, United Kingdom, both in computer science. His awards include the Global Information Infrastructure (GII) Next Generation award, the British Computer Society’s Lovelace Medal, R&D Magazine’s Innovator of the Year, the IEEE Tsutomu Kanai award.

Dr. Zhao Zhang is a computer scientist at Texas Advanced Computing Center. His current research focus is scalable deep learning on supercomputers. Dr. Zhang's past work include astronomy data processing with Apache Spark, machine learning diagnostics, and I/O optimization for many-task computing applications on supercomputers, such as Argonne's IBM Blue Gene/P. Before joining TACC, Dr. Zhang was a postdoc researcher in AMPLab and a data science fellow at Berkeley Institute for Data Science at University of California, Berkeley, working with Prof. Michael J. Franklin. He received Ph.D in computer science from University of Chicago in 2014 under supervision of Prof. Ian T. Foster.

Torsten is a Professor of Computer Science at ETH Zürich, Switzerland. He is also a key member of the Message Passing Interface (MPI) Forum where he chairs the "Collective Operations and Topologies" working group. His research interests revolve around the central topic of "Performance-centric System Design" and include scalable networks, parallel programming techniques, and performance modeling. Torsten won best paper awards at the ACM/IEEE Supercomputing Conference SC10, SC13, SC14, SC19, EuroMPI'13, HPDC'15, HPDC'16, IPDPS'15, and other conferences. He published numerous peer-reviewed scientific conference and journal articles and authored chapters of the MPI-2.2 and MPI-3.0 standards. He received the Gordon Bell Prize, the Latsis prize of ETH Zurich, as well as ERC starting and consolidator grants. Additional information about Torsten can be found on his homepage at htor.inf.ethz.ch.

Arvind Ramanathan is a computational biologist in the Data Science and Learning Division at Argonne National Laboratory and a senior scientist at the University of Chicago Consortium for Advanced Science and Engineering (CASE). His research interests are at the intersection of data science, high performance computing and biological/biomedical sciences. His research focuses on developing scalable statistical inference techniques for studying complex biological phenomena. He obtained his Ph.D. in computational biology from Carnegie Mellon University, and was the team lead for integrative systems biology team at Oak Ridge National Laboratory. More information about his group and research interests can be found at http://​ramanathanlab​.org.

Alexandre Bonvin studied Chemistry at Lausanne University, Switzerland and obtained his PhD at Utrecht University in the Netherlands (1993). After two post-docs at Yale (USA) and the ETHZ (CH) he joined Utrecht University in 1998 where I was appointed full professor of computational structural biology in 2009. He is currently Scientific Director of the Bijvoet Centre for Biomolecular Research. His group is developing and operating the HADDOCK integrative modelling platform.

Manon Réau studied Biotechnologies at Sup’Biotech Paris and In Silico Drug Design at the University of Paris. She obtained her PhD in bioinformatics at the Conservatoire National des Arts et Métiers in 2019 and joined Utrecht University in 2020 to study different computational approaches to predict and understand molecular interactions. During this post-doc, she specialized in deep learning, and developed Deeprank-GNN in collaboration with the eScience Center, Amsterdam.

Stefan graduated from the Technical University in Aachen with a Master’s in Physics and went to a Stuttgart for a PHD on soft matter physics simulating DNA. He moved to industry to different data science positions. In 2020 he joined the Jülich Supercomputing Center to head a group of AI consultants supporting scientists from various domains in applying AI methods on supercomputers.

Jonas is currently the "AI for Oncology" group leader at the Netherlands Cancer Institute. Previously, after his studies in Applied Mathematics at the Delft University of Technology he completed his PhD titled "Shedding new light on Gaussian harmonic analysis" at the same university. He started as a postdoctoral researcher in 2016 at the Netherlands Cancer Institute/Antoni van Leeuwenhoek hospital and continued within the Diagnostic Image Analysis Group at the Radboud Medical Center. His current work focuses on efficient deep learning algorithms for cancer detection in breast image modalities.

Chen Liu is a Principal Hardware Engineer at Sambanova Systems, leading the development of multiple HPC applications that leverage Sambanova's Software & Hardware stack, achieving State-of-the-Art performance and accuracy. He is working on the verification, performance and productization on Sambanova's solutions, ensuring coordination, concurrency and correctness of scalable HPC/ML applications with reconfigurable dataflow architecture.

Pete Beckman is the co-director of the Northwestern-Argonne Institute for Science and Engineering. From 2008-2010 he was the director of the Argonne Leadership Computing Facility, where he led the Argonne team working with IBM on the design of Mira, a 10 petaflop Blue Gene/Q. Pete coordinates the collaborative research activities in extreme-scale computing between the US Department of Energy and Japan’s ministry of education, science, and technology (MEXT), and leads Argo, an Exascale Computing Project focused on low-level resource management for the OS and runtime. He is the founder and leader of the Waggle project for AI@Edge. The Waggle technology and software framework is being used by the Chicago Array of Things project and is deployed in over 10 cities around the world. Dr. Beckman has a Ph.D. in Computer Science from Indiana University (1993)

Swann Perarnau is an Assistant Computer Scientist at Argonne. He leads the topology, memory and power management efforts for the Argo ECP project. In particular, he is designing low-level system software mechanisms to help applications discover the features and performance of complex heterogeneous hardware, as well as composable abstractions to make the most efficient use of it.

Rosa M. Badia holds a PhD from the UPC (1994). She is the manager of the Workflows and Distributed computing group at the Barcelona Supercomputing Center (BSC). She is a Scientific Researcher at the Spanish National Research Council (CSIC). She graduated on Computer Science at the Facultat d' Informàtica de Barcelona (UPC, 1989). She was lecturing and doing research at the Computer Architecture Department (DAC) at the UPC from 1989 to 2008, where she held an Associate Professor position from 1997 to 2008; she is currently part-time lecturing again at the same department.

Kentaro Sano is the team leader of the Processor Research team at RIKEN. Dr. Kentaro Sano received his Ph.D. from GSIS, Tohoku University, in 2000. Since 2000 until 2005, he had been a Research Associate at Tohoku University. Since 2005 until 2018, he has been an Associate Professor at Tohoku University. He was a visiting researcher at the Department of Computing, Imperial College, London, and Maxeler corporation in 2006 and 2007. Since 2017 until present, he has been a team leader of a processor research team at R-CCS, Riken. His research interests include FPGA-based high-performance reconfigurable computing systems especially for scientific numerical simulations and machine learning, high-level synthesis compilers and tools for reconfigurable custom computing machines, and system architectures for next-generation supercomputing based on the data-flow computing model.

Valentin Reis is a Software Engineer at Groq, Inc. He previously was a Postdoctoral appointee at Argonne National Laboratory and obtained his PhD from the University of Grenoble Alpes. His interests span machine learning, functional programming and HPC infrastructure.

Prasanna Balaprakash is a computer scientist with a joint appointment in the Mathematics and Computer Science Division and the Leadership Computing Facility at Argonne National Laboratory. His research work spans the areas of artificial intelligence, machine learning, optimization, and high-performance computing. He is a recipient of the U.S. Department of Energy 2018 Early Career Award. Prior to Argonne, he worked as a Chief Technology Officer at Mentis Sprl, a machine learning startup in Brussels, Belgium. He received his PhD from CoDE-IRIDIA (AI Lab), Université Libre de Bruxelles, Brussels, Belgium, where he was a recipient of European Commission’s Marie Curie and Belgian F.R.S-FNRS Aspirant fellowships.

Rob Schreiber is a Distinguished Engineer at Cerebras Systems, Inc., where he works on architecture and programming of systems for accelerated training of deep neural networks. Before Cerebras he taught at Stanford and RPI and worked at NASA, at startups, and at HP. Schreiber’s research spans sequential and parallel algorithms for matrix computation, compiler optimization for parallel languages, and high performance computer design. With Moler and Gilbert, he developed the sparse matrix extension of Matlab. He created the NAS CG parallel benchmark. He was a designer of the High Performance Fortran language. Rob led the development at HP of a system for synthesis of custom hardware accelerators. He has help pioneer the exploitation of photonic signaling in processors and networks. He is an ACM Fellow, a SIAM Fellow, and was awarded, in 2012, the Career Prize from the SIAM Activity Group in Supercomputing.

Tony Hey is a Fellow of the Royal Academy of Engineering, the Association for Computing Machinery, and the American Association for the Advancement of Science. At the University of Southampton in the UK, his parallel computing research group designed and built one of the first distributed memory message-passing computers using innovative Inmos transputers. He was later Head of the Electronics and Computer Science Department at Southampton and also Dean of Engineering. In 2005 he was awarded a CBE for Services to Science after leading the UK’s eScience initiative. After 10 years as Corporate Vice President for Technical Computing in Microsoft in the US, he returned to the UK and has been Chief Data Scientist at STFC’s Rutherford Appleton Laboratory since 2015. He was one of the originators of the MPI message passing standard in 1992 and was awarded the 2019 Lifetime Achievement Award by the International Open Benchmark Council. In 2020 he chaired a US Department of Energy subcommittee that explored ‘the opportunities and challenges from Artificial Intelligence and Machine Learning for the advancement of science and technology’ or, as a shorthand, ‘AI for Science’.

Michaela Blott is a Distinguished Engineer at Xilinx Research in Dublin, Ireland, where she heads a team of international scientists driving exciting research to define new application domains for Xilinx devices, such as machine learning, in both embedded and hyperscale deployments. She earned her Master’s degree from the University of Kaiserslautern in Germany and has over 25 years of experience in leading edge computer architecture and advanced FPGA and board design, in research institutions (ETH Zurich and Bell Labs) and development organizations. She is heavily involved with the international research community serving as the technical co-chair of FPL’2018, workshop organizer (H2RC), industry advisor on numerous EU projects, member of numerous technical program committees (FPL, ISFPGA, DATE, etc.) and winner of the WMB award in 2015 and finalist of VentureBeat Women in AI’2019, and Women in Technology‘2019 awards.

Tianjian Lu is currently a software engineer at Google Research. He received the B.E. degree from the National University of Singapore in 2010, and the M.S. and Ph.D. degrees from the University of Illinois at Urbana-Champaign in 2012 and 2016, respectively, all in electrical engineering. His research interests include multiphysics modeling and simulation, high-performance computing, and machine learning. He was the recipient of the Best Student Paper Award (The First Place Winner) at the 31st International Review of Progress in ACES, Williamsburg, VA, USA, in 2015, the Best Student Paper Award at the IEEE Electrical Design of Advanced Packaging and Systems, Honolulu, HI, USA, in 2016, and the P. D. Coleman Outstanding Research Award by the Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, in 2016.

Haohuan Fu is a professor in the Ministry of Education Key Laboratory for Earth System Modeling, and Department of Earth System Science in Tsinghua University, where he leads the research group of High Performance Geo-Computing (HPGC). He is also the deputy director of the National Supercomputing Center in Wuxi, leading the research and development division. Fu has a PhD in computing from Imperial College London. His research work focuses on providing both the most efficient simulation platforms and the most intelligent data management and analysis platforms for geoscience applications, leading to two consecutive winning of the ACM Gordon Bell Prizes (nonhydrostatic atmospheric dynamic solver in 2016, and nonlinear earthquake simulation in 2017).

Ryousei Takano is a senior researcher of the Institute of Advanced Industrial Science and Technology (AIST), Japan. He received his Ph.D. from the Tokyo University of Agriculture and Technology in 2008. He joined AXE, Inc. in 2003 and then, in 2008, moved to AIST. His research interests include operating systems and parallel and distributed computing. He is currently exploring system software for enabling a computing continuum.

Hatem Ltaief is a Principal Research Scientist in the Extreme Computing Research Center at KAUST, where is also advising several KAUST students in their MS and PhD research. His research interests include parallel numerical algorithms, parallel programming models, performance optimizations for manycore architectures and high performance computing. Hatem received the engineering degree from Polytech Lyon at the University of Claude Bernard Lyon I, the MSc in applied mathematics and the PhD degree in computer science at the University of Houston. He has contributed to the integration of numerical algorithms into mainstream vendors’ scientific libraries, such as NVIDIA cuBLAS and Cray LibSci. He has been collaborating with domain scientists, i.e., astronomers, statisticians, computational chemists and geophysicists, on leveraging their applications to meet the challenges at exascale.

Bilel Hadri is a computational scientist at the Supercomputing Lab at KAUST since July 2013. He is leading efforts in benchmarking and performance optimization and helping in coordinating strategic efforts for systems procurements, upgrades and provides regular training to users. He received his Master in Applied Mathematics and his PhD in Computer Science from the University of Houston in 2008. He joined the National Institute for Computational Science at Oak Ridge National Lab as a computational scientist in December 2009 following a Postdoctoral Position in June 2008 at the University of Tennessee Innovative Computing Laboratory lead by Dr. Jack Dongarra. His expertise area includes Linear Algebra, Numerical Analysis, Performance Analysis Tuning and Optimization, System Utilization Analysis, Monitoring and Library Tracking Usage.

David Keyes directs the Extreme Computing Research Center at the King Abdullah University of Science and Technology (KAUST), where he was the founding Dean of the Division of Mathematical and Computer Sciences and Engineering in 2009 and currently serves in the Office of the President as Senior Associate for strategic priorities and institutional partnerships. He works at the interface between parallel computing and partial differential equations and statistics, with a current focus on scalable algorithms exploiting data sparsity in the context of the HiCMA software library. David Keyes received the BSE degree in aerospace and mechanical sciences from Princeton University, in 1978, and the PhD degree in applied mathematics from Harvard University, in 1984. He works at the interface between parallel computing and the numerical analysis of PDEs, with a focus on scalable implicit solvers. He helped develop and popularize the Newton-Krylov-Schwarz (NKS), Additive Schwarz Preconditioned Inexact Newton (ASPIN), and Algebraic Fast Multipole (AFM) methods. He is a fellow of the SIAM, AMS, and AAAS and has been awarded the ACM Gordon Bell Prize, the IEEE Sidney Fernbach Award, and the SIAM Prize for Distinguished Service to the Profession.

Daniel Grünewald received a PhD in theoretical high energy physics from Ruprecht-Karls-Universität Heidelberg, Germany in 2008. He joined the Competence Center for High Performance Computing (CC-HPC) at the Fraunhofer institute for industrial mathematics (Fraunhofer ITWM) in Kaiserlautern, Germany in 2009. He works at the interface between the low level HPC tools developed at CC-HPC and their application in large scale simulations. He has provided major contributions to the development of the Gaspi specification, a PGAS communication API striving for extreme scalability. His current focus is on the extension of the GPI-2 ecosystem. GPI-2 is the Gaspi reference implementation developed at CC-HPC. Part of this effort is GaspiLS, a Gaspi based linear solver library providing an abstract high level linear algebra interface which hides the complexity of a scalable and hybrid parallel implementation from the domain expert.

Laura Grigori is a senior research scientist at INRIA in France, where she leads the Alpines group, a joint group between INRIA and the J.L. Lions Laboratory, Sorbonne University, in Paris. She leads several projects on preconditioning, communication avoiding algorithms and associated numerical libraries for large scale parallel/multicore machines. After postdoctoral research at the University of California, Berkeley and the Lawrence Berkeley National Laboratory, she became a researcher for INRIA in 2004, and became the head of the Alpines project in 2013. In 2020 Grigori was named a SIAM Fellow "for contributions to numerical linear algebra, including communication-avoiding algorithms". In 2021, she joined the SIAM Council as a Member-at-Large.

Alfredo is the Principal Investigator of the SOLHARIS project that aims at developing algorithms, programming models and scheduling methods that improve the scalability of sparse linear algebra solvers and, in general, of scientific computing libraries, on large scale parallel hand heterogeneous supercomputers. His research activity focuses on Computational Linear Algebra. This discipline deals with the issues related to the efficient and numerically reliable computation of linear algebra operations arising in numerous scientific and industrial applications from a wide range of domains including physics, chemistry or data analysis.

Hartwig Anzt is a Helmholtz-Young-Investigator Group leader at the Steinbuch Centre for Computing at the Karlsruhe Institute of Technology. Where he obtained his PhD in Mathematics He joined Jack Dongarra's Innovative Computing Lab at the University of Tennessee in 2013. Since 2015 he also holds a Senior Research Scientist position at the University of Tennessee. He teaches courses on numerics for HPC and related topics, including scientific computing and machine learning on modern architectures. In 2017, he contributed to the ISC-tutorial on Numerical Linear Algebra. Hartwig Anzt has a long track record of high-quality software development. He is author of the MAGMA-Sparse and lead and developer of the Ginkgo numerical linear algebra library, both part of the US Exascale Computing Project for production-ready numerical linear algebra. According to Google Scholar, Hartwig Anzt authored more than 60 journal and conference articles, and has an h-index of 16 and an i10-index of 31.

Ulrike Meier Yang leads the Mathematical Algorithms and Computing group in the Center for Applied Scientific Computing at LLNL. She leads the xSDK4ECP (Extreme-scale Scientific Software Development Kit for the ECP) project, which is part of the Software Technologies component of the Exascale Computing Project (ECP). She is a member of the Scalable Linear Solvers and hypre project, and the Linear Solvers Topical Area Lead in the SciDAC FASTMath Institute. Her research interests are numerical algorithms, particularly iterative linear system solvers and algebraic multigrid methods, high performance computing, parallel algorithms, performance evaluation and scientific software design. She is serving on the editorial boards of SIAM Journal for Matrix Analysis and Applications and Journal of Parallel and Distributed Computing. Prior to joining LLNL in 1998, she was a staff member in the Center for Supercomputing Research and Development at the University of Illinois at Urbana-Champaign (1985-1995) and in the Central Institute of Applied Mathematics at the Research Centre Jülich, Germany (1983-1985). She earned her Ph.D. in Computer Science at the University of Illinois at Urbana-Champaign in 1995 and a Diplom in mathematics at the Ruhr-University Bochum, Germany, in 1983.

John Shalf is Department Head for Computer Science Lawrence Berkeley National Laboratory, and recently was deputy director of Hardware Technology for the DOE Exascale Computing Project. Shalf is a coauthor of over 80 publications in the field of parallel computing software and HPC technology, including three best papers and the widely cited report “The Landscape of Parallel Computing Research: A View from Berkeley” (with David Patterson and others). Prior to coming to Berkeley Laboratory, John worked at the National Center for Supercomputing Applications and the Max Planck Institute for Gravitation Physics/Albert Einstein Institute (AEI) where he was a co-creator of the Cactus Computational Toolkit.

Cristiano Malossi is Manager of the AI Automation group at IBM Research - Zurich. The group focuses on creating solutions for scalable AI model development and deployment on Cloud and High-Performance on-prem systems. Since 2017 Cristiano is coordinator of the FET-H2020 OPRECOMP project, with focus on low-power/low-energy computing paradigms based on approximation and transprecision. Cristiano is a recipient of the 2016 IPDPS Best Paper Award and the 2015 ACM Gordon Bell Prize. Since 2015 he is also member of ACM and SIAM societies, and he is part of Technical Program committee of top conferences, including SC, ISC, and DATE. Before IBM, Cristiano graduated from the Swiss Federal Institute of Technology in Lausanne (EPFL) in Lausanne with a PhD in applied mathematics. In 2013, his thesis granted him the IBM Research Prize for Scientific Computing. Cristiano has also a B.Sc. in Aerospace Engineering and a M.Sc. in Aeronautical Engineering from the Politecnico di Milano (Italy).

Luca Benini holds the chair of digital Circuits and systems at ETHZ and is Full Professor at the Universitá di Bologna. Dr. Benini's research interests are in energy-efficient system design for embedded and high-performance computing. He is also active in the area of energy-efficient smart sensors and ultra-low power VLSI design. He was a co-recipient of the GAUSS Award at ISC 2016 for his work on energy-efficient schedulers for HPC. He has published more than 800 papers, five books and several book chapters. He is a Fellow of the IEEE and the ACM and a member of the Academia Europaea. He is the recipient of the 2016 IEEE CAS Mac Van Valkenburg award.

Norbert Wehn holds the chair for Microelectronic System Design in the department of Electrical Engineering and Information Technology at the University of Kaiserslautern. He received his Diploma and PhD from the TU Darmstadt in Germany. He is associate editor of various journals and member of several scientific industrial advisory boards. He has more than 350 publications in various fields of microelectronic system design and holds 20 patents. His special research interests are VLSI-architectures for mobile communication, forward error correction techniques, low-power techniques, advanced SoC and memory architectures, 3D integration, reliability issues in SoC, IoT and hardware accelerators for big data applications.

Roger Woods has held the chair of Digital Systems at Queen’s University of Belfast since 2003. He has an established record of research into embedded and computing systems, particularly field programmable gate arrays (FPGAs) and has published over 240 papers. He is on the advisory board to the IEEE Signal Processing Society Technical Committee on the Design and Implementation of Signal Processing Systems and a member of the UK’s research council ICT Strategic Advisory Team advising on future computing. He is a programme committee member of numerous technology conferences, e.g. FPL, FPT, SIPS and ARC. He has had a portfolio of research funding of nearly £6M over the past 5 years and recently, was successful in securing funding to establish a £2.1M Tier-2 HPC centre called Kelvin-2 at Queen’s University. He is a co-founder and Chief Scientist of Analytics Engines Ltd., a 23-person company involved in producing data analytics solutions.

Andrew Emerson graduated in Chemistry from the University of Southampton (UK) in 1987. He stayed in Southampton to study for a doctorate in computational chemistry which was awarded in 1991. After many years in research in the UK and Italy in the field of molecular dynamics, he joined in 2000 the Cineca supercomputer centre located in Bologna, Italy as an applications specialist. He currently works at Cineca in the high level support team and in a number of European projects, including PRACE, and gives courses on computational chemistry and parallel computing. In 1997 he was awarded the title “Young Scientist of the Year” by the British Liquid Crystal society. He is married with one child and lives in Bologna.

Frank K.Gürkaynak obtained his B.Sc. and M.Sc. degrees from the Istanbul Technical University, and his Ph.D. degree from the Integrated Systems Laboratory of ETH Zurich. Since 2008 he is with the Microelectronics Design Center of ETH Zurich, involved in research and teaching on the design and test of digital integrated circuits and is a member of the PULP project. He actively contribute to research in the following fields: Ultra-low-power processor design, design and test of digital integrated circuits and system design, cryptographic Hardware and Open Source Hardware.

Alberto Bosio received the PhD in Computer Engineering from the Politecnico di Torino, Italy in 2006. From 2007 to 2018 he was an Associate Professor at LIRMM - University of Montpellier in France. Hi is now a Full Professor the INL – Ecole Centrale de Lyon, France. His research interests include Approximate Computing, In-Memory Computing, Test and Diagnosis of Digital circuits and systems and Reliability. He co-authored 1 book, 3 patents 35 journals, and over 120 conference papers. He is the chair of the ETTTC. He is a member of the IEEE.

Dimitrios Nikolopoulos is the John W. Hancock Professor of Engineering, Professor in Computer Science and Professor (by courtesy) in Electrical and Computer Engineering at Virginia Tech. His current research interests are in virtualization technologies for scalable computing and memory management for large-scale heterogeneous systems. Nikolopoulos has led numerous collaborative research and technology transfer efforts in these areas. He is a recipient of major faculty investigator awards (NSF, DOE, Royal Society, SFI), industry awards (IBM), and nine Best Paper awards from ACM and the IEEE. He received BEng (1996), MSc (1997) and PhD (2000) degrees from the University of Patras.

Dr. Christos Bouganis received the M.Eng degree in Computer Engineering and Informatics from University of Patras Greece in 1998, the MSc degree in Communications and Signal Processing in 1999 and the Ph.D. degree in 2004 both from Imperial College London. He joined the Department of Electrical and Electronic Engineering as academic faculty in 2007. He is currently a Reader in Intelligent Digital Systems with the Department of Electrical and Electronic Engineering, the Director of Postgraduate Studies of the department and leads the Intelligent Digital Systems Lab (iDSL). His research inlcudes the theory and practice of reconfigurable computing and design automation, mainly targeting digital signal processing algorithms. His work is currently focused on Machine Learning, Computer Vision and Image Processing, Markov Chain Monte Carlo Systems, and computing with unreliable hardware. He currently serves on the program committees of many international conferences, including FCCM, FPL, FPT, DATE, SPPRA, and VLSI-SoC and is an editorial board member of IET Computers and Digital Techniques and Journal of Systems Architecture.

Enrique S. Quintana-Ortí received the bachelor and Ph.D. degrees in computer sciences from the Universidad Politecnica de Valencia, Spain, in 1992 and 1996, respectively. Currently, he is a Professor in Computer Architecture in the Universidad Jaume I, Castellón, Spain. He has published more than 200 papers in international conferences and journals, and has contributed to software libraries like PLiC/SLICOT, MAGMA, FLARE, BLIS and libflame for control theory and parallel linear algebra. He has also been member of the programme committe for around 100 international conferences. In 2008 Enrique received an NVIDIA professor partnership award for his contributions to the acceleration of dense linear algebra kernels on graphics processors, and he also received two awards from NASA for his contributions to fault-tolerant dense linear algebra libraries for space vehicles. Recently, he has participated/participates in EU projects on parallel programming, such as TEXT, INTERTWinE, and energy efficiency such as EXA2GREEN and OPRECOMP. His current research interests include parallel programming, linear algebra, energy consumption, transprecision computing and bioinformatics as well as advanced architectures and hardware accelerators.

Jonathan is currently a staff computer architecture researcher focusing on next generation architectures for Big Data beyond exascale. Jonathan also has served as a technical advisor to many start-up companies, and has given talks ranging from C++ parallel runtimes to debating exascale memory architectures at Supercomputing. Jonathan Beard received a BS (Biology) and BA (International Studies) in 2005 from the Louisiana State University, MS (Bioinformatics) in 2010 from The Johns Hopkins University, and a PhD in Computer Science from Washington University in St. Louis in 2015. Jonathan served as a U.S. Army Officer where he served in roles ranging from medical administrator, to Aide-de-Camp, to acting director of the medical informatics department for the U.S. Army in Europe. Jonathan's research interests also include online modeling of stream/data-flow parallel systems and extremely heterogeneous systems.

Jeffrey (Jeff) Young is a research scientist in Georgia Tech's School of Computer Science and the managing director of the Arm HPC User Group. His main research interests include investigating scheduling and data movement for accelerators like GPU and Xeon Phi and working to model and map algorithms to high-performance architectures. He is currently working on a collaborative research program that is focused on mapping bandwidth-intensive algorithms to 3D stacked memories like Hybrid Memory Cube (HMC) and High Bandwidth Memory (HBM) and on performing near-memory computation on devices like FPGAs and GPUs. He received his PhD in computer engineering in 2013 from Georgia Tech's ECE department.

Roxana Rusitoru is a Senior Research Engineer in Arm’s Research division, working in Software and Large Scale Systems. She joined Arm in 2012 after obtaining an MEng degree in Computing (Software Engineering) from Imperial College London in optimising unstructured mesh CFD applications on multicores via machine learning and code transformation. At Arm, amongst others, she has worked on Linux kernel optimizations aimed at HPC and sensitivity studies aimed to showcase Arm AArch64 microprocessor characteristics suitable for HPC. Most recently, she has been working on power-aware scheduling at OS level for heterogeneous cores and methodologies to identify representative sub-sections from multi-threaded applications. Some of her research interests are software performance optimization and next-gen heterogeneous architectures. Roxana has been a part of the Mont-Blanc 1 and 2 projects, and is now leading the Software ecosystem in Mont-Blanc 3, in addition to technical contributions.

Oscar Hernandez has a Phd in Computer Science and recently joined NVIDIA/Mellanox in 2021 after working 12 years at Oak Ridge National Laboratory (ORNL) where he was a senior staff member of the Programming Systems Group, which does research on programming models, compilers and tools that are deployed at supercomputers like Summit and Frontier at the Leadership Computing Facility (OLCF). At ORNL he helped standardize parallel languages and APIs for accelerated nodes such as OpenACC/OpenMP and communication libraries and frameworks like OpenSHMEM and UCX. He also worked for the Exascale Computing Project where he led different efforts to deploy these technologies on Exascale systems. He also worked closely with application teams including the CAAR, INCITE and ALCC projects and on many projects funded by DOE, DoD, NSF, and Industrial Partners in the Oil & Gas industry.Oscar has a lot of experience giving tutorials in different venues, like Supercomputing, ISC, ECP Annual Meeting and NSF.

Andrew Younge is a R&D Computer Scientist at Sandia National Laboratories with the Scalable System Software group. His research interests include High Performance Computing, Virtualization, Distributed Systems, and energy efficient computing. The central focal point of Andrew’s work is to improve the usability and efficiency of supercomputing system software. Andrew has a Ph.D in Computer Science from Indiana University, where he was the Persistent Systems fellow and a member of the FutureGrid project, an NSF-funded experimental cyberinfrastructure test-bed. Over the years, Andrew has held visiting positions at the MITRE Corporation, the University of Southern California / Information Sciences Institute, and the University of Maryland, College Park. He received his Bachelors and Masters of Science from the Computer Science Department at Rochester Institute of Technology (RIT) in 2008 and 2010, respectively.

RuQing (G) Xu is a 2nd year postgrad in physics now in the University of Tokyo. (https://qsl.r-xu.dns-cloud.net). I'm primarily working on computational sciences in a solid state physics context, with special focus on variational wavefunction optimization and tensor network methods. As a result, my work is very sensitive to the performance of linear algebra libraries (BLAS-level, LAPACK-level, sparse LAPACK-level, etc.). I got to know BLIS and Arm on HPC when trying to optimize our variational quantum solver on supercomputer Fugaku. Experience working with Arm processors turned out to be smooth and fruitful, with our lab program accelerated up to ~6x and BLIS on SVE almost production-ready. Apart from performance libraries, I'm a keen user of programming language Julia. Wrappers for BLIS and TBLIS are made to exploit flexibility of BLIS framework as well as Julia language itself. Improving Julia ecosystem on aarch64 is yet another thing I want to contribute to in the coming few years.

Yuetsu Kodama is a senior scientist at RIKEN CCS (Center for Computational Science) from 2015. He received the B.E., M.E. and Ph.D degree in engineering from the University of Tokyo in 1986, 1988 and 2003, respectively. He was a professor at University of Tsukuba in 2011-2015, a senior researcher at AIST (National Institute of Advanced Industrial Science and Technology) in 2000-2011 and a senior researcher at ETL (Electrotechnical Laboratory) in 1988-1999. He has been engaged in the research on parallel computer architecture. He is a member of IEEE CS, IEICE and IPSJ.

Stephen Messenger is a Senior HPC specialist Solutions Architect for AWS. He has worked with HPC and Cloud technology for the last 15 years, working on many different projects from personal clusters that fit under a desk, to some of the largest Super Computers in the world. He is still slightly amazed that anyone will pay him for tinkering with computers. When Stephen is not working he enjoys spending time mountain biking, in the New Forest or the South Downs in England.

Srinath Vadlamani, Ph.D. is an HPC Field Application Engineer with Arm. Inc. He specializes in scientific application efficacy on HPC systems with a focus on Arm enabled systems. Current interests include computation/communication overlap strategies and threading strategies. Srinath is part of the US Fortran Programming Language Standards Technical Committee.

Miwako Tsuji received master and PhD degrees from Information Science and Technology, Hokkaido University. From 2007 to 2013, she was working in University of Hokkaido, University of Tokyo, University of Tsukuba and Universite de Versailles Saint-Quentin-en-Yvelines. She is a research scientist at RIKEN Center for Computational Science. She was a member of the flagship 2020 project, which had conducted the disign and development of the supercomputer Fugaku during the full period of the project. Her current research interests are programming model and performance model of the large-scale high performance computing. She is a coauthor of the ACM Gordon Bell Prize in 2011.

After studying physics at the Bergische Universitat Wuppertal, Stepan Nassyr joined the Juelich Supercomputing Centre in July 2017 to work on his PhD dealing with future ARM-based supercomputer architectures. As part of the application oriented technology group at the Juelich Supercomputing Centre he has worked extensively with the ARM ecosystem and the ARM SVE extension, focusing mostly on hand-written assembly kernels and the requirements to the microarchitecture and memory architecture to effectively exploit the available compute capabilities in the context of HPC applications. Aside from his PhD, he is also administering a small ARM-based cluster at the JSC and has experience with a number of ARM-based HPC architectures, including Marvell ThunderX2, Huawei Kunpeng 920 and Fujitsu's A64FX.

tbd

Andrei Poenaru is a final-year PhD Student with the High Performance Computing Group at the University of Bristol. His research is centred around advanced and future architectures for HPC, and he has been involved in several studies aiming to characterise performance and evaluate portability across diverse modern architectures. His current projects are focused on vectorisation in the context of Arm SVE and upcoming Arm-based high-performance processors.

John is Arm's Director for HPC Engineering. He leads a worldwide team of HPC experts focused on making Arm a win for HPC and vice versa.

Jeff Hammond is a Principal Architect at NVIDIA, where he focuses on parallel programming models for GPUs and ARM CPUs. He has contributed to NWChem since 2006.

I am a Computational Physicists in the domain of Material Sciences, with a education in Theoretical High Energy Physics. My present research interests are related to the conception, development, and implementation of new theoretical algorithms and methods exploiting advanced computing resources, enabling large-scale computation in diverse areas in Solid-State physics, Quantum Chemistry, and Electronic Structure calculations with applications in Life-Sciences and Biology.

Miquel Moreto is a Ramon y Cajal Fellow at the Computer Architecture Departament (DAC) at the Universitat Politecnica de Catalunya-Barcelona Tech (UPC), where he teaches Computer Architecture. He is leading the High Performance Domain Specific Architectures team at the Barcelona Supercomputing Center (BSC). He received the BSc, MSc, and PhD from the UPC. His PhD thesis advisors were Mateo Valero (UPC) and Francisco J. Cazorla (BSC). During his PhD, he interned at IBM T. J. Watson Research Center for 4 months, and visited the Universities of Edinburgh and Cantabria for 3 months. After finishing the PhD, he spent 15 months at the International Computer Science Institute (ICSI), affiliated with UC Berkeley, as a Fulbright Postdoctoral Research Fellowship Holder during 2011 and 2012. Finally, he spent 2 months in Arm Research (Cambridge, UK) as a Visiting Professor in 2017.

Hatem Ltaief is a principal research scientist with the Extreme Computing Research Center, King Abdullah University of Science and Technology, Saudi Arabia. His research interests include parallel numerical algorithms, parallel programming models, and performance optimizations for multicore architectures and hardware accelerators.

"Bine Brank is a PhD student at Juelich Supercomputing Centre. After obtaining his Master's degree in Computer Simulation from the University of Wuppertal, he has joined the application-oriented technology development team at JSC. There, he is working in the context of Mont-Blanc 2020 and the European Processor Initiative project. The main topic of his dissertation is SIMD parallelisation with a focus on Arm's SVE. This includes porting of applications to Arm architectures as well as evaluation of compiler's auto-vectorisation capabilities. "

Eva Siegmann has a PhD in applied mathematics. She has extensive experience in the field of high-performance computing with special focus on simulations in the field of pharmaceutical engineering. Beginning of this year Eva joined the Stony Brook University where she is the lead research scientist in the Ookami project. Ookami is testbed which provides researchers with state-of-the-art hardware, including Fujitsu A64FX processors.

Sarat Sreepathi is a Computer Scientist interested in interdisciplinary research at the intersection of High Performance Computing and domain sciences. He is a member of the Computational Earth Sciences Group in the Computational Sciences and Engineering Division at Oak Ridge National Laboratory. He received his Ph.D. in Computer Science from North Carolina State University. He is the Chair of the OLCF User Group Executive Board and serves on the NERSC User Group Executive Committee. He co-leads the Performance group for the Energy Exascale Earth System Model. He is also a member of Exascale Computing Project (ECP) application teams (Climate: E3SM-MMF and Nuclear Fusion: XGC) .

Thomas Chen is a researcher scientist whose primary interests lie in machine learning and high-performance computing. He serves on the U.S. Technology Policy Committee of the Association for Computing Machinery. As much of his work lies at the nexus of artificial intelligence and earth science, he is also an active early-career scientist member of the European Geosciences Union and the American Geophysical Union. He particularly enjoys using Python to conduct research that has real-world impacts. Previously, Thomas has presented work at a number of conferences, workshops, and meetings, from NeurIPS workshops, to Applied Machine Learning Days, to the Open Data Science Conference, to Machine Learning Week Europe.

Craig Prunty, SiPearl VP Marketing & Business Development, joined SiPearl in May 2020. Prior to SiPearl, Craig was Marketing Director for Marvell Semiconductor’s Server Processor Business Unit in Santa Clara, California. His 20+ years in the Semiconductor industry include sales, marketing, and technical roles with Cavium, AppliedMicro (AMCC), Lockheed-Martin, and Unisys. Craig holds a B.S. in Mathematics from Lewis & Clark College in Portland, Oregon, and an MS in Electrical Engineering from San Diego State University.

Dr. Julien Bigot is a CEA Researcher at Maison de la Simulation. His main research interest is related to programming models and software engineering issues for HPC applications. During his Ph.D. Thesis (2007-2010) at IRISA Rennes and ENS Lyon, he proposed a HPC-dedicated software component model based on assembly compilation for hardware adaptation. He applied this approach to real life applications such as a MapReduce skeleton, a parallel FFT code and the extreme-scale plasma simulation code Gysela5D. Since 2014, he holds a permanent CEA researcher position at Maison de la Simulation. There, he conducts research on the separation of concern between optimization and algorithm in HPC codes. He also leads the development of the PDI library used for code modularization to support separation of concern between IO optimization and the main code as well as integration of codes in complex workflows.

Bruno Raffin is Research Director at Inria and leader of the DataMove team. He led the development of the FlowVR/Melissa middleware for large-scale data-flow oriented parallel applications, used for scientific visualization, computational steering, in situ analytics for large-scale parallel applications. He also worked on parallel algorithms and cache-efficient parallel data structures (cache oblivious mesh layouts, parallel adaptive sorting), strategies for task-based programming of multi-CPU and multi-GPU machines. Bruno Raffin accounts for more than 60 international publications, advice 16 PhD students. Bruno Raffin has been involved in more than 30 program committees of international conferences. He was responsible for INRIA of more than 15 national and European grants and was the co-founder of the Icatis start-up company (2004-2008). He leads the INRIA Integrated Project Lab focused on the convergence between HPC, AI and Big Data (2018-2021).

Dr. Leonardo Bautista Gomez is a Senior Research Scientist at the Barcelona Supercomputing Center where he work on resilience and scalability for high-performance computing and machine learning. He was awarded the 2016 IEEE TCSC Award for Excellence in Scalable Computing (Early Career Researcher). Before moving to BSC he was a Postdoctoral researcher for 3 years at the Argonne National Laboratory, where he investigated data corruption detection techniques and error propagation. Prior to that, he did his PhD. in resilience for supercomputers at the Tokyo Institute of Technology. He developed a scalable multilevel checkpointing library called Fault Tolerance Interface (FTI) to guarantee application resilience at extreme scale. For this work, he was awarded the 2011 ACM/IEEE George Michael Memorial High-Performance Computing Ph.D. Fellow at Supercomputing Conference 2011 (SC11), Honorable Mention. Before moving to Tokyo Tech, he graduated in Master for Distributed Systems from the Paris 6 University.

Wouter Klijn completed a MSc in Artificial Intelligence from the University of Groningen in the Netherlands. His Master thesis was on the information content of cell species in a 3 layer model of a cortical micro-column. He currently is a software architect in the Simlab Neuroscience at the Forschungzentrum Jülich with a focus on in Artificial Intelligence, information theory of neural networks, big data real-time streaming systems and development of complex HPC processing pipelines. He is responsible for science and use case management in the Human Brain Project, an EU Flagship Project and ICEI, the Interactive Computing E-Infrastructure for the Human Brain Project. He is currently creating the science and software infrastructure architecture for the HBP. He also works with advanced HPC oriented AI solutions and multiple neural simulators. His modelling work is focused on self-organizing dynamics of extremely large neural networks with a 2d spatial structure.

Charles Gueunet joined Kitware in February 2016. For the first three years, he worked on his PhD on the topic of “High Performance Level-set based Topological Data Analysis”, and became one of the main contributors of the Topology ToolKit (TTK). After defending in February 2019, Charles joined the Scientific Visualization team at Kitware. He now works on various projects involving parallel programming, discrete geometry and data analysis algorithms.

Sai Narasimhamurthy PhD is currently Managing Principal Engineer, Seagate (formerly Lead Researcher, Emerging Tech, Xyratex) working on Research and Development for next generation storage systems and responsible for EU R&D for the Seagate Systems business. Sai currently also holds the position of vice-chair of industry for the ETP4HPC organisation and leads the storage and I/O working group for developing ETP4HPC’s Strategic Research Agenda (SRA). He has also actively led and contributed to many European led HPC and Cloud research initiatives currently coordinating and providing technical leadership for SAGE and Sage2 consortia. Previously, Sai was CTO and Co-founder at 4Blox, inc, a venture capital backed storage infrastructure software company in California addressing IP SAN(Storage Area Network) performance issues

Dr Achim Basermann is head of the department “High-Performance Computing” at German Aerospace Center’s (DLR) Simulation and Software Technology institute and German Research Foundation (DFG) review board member in computer science, topic “Massively Parallel and Data Intensive Systems”. In 2019, he became chairman of the strategy commission for national high-performance computing (NHR) in Germany. He coordinated the application workpackage in the European Grid computing project NextGRID (2004-2007), the pre- and postprocessing activities in the European Exascale computing project CRESTA (2011-2014) and the algorithmic research in the Exascale computing projects ESSEX I and II (2013-2018) of DFG. In 1995, he obtained his Ph.D. in Electrical Engineering from RWTH Aachen followed by a postdoctoral position in Computer Science at Research Centre Jülich GmbH, Central Institute for Applied Mathematics. From 1997 to 2009 he led a team of HPC application experts at the C&C Research Laboratories, NEC Europe Ltd., in Sankt Augustin, Germany and contributed to the Japanese Earth Simulator project. Current research is focussed on massively parallel linear algebra algorithms, partitioning methods, optimization tools in the area of computational fluid dynamics for many-core architectures and GPGPU clusters, high-performance data analytics and quantum computing.

Matthieu Dorier graduated with a PhD from Ecole Normale Supérieure de Rennes, France, In 2014, and followed with a two-year postdoc at Argonne National Laboratory. Since 2017, Matthieu is a software development specialist at Argonne. His work revolves around data management for HPC, including parallel and distributed storage, data services, workflows, in situ analysis and visualization.

Amal Gueroudji is a PhD student at Maison de la simulation. Holder of a research Master and an Engineering degree in Computer Systems (2014-2019) from the Higher National School of computer science (ESI ex INI Alger). During her Masters(2019), she worked on the Tiramisu polyhedral compiler with the Commit team at MIT-CSAIL laboratory. She mainly worked on CPU/GPU communication optimization and code generation automation. Since April 2020, Amal is a PhD student working on code coupling of high performance simulation to task-based in situ analytics, namely MPI codes with DASK.

Dr Tiago Quintino is a Senior Analyst and Team Leader for Development of Production Services at ECMWF. He and his team develop high-throughput specialist software that supports ECMWF’s operational meteorological forecast model, systems for acquisition of incoming observations, management of direct model output, perpetual archival of weather observations and forecast data, and post-processing, generation and dissemination of meteorological products. His team also develops cloud meteorological and climate data provisioning services (Data-as-a-Service) in support of ECMWF’s cloud activities. Dr Quintino’s career spans 20 years researching numerical algorithms and developing high performance scientific software in the areas of Aerospace and Numerical Weather Prediction. Lately, his research focuses on scalable data handling algorithms for generation of meteorological forecast products, optimising their workloads and I/O of massive data-sets.

Prof. Dr. Dirk Pleiter is professor for HPC at KTH, director of the PDC Center for High Performance Computing and senior researcher at Forschungszentrum Jülich. He is the principal investigator of various European research and innovation projects including Maestro. Furthermore, he acts as technical coordinator of the ICEI project, which as part of the Human Brain Project works on providing a productively used federated European HPC, cloud and storage infrastructure. In the past he played a leading role in several projects for developing massively-parallel special purpose computers, including QPACE, and recently worked on Arm-based processor architectures.

Dr. Alejandro Ribés graduated in computer science (bachelor’s and master’s) from the Universitat Jaume I, Castelló (ES). He later graduated, from Université de Nice Sophia-Antipolis (FR), in a master in image processing and computer vision. Alejandro Ribés also holds a Ph.D. in multispectral imaging applied to fine art paintings, from the Ecole Nationale Supérieure des Télécommunications (FR). He later was a postdoctoral fellow at the CEA laboratory in Orsay (FR), working on parallel MRI reconstruction. During this postdoc he was appointed as a lecturer at the Computer Science Department of Ecole Polytechnique, Palaiseau, France, where he taught for two years. Alejandro also worked in MRI technology, during more than two years, as a visiting scholar at the National Yang-Ming University, Taipei, Taiwan. In 2009, Alejandro Ribés became a Research Scientist at the R&D department of EDF. In December 2016, he became Principal Research Scientist. He recently introduced AI based methods on the context of advanced numerical simulation, especially deep neural networks trained using GPU clusters. From 2013, Alejandro Ribés also collaborates with Sorbonne Université (FR).

Dr. Virginie Grandgirard received the PhD degree in mathematics and applications from Besancon University, France, in 1999. She then obtained the Habilitation à Diriger des Recherches in 2016. She is presently researcher with CEA, France. She is one of the main developer of the 5D non-linear gyrokinetic semi-Lagrangian code GYSELA used for plasma turbulence simulations. This code is highly parallelized up to hundreds of thousands cores. Her research interests focus on numerical methods for Vlasov equations, high performance computing and tokamak plasma turbulence. She has co-authored 50 publications in peer-reviewed journals.

Yuuichi ASAHI received the PhD degree from Tokyo Tech, in 2015. He is a researcher in Japan atomic energy agency (JAEA), Japan. He has focused on the nonlinear plasma turbulence by means of gyrokinetic simulations. High performance computing and large scale data management are key ingredients for these simulations. His current interests include accelerating the gyrokinetic simulation codes for more complicated physics, and analysing the large scale simulation results with machine learning methods.

Johannes Doerfert is a researcher in the Argonne Leadership Computing Facility at the Argonne National Laboratory. He develops LLVM and Clang enhancements that enable compiler optimization for parallel programs. Johannes is also part of several ongoing efforts to make compiler software ready for exascale computing. He is an active member of the OpenMP Language Committee and already organized various LLVM related workshops and conferences, including the LLVM Performance Workshops @ CGO, and the EuroLLVM in 2017. Johannes received his Ph.D. in Computer Science from Saarland University in 2018.

Anja works at the Center for Information Services and High Performance Computing at TU Dresden. A considerable part of her job role is to develop a range of courses and resources to enable users to work with the cluster. In addition, she is doing a PhD at the German Climate Research Center in Hamburg as an external member. The main topic is Compiler Optimization in High-Performance Computing with an aim to improve weather forecasting and climate modeling. The goal of her PhD is to study the compiler for deficits in terms of performance when translating HPC applications and to understand the limitations of compilers in making the necessary optimizations. These insights can then be incorporated into the compiler for future automatic compiler optimization. Automatic program transformation using source-to-source instrumentation of parallel programs will prepare HPC applications for future performance analysis.

Sameer Shende serves as the Director of the Performance Research Laboratory at the University of Oregon and the President and Director of ParaTools, Inc. He serves as the lead developer of the TAU Performance System, Program Database Toolkit (PDT), HPCLinux, and Extreme-Scale Scientific Software Stack (E4S.io). His research interests include performance instrumentation, compiler optimizations, measurement, and analysis tools for HPC. He leads the SDK project for the Exascale Computing Project (ECP), in the Programming Models and Runtime (PMR) area at the University of Oregon to provide ECP Software Technology (ST) products in a container environment for HPC. He has served as the chair of the Performance Measurement, Modeling, and Tools track at SC17 and the co-chair for the technical program at the ICPP 2018 conferences.

Jeremy Bennett founded in 2008 Embecosm. He is an expert on hardware modeling and embedded software development. Previously Dr Bennett was Vice President of ARC International plc, following their acquisition of Tenison Design where he had been CEO and CTO. Dr Bennett is author of the popular textbook, “Introduction to Compiling Techniques” (McGraw-Hill 1990, 1995, 2003) and holds an MA and PhD in Computer Science from Cambridge University.

Shintaro Iwasaki is a Named Fellow at Argonne National Laboratory. He received his Ph.D. degree from the University of Tokyo in 2020. His research interests include parallel programming languages, compiler optimizations, parallel runtime systems, and scheduling techniques. He is leading the development of a lightweight user-level threading library called Argobots and an OpenMP runtime library over Argobots, BOLT. He is also working on MPI + lightweight threads (such as Argobots + MPICH or Open MPI). For details, see https://www.mcs.anl.gov/~iwasaki/

Ernesto Su is a Senior Staff Engineer and a project lead for the Parallel Optimization team of the Intel Compilers, with a focus on OpenMP parallelization and offloading. He holds a BS degree from Columbia University and MS & Ph.D. degrees from UIUC.

Xinmin Tian is a Senior Principal Engineer and a compiler architect at Intel Corporation. He is serving as Intel representative at OpenMP ARB and driving DPC++ optimizations, OpenMP vectorization, parallelization and offloading technologies for current and future Intel architectures.

Valentin Clement is a Software Engineer in the Programming Systems Group at Oak Ridge National Laboratory. His research currently focuses on LLVM-base compiler projects. He is mainly contributing to Flang and OpenACC support for LLVM.

Arnamoy received his PhD from University of Toronto and currently working in the Heterogeneous compiler lab in Huawei, Canada as a research engineer. He is broadly interested in the area of performance enhancement through compiler optimization, cloud computing and machine learning guided optimizations. He has been actively contributing in the LLVM Flang project (especially for the driver and semantic analysis for OpenMP).

Saiyed is a Senior SDE in AMD’s GPU Compiler organization based out of Bangalore, India. There, he is part of AOMP team lead by Greg Rodgers where he focuses mainly on OpenMP frontend development and upstreaming. He obtained PhD from BITS Pilani India, where he designed a Domain Specific Language for Clustering and its Parallelizing Compiler. In this DSL, data scientists write sequential code and the compiler generates corresponding distributed memory parallel MPI C++ code. He also proposed a Virtual Machine for this compiler to abstract multiple target parallel architectures. He has published at multiple International Journals and Conferences and love teaching parallel programming.

Dr. Tobias Grosser is a Reader in Compilers and Runtime Systems at Edinburgh. He is known for his research on optimizing compilers and his contributions to open-source software. As author and development lead of the LLVM polyhedral loop optimizer Polly [27], Tobias Grosser made advanced polyhedral loop optimizations available in production-grade compilers. To coordinate the industry interest in polyhedral compilation, Tobias Grosser co-founded the Polly Labs research organization and currently works with Arjun Pitchanathan on integrating a state-of-the-art polyhedral library into LLVM/MLIR. Tobias also collaborates closely with the LLVM community on advancing the new MLIR software stack and he introduced with LLHD [39], an open-source compilation stack for hardware design that brings the innovation speed of software compilers to the hardware design world. Tobias Grosser has received a Google Ph.D. Fellowship and a Swiss National Science Foundation Career Award.

Jeff Sandoval is a senior compiler tech lead at HPE in Bloomington, Minnesota. He specializes on compiler and runtime library implementation for both the OpenMP and OpenACC programming models, targeting a variety of CPU and GPU processors. Jeff holds a PhD in computer science from Rice University and a BS in computer science from Michigan Technological University.

Christian is a Specialist Solutions Architect with AWS. With a 10 year journey rooted in the HPC parts of the german automotive industry, Christian Kniep started to support CAE applications and VR installations. When told at a conference that HPC can not learn anything from the emerging Cloud and BigData companies, he became curious and was leading the containerization effort of the cloud-stack at Playstation Now followed by working at Docker Inc as a Technical Account Manager to help push the adoption forward and be part of the innovation instead of an external bystander. At AWS he is helping customers to adopt the cloud efficiently.

Shane Canon joined NERSC in 2000 to serve as a system administrator for the PDSF cluster. While working with PDSF he gained experience in cluster administration, batch systems, parallel file systems and the Linux kernel. In 2005, Shane left LBNL to take a position as Group Leader at Oak Ridge National Laboratory. One of the more significant accomplishments while at ORNL was architecting the 10 petabyte Spider File System. In 2008, Shane returned to NERSC to lead the Data Systems Group. More recently Shane has focused on enabling data intensive applications on HPC platforms and engaging with bioinformatics applications. Shane joined the Data & Analytics Services group in 2016 to focus on these topics. Shane is involved in a number of projects outside of NERSC. He is the Production Lead on the KBase project which is developing a platform to enable predictive biology. Shane has a Ph.D in Physics from Duke University and B.S. in Physics from Auburn University.

Andrew J. Younge is a Senior Member of Technical Staff in the Scalable System Software department at Sandia National Laboratories. He currently serves as the Lead PI for the Supercontainers project under the DOE Exascale Computing Project and is a key contributor to the Astra system, the world's first supercomputer based on the Arm processor deployed under Sandia's Vanguard program. Prior to joining Sandia, Andrew held visiting positions at the MITRE Corporation, the University of Southern California's Information Sciences Institute, and the University of Maryland, College Park. He received his PhD in computer science from Indiana University in 2016. His research interests include high performance computing, virtualization, distributed systems, and energy efficient computing. The focus of his research is on improving the usability and efficiency of system software for supercomputing systems.

Eduardo is a performance engineer at Red Hat, working on the OpenShift performance & latency sensitive applications. Eduardo is also a Computer Science PhD student at Universidad del Valle, Cali, Colombia, working on containerized distributed systems for research computing, with high focus on automated workflows and DevOps. His research interests include High Performance Computing, Distributed systems, Dependency management, Linux containers and most recently, Container orchestration. Over the past 5 years Eduardo has focused on enabling researchers to build and deploy performance sensitive applications with containers on distributed environments.

Abdulrahman Azab works at the Department of Research Computing, University of Oslo, Norway. In addition he is a senior lecturer at the Department of Computer Engineering and Control Systems, Mansoura University, Egypt. He is leading the Containers-for-HPC service at PRACE (Partnership for Advanced Computing in Europe). Abdulrahman is also the Norwegian sub-project manager at NeIC/Tryggve (Collaboration on Sensitive Data in the Nordics). Abdulrahman is leading the sensitive data working group in both EOSC-hub and EOSC-Nordic (EOSC: European Open Science Cloud). His research interests are: High Performance Computing, High Throughput Computing, High Availability Computing, Linux Containers, Cloud Computing, Cyber Security, Control systems, and Bioinformatics.

He has experience working with High-Performance Computing Systems at International Centre for Integrated Mountain Development where is involvement was with Atmosphere Initiative and SERVIR-NASA Projects. Mr Upadhyaya also collects experience working with International Seabed Authority, UNDP and Election Commission of Nepal. Mr Upadhyaya is a recipient of a full grant to attend International Super Computing Conference 2017, Germany and a first recipient of Inclusivity Grant to attend Super Computing Conference 2017, USA.

Michael Kuhn is a junior professor for Parallel Computing and I/O at Otto von Guericke University Magdeburg. He conducts research in the area of high performance I/O with a special focus on I/O interfaces and data reduction techniques. Other interests of his include file systems and high performance computing in general. Michael is the principal investigator of the CoSEMoS project funded by the German Research Foundation (DFG). Moreover, he is the lead developer of the JULEA storage framework and received a 2019 R&D 100 award for his contributions to the Spack package manager. He regularly offers lectures and courses related to HPC and parallel I/O.

I studied physics at the University of Göttingen. For my PhD I focused on numerical simulations of Earth's magnetic field, which brought me in contact with high performance and parallel computing. After a stay at the MPI for Solar System Research I moved to computational biophysics. Since 2004 I am working at the Max Planck Institute for Biophysical Chemistry in the lab of Helmut Grubmüller. I am interested in method development, high performance computing, and atomistic biomolecular simulations.

Dr. Kindratenko is a Senior Research Scientist at the National Center for Supercomputing Applications, an Adjunct Associate Professor in the Department of Electrical and Computer Engineering and a Research Associate Professor in the Department of Computer Science at the University of Illinois. He received D.Sc. degree from the University of Antwerp, Belgium, in 1997 and prior to that graduated from the State Pedagogical University, Kirovograd, Ukraine, in 1993. Dr. Kindratenko’s research interests include high-performance computing, special-purpose computing architectures, and cloud computing. He serves as a department editor of IEEE Computing in Science and Engineering magazine and an associate editor of the International Journal of Reconfigurable Computing. Dr. Kindratenko’s work has been funded by NSF, NASA, ONR, and industry. He has published over 60 papers in refereed scientific journals and conference proceedings and holds 4 US patents. He is a Senior Member of IEEE and ACM.

Dr.-Ing. Andreas Lintermann is a researcher at the Jülich Supercomputing Centre (JSC) at Forschungszentrum Jülich, where he is heading the Simulation and Data Lab Engineering as part of the Jülich Aachen Research Alliance Center for Simulation and Data Science (JARA-CSD). Dr.-Ing. Lintermann received his diploma in Computer Science from RWTH Aachen University in 2009. From 2009 to 2014, he was a P.hD. student at the Institute of Aerodynamics and Chair of Fluid Mechanics, RWTH Aachen University. In his thesis, he investigated the flow in the human nasal cavity and developed a massively parallel grid generator. His research focuses on respiratory flows, lattice-Boltzmann methods, Lagrangian particle methods, fluid-structure interaction, meshing methods, and high-performance computing. Lintermann published 30 articles in peer-reviewed journals and conference proceedings, and magazines, and is reviewer for several renowned journals.

Dr Charalambos Chrysostomou is an Associate Research Scientist at The Cyprus Institute, applying advanced machine learning on data-driven applications, including computational fluid dynamics, medical imaging and computational physics. Charalambos received his BA in Computer Science, from the University of Nicosia, Cyprus, in 2006, his Master in Computational Intelligence and Robotics, and PhD in Bioinformatics from De Montfort University, United Kingdom, in 2007 and 2012, respectively. He was the University of Leicester as a postdoctoral fellow until 2016.

Ashley Scillitoe is a Research Associate within the Data-Centric Engineering group at the Alan Turing Institute. His research focuses on the quantification of aleatory and epistemic uncertainties in CFD simulations, with machine learning techniques employed to make use of high-fidelity data from Large Eddy Simulations. Ashley completed his PhD at the University of Cambridge in 2017, where his work involved the development of more reliable Large Eddy Simulation techniques for application to Gas-Turbine compressor flows. Prior to his PhD, Ashley obtained a Meng (Hons) in Aerospace Engineering from the University of Manchester.

Eloisa Bentivegna is a Research Staff Member in Daresbury, UK. She holds a PhD in Physics, with a minor in High Performance Computing, from Penn State University, and has served as a postdoctoral scholar at the Center for Computational and Technology (USA), a Marie Curie Fellow at the Max Planck Institute for Gravitational Physics (Germany), as well as a National Montalcini Fellow and faculty member of the Physics Department at the University of Catania (Italy) before joining IBM. She has vast experience in the application of computational techniques to the frontiers of theoretical physics, most notably strong gravity and high-energy quantum fields. She currently works on building computational models of fluid-dynamical systems and developing an infrastructure for verifying and streamlining these models using cognitive technologies. Her broader expertise involves multiscale phenomena and coarse graining, relativistic optics, and nonlinear elliptic problems.

Jiahuan Cui is an assistant professor at ZJU-UIUC institute, Zhejiang University. He is leading a group working on the high-fidelity simulation using high performance computers and the turbulence modelling using data driven methods. Jiahuan Cui received his Ph.D from the University of Cambridge in 2016, where his research focused on the high-fidelity simulation for the turbulent flow in turbomachinery. After receiving his PH.D, he worked as a research associate from 2016 to 2017 at the University of Cambridge on a fan modelling project sponsored by Rolls Royce and Innovate UK.

George Karniadakis received his S.M. (1984) and Ph.D. (1987) from Massachusetts Institute of Technology. He was appointed Lecturer in the Department of Mechanical Engineering at MIT in 1987 and subsequently he joined the Center for Turbulence Research at Stanford/NASA Ames. He joined Princeton University as Assistant Professor in the Department of Mechanical and Aerospace Engineering and as Associate Faculty in the Program of Applied and Computational Mathematics. He was a Visiting Professor at Caltech (1993) in the Aeronautics Department. He joined Brown University as Associate Professor of Applied Mathematics in the Center for Fluid Mechanics on January 1, 1994. He became a full professor on July 1, 1996. He has been a Visiting Professor and Senior Lecturer of Ocean/Mechanical Engineering at MIT since September 1, 2000. He was Visiting Professor at Peking University (Fall 2007 & 2013). He is a Fellow of the Society for Industrial and Applied Mathematics (SIAM, 2010-), Fellow of the American Physical Society (APS, 2004-), Fellow of the American Society of Mechanical Engineers (ASME, 2003-) and Associate Fellow of the American Institute of Aeronautics and Astronautics (AIAA, 2006-). He received the Ralf E Kleinman award from SIAM (2015), the J. Tinsley Oden Medal (2013), and the CFD award (2007) by the US Association in Computational Mechanics. His h-index is 73 and he has been cited over 26,000 times.

Kazuto Ando is a senior technical staff in the Operations and Computer Technologies Division and Complex Phenomena Unified Simulation Research Team at RIKEN Center for Computational Science (R-CCS), Kobe, Japan. His research interests are High-Performance Computing (specifically computational performance optimization on HPC systems), Computational Fluid Dynamics, and Artificial Intelligence. He had also worked in the application area of earthquake and tsunami simulation at JAMSTEC. He received his BS and MS degree in Physics from Tokyo Metropolitan University, Japan.

Mario Rüttgers joined the Institute of Aerodynamics and the Jülich Supercomputing Centre as a researcher in February 2019. His research focuses on an improved treatment in rhinology by combining numerical flow simulations with machine learning techniques. Since February 2019 he is also a PhD student at RWTH Aachen University. Before starting the PhD program, he completed a Master's degree program in mechanical engineering at the Pohang University of Science and Technology in South Korea, specializing in fluid mechanics and machine learning techniques.

Michael Gauding is research scientist at the French research institute CORIA and at the University of Rouen. He received his PhD from RWTH Aachen University in 2014 and is an expert in turbulence modeling, combustion and high-performance computing. He performed simulations of turbulence with more than 230 Billion grid points to analyze strong turbulent bursts at smallest scales. To tackle the complex statistics of these bursts, he developed data-driven methods based on super- resolution networks.

Mario Bedrunka is research assistant at the University of Siegen, Germany and Bonn-Rhein-Sieg University of Applied Sciences. He holds a M. Eng. degree in mechanical engineering from the Bonn-Rhein-Sieg University of Applied Sciences. Now he pursues a Ph.D. on machine learning in the lattice Boltzmann methods and the modeling and simulation of hydrogen storages.

Felipe de Castro Teixeira Carvalho is a Ph.D. student in Mechanical Engineering at the University of Campinas and master in Mechanical Engineering from the University of Campinas. He has experience in signal processing, mechanical vibration and multiphase flows. Currently, he has a keen interest in dynamical systems modelling and machine learning applied to dynamical systems and dimensionality reduction

Dr. Jinhui Yan is an assistant professor in civil and environmental engineering at the University of Illinois at Urbana-Champaign. His research interests lie in computation mechanics, CFD, fluid-structure interaction, and their applications to wind, tidal energy, and additive manufacturing. He won ASME Robert M. and Mary Haythornthwaite Young Investigator Award in 2018. He currently serves as the vice-chair for both the CFD and FSI thrust of the US Association for Computational Mechanics and computational fluid-structure interaction committee of ASME.

Thomas Brown obtained his PhD in Mathematics from the University of Delaware in 2018. He is a numerical analyst interested in Galerkin methods for models in continuum mechanics, optimization and optimal control problems, and scientific computing. His research focuses on analysis and implementation of novel numerical methods for different problems of interest. The analysis includes well-posedness, stability, and approximation properties of the methods. Recently he has also been investigating the use of machine learning techniques to solve systems of ODEs and PDEs. He is a co-author of the textbook: Variational Techniques for Elliptic Partial Differential Equations: Theoretical Tools and Advanced Applications.

Sarath Radhakrishnan is a PhD student in the Computer Applications in Science and Engineering department of the Barcelona Supercomputing Center. His research is on wall modeling in Large Eddy Simulation.

Yaning Wang is studying for his PH.D degree in Computational Fluids Dynamics (CFD) at Zhejiang University. He graduated from Xi’an JiaoTong University in 2019 with a Bachelor's Degree in Mechanical Engineering. His research interest is using machine learning techniques for CFD application. Currently, his work focuses on using machine learning technology to predict the film cooling performance for high pressure turbines.

Dr. Shirui Luo is a research scientist in the Industrial Application Domains group at the National Center for Supercomputing Applications (NCSA). Dr. Luo is experienced in multi-physics and multiscale computational modeling and machine learning. He has carried out large-scale simulations and performance profiling on a diverse range of supercomputers in the private sector and government-funded research projects.

Dr. Kunkel is a Lecturer at the Computer Science Department at the University of Reading. Previously, he worked as postdoc in the research department of the German Climate Computing Center (DKRZ) that partners with the Scientific Computing group at the Universität Hamburg. He manages several research projects revolving around High-Performance Computing and particularly high-performance storage. Julian became interested in the topic of HPC storage in 2003, during his studies of computer science. Besides his main goal to provide efficient and performance-portable I/O, his HPC-related interests are: data reduction techniques, performance analysis of parallel applications and parallel I/O, management of cluster systems, cost-efficiency considerations, and the software engineering of scientific software.

Dr. Jay Lofstead is a Principal Member of Technical Staff at Sandia National Laboratories in Albuquerque, New Mexico. Since 2010, Jay has been working on HPC simulation workflows focusing on data management issues and as well as general I/O and storage issues for HPC. His prior work includes the R&D100 Award winning ADIOS I/O componentization framework in use in more than 30 production scientific simulations. He is a member of several conference and workshop program committees.

Jean-Thomas has obtained his Ph.D in 2000 from CEA, DAM (French Atomic Commission, Military Dept.) and University of Versailles (France). After spending 2 years at Intel Compiler group in Santa Clara, he joined the University of Versailles as a Research Engineer, and afterward joined CEA (civilian department) still as a Research Engineer. Jean-Thomas was one of the founding members of the Exascale Research Centre, a joint lab between Intel, CEA and UVSQ, where he took the head of the performance group. He’s now actively participating in the development of DDN’s newly set Advanced Technology Center in France. Jean-Thomas is chairing two workshops focused on parallel file systems and performance scalability of file systems. He has authored or co-authored around 20 international publications.

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Tom Vierjahn is a Professor of Computer Science at the Westphalian University of Applied Sciences, Germany. There, he is working on visualization, rendering, and virtual reality. During his postdoc stay at RWTH Aachen University, Germany, he researched analysis and visualization of performance data acquired from massively parallel application runs on supercomputers. Furthermore, he applied in situ visualization to parallel simulations stemming from neuroscience research. Tom received his Diploma and Master's degree from Dusseldorf University of Applied Sciences, Germany. He received his PhD in computer science from the University of Münster, Germany, for his work on online surface reconstruction from unorganized point clouds with integrated texture mapping.

Thomas Theussl is currently a Visualization Scientist in the KAUST Visualization Core Lab. He received his M.S. in Computer Science from the Vienna University of Technology in 2000.

Steffen Frey is a is an Assistant Professor at the University of Groningen. His research interests are in visual analysis techniques for large and complex spatio-temporal data, with a particular focus on performance-related aspects and the expressive visual representations of dynamic processes.

Dr. Kenneth Moreland is a principal member of technical staff at Sandia National Laboratories. He received BS degrees in computer science and in electrical engineering from the New Mexico Institute of Mining and Technology in 1997. He received MS and Ph.D. degrees in computer science from the University of New Mexico in 2000 and 2004, respectively. Dr. Moreland specializes in large-scale visualization and graphics and has played an active role in the development of several HPC products including ParaView, VTK, IceT, Catalyst, Dax, and VTK-m. His current interests include the design and development of visualization algorithms and systems to run on multi-core, many-core, and future-generation computer hardware.

Dr. Guido Reina is senior lecturer and research associate at the Visualization Research Center of the University of Stuttgart. He received his diploma in Software Engineering and his Doctoral degree in Visualization from the University of Stuttgart. His research interests include large data visualization, parallel and in situ methods especially for particle data, focusing on molecular data sets. He is the MegaMol development team leader and interested in visualization system design and engineering as well as in long-term software sustainability issues.

Andy is a Research Mechanical Engineer at the United States Army Corps of Engineers. He works primarily on developing algorithms and interfaces for software that numerically discretizes partial differential equations (PDE). His focus has been on the finite element method (FEM) for spatial discretizations of the PDE using adaptive techniques and parallel computing to ensure efficient use of available computing resources. Previously, Andy was a Staff R&D Engineer at Kitware where he has worked on the Visualization Toolkit (vtk.org) and ParaView (paraview.org) open source projects focusing on ParaView Catalyst.

Dr. Stahlberg is director of Biomedical Informatics and Data Science (BIDS) at the Frederick National Laboratory for Cancer Research, spanning explorations from the molecular level to clinical trials. He has been instrumental in the laboratory's high-performance computing initiative and in assembling scientific teams across multiple, complex organizations to advance predictive oncology. Stahlberg has played a leadership role in establishing a collaboration between the NCI and the Department of Energy (DOE) to accelerate progress in precision oncology and computing. The Joint Design of Advanced Computing Systems for Cancer (JDACS4C) collaboration is rooted in three national initiatives and undertakes exploring predictive oncology and exascale computing in fundamental RAS biology, predicting tumor response, developing patient level health trajectories, and uses of AI to accelerate drug discovery. Dr. Stahlberg holds a Ph.D. in computational chemistry from The Ohio State University.

Thomas Steinke (organizer) heads the Supercomputing Dept. at the Zuse Institute Berlin (ZIB) and is responsible for the HPC research, consulting and operation His research interest is in high performance computing, heterogeneous systems for scientific and data analytics applications, and parallel simulation methods. Thomas leads the Intel Parallel Computing Center at ZIB since 2013. He received his Doctorate in Natural Sciences (Dr. rer. nat.) in chemistry from the Humboldt University of Berlin.

As Head of the Registry Informatics department at the Cancer Registry, responsibility include modernization and digitalisation of the Cancer Registry, including the development and deployment of an IKT-framework for cancer registries with electronic cancer reporting using the Norwegian Health Network, establishing the IT-system for the pilot project for Colorectal screening programme, modernization of the cervical cancer screening programme, and the insourcing the ICT-systems of the National Mammography programme. He is a board member of the CERTUS SFI, as well as serving on several reference and steering committees.

Marco Berghoff received the diploma degree in mathematics from the University of Paderborn, Germany, with a focus on microlocal analysis, numerics, and physics. He received the PhD degree in computational materials science from the Institute for Applied Materials. He has been a member of the Karlsruhe Institute of Technology, at the Institute for Applied Materials. He has years of experience in multiscale modeling and high-performance optimization, and with the scale-bridging of the atomistic phase-field crystal model to the mesoscopic phase-field method. As a postdoctoral researcher in the Simulation Laboratory “NanoMicro”, he has introduced the framework NAStJA, and currently leads the developments. He is involved in several activities within this project, in particular in the development of large-scale simulations for biological or material science research topics. The NAStJA Framework is used to simulate the growth and treatment of cancerous tumor with a cell geometric resolution.

Sunita Chandrasekaran is assistant professor in the Computer and Information Sciences Department at the University of Delaware. Her research interests include exploring the suitability of high-level programming models and runtime systems for HPC and embedded platforms, and migrating scientific applications to heterogeneous computing systems. Dr. Chandrasekaran was a post-doctoral fellow at the University of Houston and holds a Ph.D. from Nanyang Technological University, Singapore. She is a member of OpenACC, OpenMP, MCA and SPEC HPG. She has served on the program committees of various conferences and workshops including SC, ISC, ICPP, CCGrid, Cluster, and PACT, and has co-chaired parallel programming workshops co-located with SC, ISC, IPDPS, and SIAM.

Petrina Hollingsworth serves as an engagement manager for NCI-DOE collaborations at Frederick National Laboratory for Cancer Research.

Andreas Deutsch is head of the department of Innovative Methods of Computing at the Centre for Information Services and High Performance Computing (Dresden University of Technology). His research is focused on mathematical biology, especially cellular automata and agent-based modeling, cancer invasion and collective phenomena in the life sciences.

Emmanuelle Saillard is a tenured research scientist at Inria Bordeaux Sud-Ouest. She received her PhD in Computer science from the University of Bordeaux in 2015. From October 2015 to October 2016, she was employed as a postdoctoral researcher at the University of California Berkeley (USA). During this time, she developed dynamic program analyses for communication and synchronization optimizations in large scientific codes. From December 2016 to September 2017, she worked on the European project HPC4E. Her goal was to optimize kernels of some applications developed in the project with a metaprogramming language. In October 2017, she joined the STORM team at Inria Bordeaux. Her research interests focus on compiler/runtime interaction and code optimization. She has expertise in compiler technology, debugging and validation methods as well as parallel languages and codes.

Julien Jaeger is a research scientist at CEA. He received his PhD in Computer Science from the University of Versailles in 2012. After its PhD focusing on parallel code optimisation, he was hired at CEA to work on MPC, a framework combining an MPI, an OpenMP and a Pthread implementation on top of a user-level thread scheduler. Since 2019, he is the head of the MPC team. In addition to his position at CEA, Julien Jaeger teaches parallel programming and parallel optimisations in several schools. He participates actively to the MPI Forum. His main research interest is runtime stacking, with a focus on MPI implementations (collective algorithms and asynchronous progression) and their interactions with other parallel runtimes, along with compiler transformations for parallelism.

Dr. Baxter has been involved with computing since 1966, initially in hardware working with relay, discrete transistor logic and early Diode-Transistor Logic ICs. He learned to program with IBM 1401 (Autocoder), 1620 (Fortran) and 360 systems (BAL, PL/1, APL). He implemented one of the first commercial minicomputer timesharing systems on a Data General Nova in 1970, before receiving his B.S. in Computer Science (1973). During a brief stint in the numerical controls business, he designed and implemented a complete 16 bit virtual memory minicomputer, its OS and development tools for automated milling systems. In 1976, he started Software Dynamics, a systems software house, where he designed compilers, time-sharing and distributed network operating systems. The similarity in concepts and dissimilarity in implementation of the various OSes suggested that managing designs was key to managing long-lived software systems, and turned Ira's interests towards deeper software engineering research. In 1990, he received a Ph.D. in Computer Science from the University of California at Irvine, where he studied Software Engineering, focusing on design reuse using transformational methods. Dr. Baxter spent several years with Schlumberger, working on a PDE-solver generator for CM-5 supercomputers (Sinapse). He was consulting Research Scientist for Rockwell International, focusing on industrial control automation software engineering tools for several years.

Tim Jammer is a PhD candidate at the Institute for Scientific Computing at Technical University of Darmstadt. He received his Bachelor and Master degree from the University of Hamburg, while also working as a student research assistant at the DKRZ. His research interests are mainly in parallel and high performance computing with a particular focus on compiler-based analysis and rewriting tools for the efficient use of MPI. He is one of the authors and main contributors of the MPI correctness benchmark suite MPI-CorrBench, as well as other MPI-related tools that can be found at https://github.com/tudasc. In addition to his research position, he is a staff member at the Hessian Competence Center for High Performance Computing (www.hkhlr.de), providing user support and regular training courses for Hessian HPC users.

Julia Lawall is a senior research at Inria-Paris. Previously, she was on the faculty of the University of Copenhagen. She received her PhD in 1994 from Indiana University, USA. She has been program chair of GPCE, ICFP, and ASE, a member of the SIGPLAN Executive Committee, and is on the editorial board of Science of Computer Programming. Her research is at the crossroads of programming languages, software engineering, and operating systems. She is particularly interested in the design of tools that address problems in the maintenance of large software. She is the primary developer of the open-source Coccinelle program transformation system and has over 2000 patches in the Linux kernel based on her research.

Michael Blesel is a doctoral candidate at the Otto von Guericke University Magdeburg in the Parallel Computing and I/O group. His main research is in the field of compiler-assisted correctness checks for SPMD applications in the context of high-performance computing. During his time as a student at the University of Hamburg he has worked for the Scientific Computing group as a research and teaching assistant for their high-performance computing related courses. His interests include compiler-based tools, high-performance computing in general and performance optimizations for parallel applications.

Reed Milewicz is a senior member of technical staff in the Department of Software Engineering and Research within the Center for Computing Research at Sandia National Laboratories. He does research in the areas of software engineering, formal verification, and compilers. He believes that the quality of our lives depends upon the quality of our software, and that’s why he focuses on developing better practices, processes, and tools to target all phases of the software development lifecycle. This is a course of research that straddles the line between systems and human factors, and it’s carried out in close coordination with the communities he supports. Since joining Sandia in late 2016, his focus has been on the scientific software development community.

Dr. Dhabaleswar K. (DK) Panda is a Professor of Computer Science and Engineering at the Ohio State University. His research interests include parallel computer architecture, high-performance networking, InfiniBand, Exascale computing, Big Data, programming models, GPUs and accelerators, high-performance file systems and storage, virtualization, deep learning and cloud computing. He has published over 400 papers in major journals and international conferences related to these research areas. Dr. Panda and his research group members have been doing extensive research on modern networking technologies including InfiniBand, High-Speed Ethernet and RDMA over Converged Enhanced Ethernet (RoCE). Recently, Dr. Panda and his team have also developed high-performance RDMA-enabled Apache Hadoop and Memcached to accelerate Big Data applications. He is an IEEE Fellow and a member of ACM. More details about Prof. Panda are available at http://www.cse.ohio-state.edu/~panda.

Dr. Hari Subramoni received the Ph.D. degree in Computer Science from The Ohio State University, Columbus, OH, in 2013. He is a research scientist in the Department of Computer Science and Engineering at the Ohio State University, USA, since September 2015. His current research interests include high performance interconnects and protocols, parallel computer architecture, network-based computing, exascale computing, network topology aware computing, QoS, power-aware LAN-WAN communication, fault tolerance, virtualization, big data and cloud computing. He has published over 50 papers in international journals and conferences related to these research areas. Recently, Dr. Subramoni is doing research and working on the design and development of MVAPICH2, MVAPICH2-GDR, and MVAPICH2-X software packages. He is a member of IEEE. More details about Dr. Subramoni are available from http://www.cse.ohio-state.edu/~subramon.

Aamir is currently a Research Scientist in the Dept. of Computer Science & Engineering at the Ohio State University. He works as part of the Network-Based Computing Lab led by Dr. Dhabaleswar K. Panda. Aamir was an Associate Professor at FAST National University of Computing and Emerging Sciences in Lahore, Pakistan. Prior to joining FAST-NUCES, Aamir was at Imam Abdulrahman Bin Faisal University. Before that, he was affiliated with SEECS, NUST where he taught CS courses including Operating Systems and Parallel Computing. Aamir conducts research in the area of Parallel Computing, Multicore Computing, Data Center Computing, and Software-Defined Networking. In the academic year 2011, Dr Aamir Shafi was a visiting scholar at MIT where he worked with Professor Charles Leiserson on the Cilk technology.

Satoshi Matsuoka from April 2018 has become the director of Riken CCS, the top-tier HPC center that represents HPC in Japan, developing and hosting Japan’s tier-one ‘Fugaku’ supercomputer which has become the fastest supercomputer in the world in all four major supercomputer rankings, along with multitudes of ongoing cutting edge HPC research being conducted, including investigating Post-Moore era computing. He had been a Full Professor at the Global Scientific Information and Computing Center (GSIC), the Tokyo Institute of Technology since 2000, and the director of the joint AIST- Tokyo Tech. Real World Big Data Computing Open Innovation Laboratory (RWBC- OIL) since 2017, and became a Specially Appointed Professor at Tokyo Tech in 2018 along with his directorship at R-CCS. He has been the leader of the TSUBAME series of supercomputers that have won many accolades such as world #1 in power-efficient computing. He also leads various major supercomputing research projects in areas such as parallel algorithms and programming, resilience, green computing, and convergence of big data/AI with HPC. He has written over 500 articles according to Google Scholar, and chaired numerous ACM/IEEE conferences, including the Program Chair at the ACM/IEEE Supercomputing Conference (SC13) in 2013. He is a Fellow of the ACM and European ISC, and has won many awards, including the JSPS Prize from the Japan Society for Promotion of Science in 2006, presented by his Highness Prince Akishino; the ACM Gordon Bell Prize in 2011; the Commendation for Science and Technology by the Minister of Education, Culture, Sports, Science and Technology in 2012; the 2014 IEEE-CS Sidney Fernbach Memorial Award, the highest prestige in the field of HPC; HPDC 2018 Achievement Award from ACM; and recently SC Asia 2019 HPC Leadership Award.

Gilad Shainer serves as senior vice-president of marketing for Mellanox networking at NVIDIA, focusing on high- performance computing, artificial intelligence and the InfiniBand technology. Mr. Shainer joined Mellanox in 2001 as a design engineer and later served in senior marketing management roles since 2005. Mr. Shainer serves as the chairman of the HPC-AI Advisory Council organization, the president of UCF and CCIX consortiums, a member of IBTA and a contributor to the PCISIG PCI-X and PCIe specifications. Mr. Shainer holds multiple patents in the field of high-speed networking. He is a recipient of 2015 R&D100 award for his contribution to the CORE-Direct In-Network Computing technology and the 2019 R&D100 award for his contribution to the Unified Communication X (UCX) technology. Gilad Shainer holds a MSc degree and a BSc degree in Electrical Engineering from the Technion Institute of Technology in Israel.

Duncan Roweth is a Distinguished Technologist in the HPC and Mission Critical Business Unit CTO office at HPE. He joined HPE in Jan 2020 with the acquisition of Cray. While at Cray he worked on three generations of HPC network. He has been in a leading figure in the Slingshot program since its inception. He is currently working on design of 2nd and 3rd generation Slingshot products for future HPE systems. Duncan holds a Ph.D. from the University of Edinburgh.

As CEO of Cornelis Networks, Phil is responsible for the overall management and strategic direction of the company. Prior to co-founding Cornelis Networks, Phil served as a director at Intel Corporation, responsible for fabric platform planning and architecture, product positioning, and business development support. Prior to that role, Phil served as vice president of engineering and vice president of HPC technology within QLogic’s Network Solutions Group, responsible for the design, development, and evangelizing of all high-performance computing products, as well as all storage area network switching products. Before joining QLogic, Phil was vice president of engineering at SilverStorm Technologies, which he co-founded in 2000 and which was acquired by QLogic in 2006. SilverStorm’s core focus was on providing complete network solutions for high performance computing clusters. Prior to co-founding SilverStorm, Phil served as director of engineering at Unisys Corporation and was responsible for all I/O development across the company’s diverse product lines. Phil holds a BS in Mathematics from St. Joseph’s University and an MS in Computer and Information Science from the University of Pennsylvania.

Hemal Shah is a Distinguished Engineer and Systems/Software/Standards architect in the Data Center Solutions Group (DCSG) division at Broadcom Inc. He leads and manages a team of architects. Hemal is responsible for the definition of product architecture and software roadmap/architecture of all product lines of Ethernet NICs. Hemal led the architecture definition of several generations of NetXtreme E-Series/NetXtreme I server product lines and NetXtreme I client product lines. Hemal spearheaded the system architecture development of TruFlow technology for vSwitch acceleration/packet processing software frameworks, TruManage technology for system and network management, device security features, virtualization and stateless offloads. Hemal has defined the system architecture of RDMA hardware/software solutions for more than two decades. Before joining Broadcom in 2005, Hemal worked at Intel Corporation where he led the development of system/silicon/software architecture of communication processors, 10 Gigabit Ethernet controllers, TCP/iSCSI/RDMA offloads, and IPsec/SSL/firewall/VPN accelerations. Hemal is the lead technical representative/contributor from Broadcom Inc. in the Open Compute Project (OCP) and Distributed Management Task Force (DMTF). Hemal serves as Senior VP of Technology in the DMTF and a project co-lead of OCP Hardware Management project. Hemal has co-authored several OCP specifications, 70+ DMTF specifications, four IETF RFCs, and 10 plus technical conference/journal papers. Hemal is a named inventor on 40+ patents with several pending patents. Hemal holds Ph. D. (computer engineering) and M.S. (computer science) degrees from Purdue University, M.S.E.E. degree from The University of Arizona, and B.S. (electronics and communication engineering) degree from Gujarat University, India.

Moshe Voloshin is Systems architect in Data Center Solutions Group (DCSG) division at Broadcom Inc. Moshe spearheaded the system architecture development of ROCE and Congestion Control in Broadcom Ethernet NICs, involved in definition of product architecture, modeling, and system simulations. Previously Moshe was a Director, manager, ASIC/HW engineer at Cisco High End router division where he developed and managed the development of Network Processing Unit (NPU), QOS, and fabric ASICs, in products such as GSR and CRS.

Matthew Williams is CTO of Rockport Networks and has 25 years of technical leadership and engineering experience, 14 years as CTO of successful network technology companies and has 21 issued US patents. He is an expert strategist, analyst and visionary who has delivered on transformational product concepts. Matthew is an insightful and energetic communicator who enjoys product evangelization and inspiring global business and technical audiences. Matthew has a B.Sc. in Electrical Engineering with First Class Honours from Queen’s University, Kingston, Canada and is a registered P.Eng.

Sanjay is currently serving as Director Cloud Engineering at Oracle. His focus area is Machine Learning on HPC/GPU, Data Science Platform and Blockchain-As-A-Service on Oracle’s 2nd Generation Bare Metal Cloud Computing Services. His most recent contribution is creating the set of " Validated Solution Guides" for "Architecting Deep Learning on Oracle Cloud IaaS for Autonomous Driving". Sanjay has 28 years of progressive experience in Information Technology related to Security, Cryptography and Infrastructure-as-a-Service. He has the distinction of being the lead architect for Dell Services first ever Private Cloud launched in 2008 and Chief Network Architect for Dell’s vCloud Public Offering in 2010. His past roles also include being field CTO for VCE/EMC’s Managed Cloud Services for Converged Systems and an executive consultant for AWS ProServe Enterprise Advisory Services. Additionally Sanjay has served in advisory boards of companies focusing in Database Load-balancing and advanced trainings for virtualization and AI/ML. Sanjay is an alumnus of FinTech professionals from Oxford Said Business School. Sanjay has successfully completed advanced certificates on Design Thinking from Harvard, , Masters in Systems Design and Advanced courses in AI/ML from MIT and Professional MBA from Boston University. Sanjay is also an alumnus of Amazon Machine Learning University. Additionally he is an adjunct professor with Divergence Academy in Dallas. He has been awarded 5 Patents, so far. He is a regular speaker/presenter at Certified Information Security Conference, Quantum Optics and Computing, Annual Hamburg AIML Startup Conference, Oracle Open World, etc. His upcoming book is being published from Apress. He is a life member of ACM , SIAM, AAAI and Senior Member of IEEE and AMA.

Dr. Nitin Sukhija, is a Director of Center of Cybersecurity and Advanced Computing (C2AC), an assistant professor and one of the XSEDE Campus Champion specializes in the area of high performance data analytics and security. He has been involved in research and management of various projects pertaining to the HPC and software challenges in industry and academia for over a decade. Dr. Sukhija chaired and co-chaired many conferences such as ACM XSEDE16, ACM MEDES18, and IEEE WHPBDC(16, 17) conference and is also serving as an active member of the organizing committees of various esteemed (national and international) ACM and IEEE conferences and workshops, such as, XSEDE,IPDPS, PASA, ICPP, ISPDC, WHPBDC, SC EduHPC, SC18 Early Career Program, SIAM CSE Broader Engagement and others. He currently co-chairs the SIGHPC Education Chapter workshop committee and has been active in the planning and participation in HPC Training Workshops series at the SC, ISC and other conferences since 2015.

Through his position with the Shodor Education Foundation, Inc., Scott Lathrop is the Blue Waters Technical Program Manager for Education. Lathrop has been involved in high performance computing and communications activities since 1986. Lathrop coordinates the community engagement activities for the Blue Waters project. He helps ensure that Blue Waters education, outreach and training activities are meeting the needs of the community. Lathrop has been involved in the SC Conference series since 1989, served as a member of the SC Steering Committee for six years. He served as the Conference Chair for the SC’11 and XSEDE14 Conferences. He helped form the International HPC Training Consortium which was merged into the ACM SIGHPC Education Chapter during 2018, and has been active in the planning and participation in HPC Training Workshops at the SC and ISC Conferences.

Dr. Nia Alexandrova is the Training Manager at Hartree Centre. She was a Training Coordinator at BSC, Barcelona (2011- 16) and was involved in PRACE Projects 1-5, as a PRACE Advanced Training Centre coordinator. She has over 17 years of experience as a PG Studies Coordinator and Research Assistant at the School of Systems Engineering and ACET (Advanced Computing and Emerging Technologies) Centre at the University of Reading, at BSC and now at STFC. Her research is in the area of collaborative learning in technology-rich environments in university education and professional training and developing evaluation methodologies for professional training programs. She co-edited and co-authored the book entitled Technological Advances in Interactive Collaborative Learning as well as authored 30 research papers in journals and peer-reviewed conference proceedings, up to date. She is a co-chair of a number of training and education related workshops on HPC and Computational Science Conferences.

Andrew works on future HPC & AI capabilities for Azure, as part of the corporate engineering & product group. He joined Microsoft in early 2020, after nearly 25 years experience in the supercomputing community. Andrew has been an HPC end-user, researcher, software developer, HPC service manager, and impartial consultant. He has been a trusted voice on HPC strategy, technology evaluation and benchmarking, metrics, cost/value models and more. He has been lucky to have had rare exposure to state-of-practice in a wide range of HPC services/facilities across industry, government and academia around the world. Andrew is active on twitter as @hpcnotes.

Marjut manages NVIDIA’s Deep Learning Institute (DLI) in EMEA. In her role, Marjut is responsible for advising corporations, universities, and governments on the importance of AI and why now is the right time for employees to start developing their skills. Over the past four+ years, she has helped over 5000 organizations educate their staff.

Kevin McFall contributes to the NVIDIA Deep Learning Institute (DLI) as a Master Instructor by teaching workshops and supporting DLI certified instructors in the Europe, Middle East, and Africa region. He applies his prior academic experience as an educator and scholar to making the student experience in DLI workshops engaging and informative. His areas of expertise span computer vision, robotics, and autonomous systems.

Thor has an academic background in computational chemistry and materials science. After obtaining his Ph.D. from Stockholm University in 2011 he worked as a postdoc first at University College London and then the University of Iceland, before returning to a researcher position at Stockholm University. In 2016 Thor jumped over to HPC and worked as an application expert in molecular dynamics at the PDC HPC center at KTH. During this time he became increasingly drawn towards teaching workshops and developing training material, both at PDC and within the CodeRefinery project. Thor is passionate about helping researchers write better and more scalable code with less effort, is helping to build a community of research software engineers in the Nordics through the Nordic-RSE initiative, and enjoys programming in Julia.

Dr Mozhgan Kabiri Chimeh is a GPU developer advocate at NVIDIA helping to bring GPU and HPC to growing user community in Europe and around the world. She is a community builder with a passion for open source software and is actively involved in the HPC and RSE communities. As a Software Sustainability Institute fellow, and Research Software Engineer (RSE) advocate, she is actively promoting reproducible and sustainable software, use of HPC and particularly GPUs through training, seminars, research software consultancy and outreach. Prior to joining Nvidia, Mozhgan was a Research Software Engineer in Massive Scale Complex Systems Simulation with Accelerated Computing at the University of Sheffield, UK. She worked in the area of complex system modelling using emerging high-performance parallel architectures. Mozhgan served as the chair of the women in HPC series of workshops at the International Supercomputing Conference and was on the organizing and program committee of leading conferences in the HPC field. She holds a Ph.D. in computer science and a master's degree in Information Technology from the University of Glasgow, UK.

Weronika Filinger is an HPC Applications Consultant working at EPCC, The University of Edinburgh. She has been deeply involved in the design and development of the first Massive Open Online Course (MOOC) on Supercomputing and facilitated all runs of the course. She is teaching Practical Introduction to HPC – a postgraduate online course offered by the University of Edinburgh. For years Weronika has been a member of the EPCC outreach team, taking HPC related activities to public events. She is serving as the co-chair of the Outreach Committee of the ACM SIGHPC Education Chapter and the publicity chair of the International HPC Certification Program. She is also involved in running the International HPC Summer School. Over the years she has worked on a number of collaborative projects such as CRESTA, ADEPT, APES, SARGASSO and DEEP-EST, and provided consultancy for the Software Sustainability Institute.

Dr. Julie Mullen is a member of the technical staff in the MIT Lincoln Laboratory Supercomputing Center (LLSC), where she assists researchers in maximizing their use of high-performance computing resources in order to minimize their time to solution. As an expert in high-performance computing for computational engineering applications, she focuses on redesigning scientific workflows to streamline processing and improve the performance of computational engineering applications. Dr. Mullen leads the design and creation of online professional education courseware for the LLSC. As part of this effort, she facilitates the development of new tools for the Open edX platform to provide support for online Laboratory courseware. Her research includes learning analytics for adaptive learning design and the integration of hands-on physical construction and experimentation with massive open online course technologies. Her work has been published in both the scientific computing and educational domains.

Ann Backhaus has a passion for lifelong learning. Ann lives this passion, as exampled by her doing a ‘refresher’ Teaching and Learning Graduate Certificate “for fun” before joining Pawsey in 2019, even though she already had previous degrees as well as 25 years of experience in training and talent development in private industry and academia. “I enjoy teaching and learning at all levels and in all forms, from designing programs to developing content across a range of platforms,” says Ann.

Richard Lawrence obtained his Bachelor’s degree from the University of California, Davis in 2012 and his Master’s degree in 2018 from Texas A&M University, both in Physics. He has been a graduate student at Texas A&M University since 2014 pursuing his Ph.D., currently in progress. He works under the supervision of his advisor David Toback on a joint project between the Cryogenic Dark Matter Search collaboration and the Quantum Information Science group at Pacific Northwest National Laboratory, studying cryogenic silicon devices. Richard joined the High Performance Research Computing Group at Texas A&M University in 2020 as a User Support Specialist to assist with software maintenance and training for scientific research. He is interested in high-performance computing technologies including containers and machine learning. In his spare time Richard volunteers for a local Girl Scouts troop.

Janis Keuper is full professor for Data Science and Analytics at the Institute for Machine Learning and Analytics (IMLA), Offenburg University and scientific advisor at the "Large Scale Machine Learning" group at the Fraunhofer Competence Center for High Performance Computing. His current research is focused on scalable machine learning systems, especially Deep Learning. Before joining IMLA in 2019, he was a Group Leader at Fraunhofer ITWM and the Intel Visual Computing Institute (Saarbrücken, Germany). Janis was the chair of the Deep Learning tracs at the ISC Supercomputing 2017 and 2018 conference and member of the organizing committee of the "Machine Learning in HPC" Workshop at the ACM Supercomputing 2018/2019 conferences.

Sunna Torge is a senior researcher in the national AI and Big Data competence center ScaDS.AI Dresden/Leipzig at ZIH (TU Dresden). She obtained a diploma in mathematics (minor physics) from the University of Freiburg and a PhD in computer science with focus on mathematical logic and automated deduction. After working in the research group man-machine-interface at Sony International (Europe) and the machine learning group at University of Freiburg she was a full professor for theoretical computer science at the University of Applied Science Furtwangen. After her move to Dresden Sunna Torge worked in machine learning and data analytics groups within the TU Dresden and Fraunhofer Institute for Transportation and Infrastructure Systems with focus on text data analytics. Her main research topics currently are text and sequence analysis on large data sets.

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PD Dr. Juan José Durillo Barrionuevo (male) received the MSc and PhD degrees in computer science from the University of Málaga in 2006 and 2011. From 2011 to 2017, he worked as Assistant Professor at UIBK (Austria), where he also did his habilitation work focusing on workflow scheduling as the main topic. He has authored more than 50 publications in international journals, conferences and books. As a lecturer, he taught courses on optimisation, operating systems, GPU programming and C++. Since 2018, he has worked as a scientist at the BADW-LRZ. His research interests include automatic tuning of scientific applications, workflow scheduling, multi-criteria optimisation, GPU computing, and artificial intelligence.

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Daniel is an assistant professor and in the Electrical Engineering Department at the Technion, working in the areas of machine learning and neural networks. His recent works focus on resource efficiency and implicit bias in neural networks. He did his post-doc working with Prof. Liam Paninski in the Department of Statistics and the Center for Theoretical Neuroscience at Columbia University, and his Ph.D. in the Electrical Engineering Department at the Technion. He is the recipient of the Gruss Lipper Fellowship, the Taub Fellowship, the Goldberg Award, and Intel's Rising Star Faculty Award.

Nico Hoffmann, young investigator group leader. Nico earned his PhD in 2016 from Technische Universität Dresden in medical image analysis. He developed statistical machine learning methods for analysis of intraoperative neuroimaging data of the exposed human brain. He visited the Laboratory of Mathematics in Imaging of Harvard University from 2018 to 2019. During that time, he developed recurrent convolutional neural networks for reconstruction of nerve fibre bundles of the human brain. He is currently heading a Helmholtz AI Young Investigators Group at Helmholtz-Zentrum Dresden-Rossendorf “AI for Future Photon Sciences” researching Physics-guided Neural Networks for PDE learning as well as inverse problems.

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Ahmed Elnaggar is a Ph.D. candidate at the Technical University of Munich. His main focus of research is self-supervised learning on various modalities (Text, Protein, Source code, Images, and speech) using high-performance computing.

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Sadaf R. Alam is Chief Technology Officer (CTO) at the Swiss National Supercomputing Centre (CSCS) in Lugano, Switzerland. Dr. Alam studied computer science at the University of Edinburgh, UK, where she received her Ph.D. in 2004. Until March 2009, she was a computer scientist at the Oak Ridge National Laboratory, USA. In her role as the CTO, she ensures end-to-end integrity of HPC systems and storage solutions and leads strategic projects at the centre. She has held different roles at CSCS including group lead of future systems, chief architect and head of operations. She is a member of ACM, ACM-W, SIGHPC and Women in HPC.

David Hancock is the director for advanced cyberinfrastructure in IU's Research Technologies division. Hancock is responsible for directing IU's local and national high performance computing (HPC), storage, and cloud resources for research. Hancock is the primary investigator for the Jetstream project funded by the National Science Foundation (NSF). He is also responsible for directing IU system administrators who participate in the NSF XSEDE and Wrangler projects. Hancock is an active member in multiple HPC community organizations and currently a member on the board of the Cray User Group where he has served as president and vice president. Hancock is also an elected member of the XSEDE Advisory Board, and a representative in the XSEDE Service Provider (SP) Forum. Previously he served as the vice president for the IBM HPC User Group (SPXXL) and vice chair of the XSEDE SP Forum.

François Tessier has been a Research Scientist at Inria (Rennes, France) since November 2020. He received a Ph.D in Computer Science in 2015 from University of Bordeaux. His thesis focused on topology and affinity-aware process placement and load balancing algorithms for large-scale applications. From 2016 to 2018, he was a postdoctoral appointee at Argonne National Laboratory, IL, USA, within the LCF division (Leadership Computing Facility) where his research work has been more oriented towards I/O optimization in parallel libraries. Before joining Inria, he was a Computational Scientist at ETH Zürich within CSCS (Swiss National Supercomputing Center) located in Lugano, Switzerland, where he addressed the problem of dynamically provisioning of storage resources for HPC applications and large-scale workflows on supercomputers. At Inria, he is now working on various I/O and storage challenges in a context of HPC/Cloud convergence.

David Hancock is the director for advanced cyberinfrastructure in IU's Research Technologies division. Hancock is responsible for directing IU's local and national high performance computing (HPC), storage, and cloud resources for research. Hancock is the primary investigator for the Jetstream project funded by the National Science Foundation (NSF). He is also responsible for directing IU system administrators who participate in the NSF XSEDE and Wrangler projects. Hancock is an active member in multiple HPC community organizations and currently a member on the board of the Cray User Group where he has served as president and vice president. Hancock is also an elected member of the XSEDE Advisory Board, and a representative in the XSEDE Service Provider (SP) Forum. Previously he served as the vice president for the IBM HPC User Group (SPXXL) and vice chair of the XSEDE SP Forum.

Nic Bellingham joined the Met Office as a graduate in 1992 with a degree in Mathematics & Computer Science.  Most of her career has been in IT-focused roles, from developing mainframe and PC applications to working with the Programme that will deliver the Met Office’s Supercomputing capability through to 2032. In 2012 she moved from software engineering into an IT Service Management role, with responsibility for the delivery of a range of operational services, including forecaster applications and public and commercial web offerings. From 2014 to 2016, Nic was Deputy Head of IT Infrastructure & Operations with day-to-day responsibility for all Met Office IT services.  In late 2016, she became Head of IT Infrastructure & Operations, leading the delivery of the Met Office IT estate and associated services. Since April 2019 Nic has been seconded to the Met Office’s Supercomputing Programme, leading the engagement with the Programme from the organisation’s Technology directorate.

Stig has a background in R&D working for various prominent technology companies, particularly in HPC and software-defined networking. Stig is now CTO for StackHPC, a consultancy specialising in the convergence of cloud, HPC and big data. Stig is also co-chair of the OpenStack Scientific Special Interest Group, a globally-distributed grouping of research institutions using OpenStack for research computing use cases

Andrew leads planning of future capabilities for HPC & AI within Microsoft Azure, as part of the corporate engineering & product group. He joined Microsoft in early 2020, after nearly 25 years experience in the supercomputing community. Andrew has been an HPC end-user, researcher, software developer, HPC service manager, and impartial consultant. He has been a trusted voice on HPC strategy, technology evaluation and benchmarking, metrics, cost/value models and more. He has been lucky to have had rare exposure to state-of-practice in a wide range of HPC services/facilities across industry, government and academia around the world. Andrew is active on twitter as @hpcnotes.

Arjun Shankar is a distinguished staff member and the section head for Advanced Technologies in the National Center for Computational Sciences at Oak Ridge National Laboratory (ORNL). He also directs the Compute and Data Environment for Science (CADES) institutional computing capability at ORNL. Arjun’s research in the national laboratory setting has involved designing large-scale data analysis and modeling systems, sensor networking systems, energy grid monitoring and control frameworks, and deploying middleware to overlay data, computation, and control across systems and infrastructure. His sponsored R&D project outputs have several active users in the federal government as well as in the commercial sector. His research has resulted in over seventy peer-reviewed publications including those that address jointly modeling and simulating systems coupled with observational data, incorporating policy constraints, and creating scalable cross-facility data infrastructures. Arjun received his B.Tech. from the Indian Institute of Technology, Mumbai, and his M.S. and Ph.D. in computer science from the University of Illinois, Urbana. He has served on the DOE ASCAC subcommittee on Scientific and Technical Information, is a member of the AAAS, and a Senior Member of the ACM and the IEEE.

Bjoern Enders joined NERSC in 2019 as a Data Science Workflows Architect in the Data Science Engagement Group where he liaises with various large-scale experimental facilities, engages with the wider scientific workflows community and contributes to NERSC's API efforts. He works towards a future where HPC resources integrate seamlessly and effortlessly into experimental science workflows. Bjoern has a background in software development for experimental sciences with a specialization for computational microscopy at synchrotron light sources. He holds a PhD in Physics from the Technical University of Munich, Germany and a MSc equivalent degree in physics from the University of Goettingen, Germany.

Gabor has decades of experience building, maintaining and debugging large-scale web applications. He started his career at Berkeley Lab in the 1990-s. A few years later, he worked as a back-end and fullstack software engineer for various start-ups and larger companies. After about 20 years in the private sector, he is now working for NERSC and couldn't be more excited to use his experience to make computing for science run smoother. Gabor's recent contributions are Iris, the NERSC banking and account management system, as well as the Superfacility API which allows for programmatic access to NERSC resources.

Christopher Haine earned in 2017 a Ph.D. from the University of Bordeaux, on the topic of loop kernel optimisation and data layout restructuring. Christopher then joined Cray (now HPE) in the HPC/AI EMEA Research Lab, where he focuses on data-aware middleware, data movement in complex memory hierarchies, and optimisation and programmability of scientific applications and workflows.

Florina Ciorba is an Associate Professor of High Performance Computing at the University of Basel, Switzerland. She received her Diploma in Computer Engineering in 2001 from University of Oradea, Romania and her doctoral degree in Computer Engineering in 2008 from National Technical University of Athens, Greece. She has held postdoctoral research associate positions at the Center for Advanced Vehicular Systems at Mississippi State University, Mississippi State, USA (2008 to 2010) and at the Center for Information Services and High Performance Computing at Technische Universität Dresden, Dresden Germany (2010-2015). Her research interests include parallelization, dynamic load balancing, loop scheduling, robustness, resilience, scalability, reproducibility of scientific applications executing on small to large scale parallel computing systems, and system and application monitoring for improving their operations. More information at https://hpc.dmi.unibas.ch/en/people/florina-ciorba/

Daniele Tafani received his PhD in Electronic Engineering from Dublin City University (DCU) in 2012, where he conducted research on analytic modelling and resource optimisation of optical burst switched networks. He worked at the IBM Tivoli Rome Labs as a software engineer, and was a visiting researcher at the University of Ottawa, where he developed algorithms for energy-efficient light paths in computational grids. Daniele spent 8 years as a research scientist in the High-Performance Systems division of the Leibniz Supercomputing Centre (LRZ), focusing his interests on energy efficiency of HPC systems, scalable sensor monitoring and operational data analytics. He is now Technical Product Manager at Fujitsu.

Utz-Uwe Haus is a Senior Research Engineer at CRAY. He studied Mathematics and Computer Science at the TU Berlin. After obtaining a Doctorate in Mathematics at the University of Magdeburg he worked on nonstandard applications of Mathematical Optimization in Chemical Engineering, Material Science and Systems Biology. After 5 years as a Senior Researcher at the Department of Mathematics at ETH Zürich he is now leading the Cray European Research Lab in Basel, developing the Mathematical Optimization and Operations Research group, working on data-dependency driven workflow optimization on future HPC architectures.

Nicolas Lachiche received his PhD in Computer Science from the University of Nancy, France in 1997, where he conducted research on machine learning. After a postdoc at the University of Bristol, he joined the University of Strasbourg as an associate professor. He is the head of the Data Science and Knowledge research group in the ICube laboratory. His research interests are in mining relational or sequential data.

Ann Gentile is the Manager of the HPC Development Department at Sandia National Laboratories. Prior to that, she was a Distinguished Member of Technical Staff and she continues her interests in Resource-Aware Computing in her current role. Ann is a co-author of the R&D 100 award-winning, open source Lightweight Distributed Metric Service (LDMS) which is deployed at large-scale HPC sites within the US national labs and the NSF for monitoring and resource utilization understanding on large-scale HPC systems. HPE/Cray has implemented LDMS in its monitoring solution to be part of every currently announced NNSA exascale machine. Ann serves on investment area teams determining priorities for Sandia’s Computational CoDesign and Trusted AI Research and on evaluation teams of extreme-scale architectures for the US national labs. Ann is also a co-founder of the Workshop on Monitoring and Analysis for High Performance Computing Systems Plus Applications (HPCMASPA), now in its 9th year held in conjunction with IEEE Cluster. She earned her Ph.D. in Chemical Physics and M.S. in Chemistry from UIUC and her B.S. in Physics from Carnegie-Mellon University.

Natalie Bates has led the Energy Efficient High Performance Computing Working Group (EE HPC WG) since its inception in 2010. The purpose of the WG is to drive implementation of energy efficient design in HPC. Today, there are ~800 members from 25+ countries. Natalie has been the technical and executive leader for this ‘open source’ working group that disseminates best practices, shares information (peer to peer exchange), and takes collective action. The EE HPC WG has collaborated and negotiated with industry standards committees and major HPC organizations as well as influenced HPC system development. Prior to leading the EE HPC WG, Natalie's career spanned twenty years with Intel Corporation where she was a senior manager of highly complex programs taking new products to market, delivering multi-component and multi-partner platforms, and negotiating strategic technical industry initiatives.

Torsten is a system architect for Exascale monitoring and system power and energy management at Hewlett Packard Enterprise (HPE). His research activities are related to high volume, high frequency data collection and analytics for improved IT operations as well as dynamic power management. He is the lead architect for HPE's Exascale monitoring framework developed as part of the ECP funded PathForward project. Torsten is part of the leadership team of the Energy Efficient High Performance Computing Working Group (EE HPC WG) and currently serves as the Workshop and Conferences Co-Chair. Torsten received his MSc in parallel and scientific computation from the University of Liverpool, UK, and a MSc in Computer Engineering from the University of Applied Sciences in Berlin, Germany. He received his Dr. rer. nat. degree ​in computer science from the Technical University of Munich, Germany, in 2018.

Ales Zamuda received his B.Sc., M.Sc., and Ph.D. degrees in computer science from University of Maribor, Slovenia, in 2006, 2008, and 2012, respectively. As an affiliate of Faculty of Electrical Engineering and Computer Science at the University of Maribor he acts within research group Computer Architecture and Languages Laboratory and programme-funded unit Computer Systems, Methodologies, and Intelligent Services. His areas of interest include evolutionary algorithms, multicriterion optimization, artificial life, and computer animation. He has written over 50 scientific papers and among them several journal papers ranked in first quarter of computer science category such as Applied Soft Computing and Information Sciences and received several citations of his scientific works.

Martin Molan is a PhD student of data science and computation at University of Bologna. He has received BA in mathematics at University of Ljubljana and MA in ICT at JSI institute. As a student he has collaborated with CERN openlab, UCL center for AI, UNESCO International Research Center On Artificial Intelligence, and CINECA.

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Michael Alexander holds degrees in electrical engineering (TGM), business administration (University of Southern California) and economics (University of Vienna). He is currently performing large data analytics for multiple domains and the architecting of clusters. His professional experience includes education and product management at IBM, and Alcatel. Prior he was a HPC Specialist at TU Wien and a Product Line Manager for Alcatel ADSL and Optical Access Networks. He is the author of a textbook on networks and network security published by Hüthig/Verlagsgruppe Süddeutsche, and editor of a special issue on mathematical methods in network management of the Wiley International Journal of Network Management. For the last sixteen years, he has served as the Program Committee Chair for VHPC, Workshop on Virtualization in High-Performance Cloud Computing. His current research interests include content centric networking, distributed databases, virtualization system-network management.

With over 12 years of experience in Virtualization technologies, Anastassios Nanos is currently working on the lower-level parts of the stack to attack issues related to performance, scalability, power-efficiency, and security in hypervisors. Previously, he was a post-doc at CSLab, NTUA, working on bridging the gap between common HPC practices and virtualization. His research interests include I/O Virtualization, systems software for high-performance I/O in virtualized environments, systems support for heterogeneous platforms, communication architectures for clusters, and scalable storage architectures based on clusters. He holds a Diploma in Engineering (2006) from ECE, NTUA and a PhD in Computer Engineering (2013) from NTUA. He has been involved in EU-funded projects, conducting research in emerging, power-efficient micro-server architectures on scalable network and storage I/O, and energy-driven resource management in cloud architectures.

With over 12 years of experience in Virtualization technologies, Anastassios Nanos is currently working on the lower-level parts of the stack to attack issues related to performance, scalability, power-efficiency, and security in hypervisors. Previously, he was a post-doc at CSLab, NTUA, working on bridging the gap between common HPC practices and virtualization. His research interests include I/O Virtualization, systems software for high-performance I/O in virtualized environments, systems support for heterogeneous platforms, communication architectures for clusters, and scalable storage architectures based on clusters. He holds a Diploma in Engineering (2006) from ECE, NTUA and a PhD in Computer Engineering (2013) from NTUA. He has been involved in EU-funded projects, conducting research in emerging, power-efficient micro-server architectures on scalable network and storage I/O, and energy-driven resource management in cloud architectures.

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Valeriu Codreanu studied Electrical Engineering and got his MSc at the Polytechnic University of Bucharest. He followed-up with a PhD in Computer Architecture at the same institute, graduating in 2011. Valeriu continued as a researcher at Eindhoven University of Technology and University of Groningen, working on GPU computing, computer vision, and embedded systems. In 2014, he joined SURFsara as an HPC consultant, and in 2016 he became the PI of an Intel Parallel Computing Center project on ‘Scaling up deep learning’. Valeriu is currently leading the High-Performance Machine Learning group at SURFsara, and is focused on applying deep learning techniques to real-world applications from various scientific fields.

Dr. Ian Foster is the Director of Argonne’s Data Science and Learning Division, Argonne Senior Scientist and Distinguished Fellow and the Arthur Holly Compton Distinguished Service Professor of Computer Science at the University of Chicago. Foster’s research contributions span high-performance computing, distributed systems, and data-driven discovery. He has published hundreds of scientific papers and eight books on these and other topics. Methods and software developed under his leadership underpin many large national and international cyberinfrastructures. Foster received a BSc (Hons I) degree from the University of Canterbury, New Zealand, and a PhD from Imperial College, United Kingdom, both in computer science. His awards include the Global Information Infrastructure (GII) Next Generation award, the British Computer Society’s Lovelace Medal, R&D Magazine’s Innovator of the Year, the IEEE Tsutomu Kanai award.

Dr. Zhao Zhang is a computer scientist at Texas Advanced Computing Center. His current research focus is scalable deep learning on supercomputers. Dr. Zhang's past work include astronomy data processing with Apache Spark, machine learning diagnostics, and I/O optimization for many-task computing applications on supercomputers, such as Argonne's IBM Blue Gene/P. Before joining TACC, Dr. Zhang was a postdoc researcher in AMPLab and a data science fellow at Berkeley Institute for Data Science at University of California, Berkeley, working with Prof. Michael J. Franklin. He received Ph.D in computer science from University of Chicago in 2014 under supervision of Prof. Ian T. Foster.

Torsten is a Professor of Computer Science at ETH Zürich, Switzerland. He is also a key member of the Message Passing Interface (MPI) Forum where he chairs the "Collective Operations and Topologies" working group. His research interests revolve around the central topic of "Performance-centric System Design" and include scalable networks, parallel programming techniques, and performance modeling. Torsten won best paper awards at the ACM/IEEE Supercomputing Conference SC10, SC13, SC14, SC19, EuroMPI'13, HPDC'15, HPDC'16, IPDPS'15, and other conferences. He published numerous peer-reviewed scientific conference and journal articles and authored chapters of the MPI-2.2 and MPI-3.0 standards. He received the Gordon Bell Prize, the Latsis prize of ETH Zurich, as well as ERC starting and consolidator grants. Additional information about Torsten can be found on his homepage at htor.inf.ethz.ch.

Arvind Ramanathan is a computational biologist in the Data Science and Learning Division at Argonne National Laboratory and a senior scientist at the University of Chicago Consortium for Advanced Science and Engineering (CASE). His research interests are at the intersection of data science, high performance computing and biological/biomedical sciences. His research focuses on developing scalable statistical inference techniques for studying complex biological phenomena. He obtained his Ph.D. in computational biology from Carnegie Mellon University, and was the team lead for integrative systems biology team at Oak Ridge National Laboratory. More information about his group and research interests can be found at http://​ramanathanlab​.org.

Alexandre Bonvin studied Chemistry at Lausanne University, Switzerland and obtained his PhD at Utrecht University in the Netherlands (1993). After two post-docs at Yale (USA) and the ETHZ (CH) he joined Utrecht University in 1998 where I was appointed full professor of computational structural biology in 2009. He is currently Scientific Director of the Bijvoet Centre for Biomolecular Research. His group is developing and operating the HADDOCK integrative modelling platform.

Manon Réau studied Biotechnologies at Sup’Biotech Paris and In Silico Drug Design at the University of Paris. She obtained her PhD in bioinformatics at the Conservatoire National des Arts et Métiers in 2019 and joined Utrecht University in 2020 to study different computational approaches to predict and understand molecular interactions. During this post-doc, she specialized in deep learning, and developed Deeprank-GNN in collaboration with the eScience Center, Amsterdam.

Stefan graduated from the Technical University in Aachen with a Master’s in Physics and went to a Stuttgart for a PHD on soft matter physics simulating DNA. He moved to industry to different data science positions. In 2020 he joined the Jülich Supercomputing Center to head a group of AI consultants supporting scientists from various domains in applying AI methods on supercomputers.

Jonas is currently the "AI for Oncology" group leader at the Netherlands Cancer Institute. Previously, after his studies in Applied Mathematics at the Delft University of Technology he completed his PhD titled "Shedding new light on Gaussian harmonic analysis" at the same university. He started as a postdoctoral researcher in 2016 at the Netherlands Cancer Institute/Antoni van Leeuwenhoek hospital and continued within the Diagnostic Image Analysis Group at the Radboud Medical Center. His current work focuses on efficient deep learning algorithms for cancer detection in breast image modalities.

Chen Liu is a Principal Hardware Engineer at Sambanova Systems, leading the development of multiple HPC applications that leverage Sambanova's Software & Hardware stack, achieving State-of-the-Art performance and accuracy. He is working on the verification, performance and productization on Sambanova's solutions, ensuring coordination, concurrency and correctness of scalable HPC/ML applications with reconfigurable dataflow architecture.

Pete Beckman is the co-director of the Northwestern-Argonne Institute for Science and Engineering. From 2008-2010 he was the director of the Argonne Leadership Computing Facility, where he led the Argonne team working with IBM on the design of Mira, a 10 petaflop Blue Gene/Q. Pete coordinates the collaborative research activities in extreme-scale computing between the US Department of Energy and Japan’s ministry of education, science, and technology (MEXT), and leads Argo, an Exascale Computing Project focused on low-level resource management for the OS and runtime. He is the founder and leader of the Waggle project for AI@Edge. The Waggle technology and software framework is being used by the Chicago Array of Things project and is deployed in over 10 cities around the world. Dr. Beckman has a Ph.D. in Computer Science from Indiana University (1993)

Swann Perarnau is an Assistant Computer Scientist at Argonne. He leads the topology, memory and power management efforts for the Argo ECP project. In particular, he is designing low-level system software mechanisms to help applications discover the features and performance of complex heterogeneous hardware, as well as composable abstractions to make the most efficient use of it.

Rosa M. Badia holds a PhD from the UPC (1994). She is the manager of the Workflows and Distributed computing group at the Barcelona Supercomputing Center (BSC). She is a Scientific Researcher at the Spanish National Research Council (CSIC). She graduated on Computer Science at the Facultat d' Informàtica de Barcelona (UPC, 1989). She was lecturing and doing research at the Computer Architecture Department (DAC) at the UPC from 1989 to 2008, where she held an Associate Professor position from 1997 to 2008; she is currently part-time lecturing again at the same department.

Kentaro Sano is the team leader of the Processor Research team at RIKEN. Dr. Kentaro Sano received his Ph.D. from GSIS, Tohoku University, in 2000. Since 2000 until 2005, he had been a Research Associate at Tohoku University. Since 2005 until 2018, he has been an Associate Professor at Tohoku University. He was a visiting researcher at the Department of Computing, Imperial College, London, and Maxeler corporation in 2006 and 2007. Since 2017 until present, he has been a team leader of a processor research team at R-CCS, Riken. His research interests include FPGA-based high-performance reconfigurable computing systems especially for scientific numerical simulations and machine learning, high-level synthesis compilers and tools for reconfigurable custom computing machines, and system architectures for next-generation supercomputing based on the data-flow computing model.

Valentin Reis is a Software Engineer at Groq, Inc. He previously was a Postdoctoral appointee at Argonne National Laboratory and obtained his PhD from the University of Grenoble Alpes. His interests span machine learning, functional programming and HPC infrastructure.

Prasanna Balaprakash is a computer scientist with a joint appointment in the Mathematics and Computer Science Division and the Leadership Computing Facility at Argonne National Laboratory. His research work spans the areas of artificial intelligence, machine learning, optimization, and high-performance computing. He is a recipient of the U.S. Department of Energy 2018 Early Career Award. Prior to Argonne, he worked as a Chief Technology Officer at Mentis Sprl, a machine learning startup in Brussels, Belgium. He received his PhD from CoDE-IRIDIA (AI Lab), Université Libre de Bruxelles, Brussels, Belgium, where he was a recipient of European Commission’s Marie Curie and Belgian F.R.S-FNRS Aspirant fellowships.

Rob Schreiber is a Distinguished Engineer at Cerebras Systems, Inc., where he works on architecture and programming of systems for accelerated training of deep neural networks. Before Cerebras he taught at Stanford and RPI and worked at NASA, at startups, and at HP. Schreiber’s research spans sequential and parallel algorithms for matrix computation, compiler optimization for parallel languages, and high performance computer design. With Moler and Gilbert, he developed the sparse matrix extension of Matlab. He created the NAS CG parallel benchmark. He was a designer of the High Performance Fortran language. Rob led the development at HP of a system for synthesis of custom hardware accelerators. He has help pioneer the exploitation of photonic signaling in processors and networks. He is an ACM Fellow, a SIAM Fellow, and was awarded, in 2012, the Career Prize from the SIAM Activity Group in Supercomputing.

Tony Hey is a Fellow of the Royal Academy of Engineering, the Association for Computing Machinery, and the American Association for the Advancement of Science. At the University of Southampton in the UK, his parallel computing research group designed and built one of the first distributed memory message-passing computers using innovative Inmos transputers. He was later Head of the Electronics and Computer Science Department at Southampton and also Dean of Engineering. In 2005 he was awarded a CBE for Services to Science after leading the UK’s eScience initiative. After 10 years as Corporate Vice President for Technical Computing in Microsoft in the US, he returned to the UK and has been Chief Data Scientist at STFC’s Rutherford Appleton Laboratory since 2015. He was one of the originators of the MPI message passing standard in 1992 and was awarded the 2019 Lifetime Achievement Award by the International Open Benchmark Council. In 2020 he chaired a US Department of Energy subcommittee that explored ‘the opportunities and challenges from Artificial Intelligence and Machine Learning for the advancement of science and technology’ or, as a shorthand, ‘AI for Science’.

Michaela Blott is a Distinguished Engineer at Xilinx Research in Dublin, Ireland, where she heads a team of international scientists driving exciting research to define new application domains for Xilinx devices, such as machine learning, in both embedded and hyperscale deployments. She earned her Master’s degree from the University of Kaiserslautern in Germany and has over 25 years of experience in leading edge computer architecture and advanced FPGA and board design, in research institutions (ETH Zurich and Bell Labs) and development organizations. She is heavily involved with the international research community serving as the technical co-chair of FPL’2018, workshop organizer (H2RC), industry advisor on numerous EU projects, member of numerous technical program committees (FPL, ISFPGA, DATE, etc.) and winner of the WMB award in 2015 and finalist of VentureBeat Women in AI’2019, and Women in Technology‘2019 awards.

Tianjian Lu is currently a software engineer at Google Research. He received the B.E. degree from the National University of Singapore in 2010, and the M.S. and Ph.D. degrees from the University of Illinois at Urbana-Champaign in 2012 and 2016, respectively, all in electrical engineering. His research interests include multiphysics modeling and simulation, high-performance computing, and machine learning. He was the recipient of the Best Student Paper Award (The First Place Winner) at the 31st International Review of Progress in ACES, Williamsburg, VA, USA, in 2015, the Best Student Paper Award at the IEEE Electrical Design of Advanced Packaging and Systems, Honolulu, HI, USA, in 2016, and the P. D. Coleman Outstanding Research Award by the Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, in 2016.

Haohuan Fu is a professor in the Ministry of Education Key Laboratory for Earth System Modeling, and Department of Earth System Science in Tsinghua University, where he leads the research group of High Performance Geo-Computing (HPGC). He is also the deputy director of the National Supercomputing Center in Wuxi, leading the research and development division. Fu has a PhD in computing from Imperial College London. His research work focuses on providing both the most efficient simulation platforms and the most intelligent data management and analysis platforms for geoscience applications, leading to two consecutive winning of the ACM Gordon Bell Prizes (nonhydrostatic atmospheric dynamic solver in 2016, and nonlinear earthquake simulation in 2017).

Ryousei Takano is a senior researcher of the Institute of Advanced Industrial Science and Technology (AIST), Japan. He received his Ph.D. from the Tokyo University of Agriculture and Technology in 2008. He joined AXE, Inc. in 2003 and then, in 2008, moved to AIST. His research interests include operating systems and parallel and distributed computing. He is currently exploring system software for enabling a computing continuum.

Hatem Ltaief is a Principal Research Scientist in the Extreme Computing Research Center at KAUST, where is also advising several KAUST students in their MS and PhD research. His research interests include parallel numerical algorithms, parallel programming models, performance optimizations for manycore architectures and high performance computing. Hatem received the engineering degree from Polytech Lyon at the University of Claude Bernard Lyon I, the MSc in applied mathematics and the PhD degree in computer science at the University of Houston. He has contributed to the integration of numerical algorithms into mainstream vendors’ scientific libraries, such as NVIDIA cuBLAS and Cray LibSci. He has been collaborating with domain scientists, i.e., astronomers, statisticians, computational chemists and geophysicists, on leveraging their applications to meet the challenges at exascale.

Bilel Hadri is a computational scientist at the Supercomputing Lab at KAUST since July 2013. He is leading efforts in benchmarking and performance optimization and helping in coordinating strategic efforts for systems procurements, upgrades and provides regular training to users. He received his Master in Applied Mathematics and his PhD in Computer Science from the University of Houston in 2008. He joined the National Institute for Computational Science at Oak Ridge National Lab as a computational scientist in December 2009 following a Postdoctoral Position in June 2008 at the University of Tennessee Innovative Computing Laboratory lead by Dr. Jack Dongarra. His expertise area includes Linear Algebra, Numerical Analysis, Performance Analysis Tuning and Optimization, System Utilization Analysis, Monitoring and Library Tracking Usage.

David Keyes directs the Extreme Computing Research Center at the King Abdullah University of Science and Technology (KAUST), where he was the founding Dean of the Division of Mathematical and Computer Sciences and Engineering in 2009 and currently serves in the Office of the President as Senior Associate for strategic priorities and institutional partnerships. He works at the interface between parallel computing and partial differential equations and statistics, with a current focus on scalable algorithms exploiting data sparsity in the context of the HiCMA software library. David Keyes received the BSE degree in aerospace and mechanical sciences from Princeton University, in 1978, and the PhD degree in applied mathematics from Harvard University, in 1984. He works at the interface between parallel computing and the numerical analysis of PDEs, with a focus on scalable implicit solvers. He helped develop and popularize the Newton-Krylov-Schwarz (NKS), Additive Schwarz Preconditioned Inexact Newton (ASPIN), and Algebraic Fast Multipole (AFM) methods. He is a fellow of the SIAM, AMS, and AAAS and has been awarded the ACM Gordon Bell Prize, the IEEE Sidney Fernbach Award, and the SIAM Prize for Distinguished Service to the Profession.

Daniel Grünewald received a PhD in theoretical high energy physics from Ruprecht-Karls-Universität Heidelberg, Germany in 2008. He joined the Competence Center for High Performance Computing (CC-HPC) at the Fraunhofer institute for industrial mathematics (Fraunhofer ITWM) in Kaiserlautern, Germany in 2009. He works at the interface between the low level HPC tools developed at CC-HPC and their application in large scale simulations. He has provided major contributions to the development of the Gaspi specification, a PGAS communication API striving for extreme scalability. His current focus is on the extension of the GPI-2 ecosystem. GPI-2 is the Gaspi reference implementation developed at CC-HPC. Part of this effort is GaspiLS, a Gaspi based linear solver library providing an abstract high level linear algebra interface which hides the complexity of a scalable and hybrid parallel implementation from the domain expert.

Laura Grigori is a senior research scientist at INRIA in France, where she leads the Alpines group, a joint group between INRIA and the J.L. Lions Laboratory, Sorbonne University, in Paris. She leads several projects on preconditioning, communication avoiding algorithms and associated numerical libraries for large scale parallel/multicore machines. After postdoctoral research at the University of California, Berkeley and the Lawrence Berkeley National Laboratory, she became a researcher for INRIA in 2004, and became the head of the Alpines project in 2013. In 2020 Grigori was named a SIAM Fellow "for contributions to numerical linear algebra, including communication-avoiding algorithms". In 2021, she joined the SIAM Council as a Member-at-Large.

Alfredo is the Principal Investigator of the SOLHARIS project that aims at developing algorithms, programming models and scheduling methods that improve the scalability of sparse linear algebra solvers and, in general, of scientific computing libraries, on large scale parallel hand heterogeneous supercomputers. His research activity focuses on Computational Linear Algebra. This discipline deals with the issues related to the efficient and numerically reliable computation of linear algebra operations arising in numerous scientific and industrial applications from a wide range of domains including physics, chemistry or data analysis.

Hartwig Anzt is a Helmholtz-Young-Investigator Group leader at the Steinbuch Centre for Computing at the Karlsruhe Institute of Technology. Where he obtained his PhD in Mathematics He joined Jack Dongarra's Innovative Computing Lab at the University of Tennessee in 2013. Since 2015 he also holds a Senior Research Scientist position at the University of Tennessee. He teaches courses on numerics for HPC and related topics, including scientific computing and machine learning on modern architectures. In 2017, he contributed to the ISC-tutorial on Numerical Linear Algebra. Hartwig Anzt has a long track record of high-quality software development. He is author of the MAGMA-Sparse and lead and developer of the Ginkgo numerical linear algebra library, both part of the US Exascale Computing Project for production-ready numerical linear algebra. According to Google Scholar, Hartwig Anzt authored more than 60 journal and conference articles, and has an h-index of 16 and an i10-index of 31.

Ulrike Meier Yang leads the Mathematical Algorithms and Computing group in the Center for Applied Scientific Computing at LLNL. She leads the xSDK4ECP (Extreme-scale Scientific Software Development Kit for the ECP) project, which is part of the Software Technologies component of the Exascale Computing Project (ECP). She is a member of the Scalable Linear Solvers and hypre project, and the Linear Solvers Topical Area Lead in the SciDAC FASTMath Institute. Her research interests are numerical algorithms, particularly iterative linear system solvers and algebraic multigrid methods, high performance computing, parallel algorithms, performance evaluation and scientific software design. She is serving on the editorial boards of SIAM Journal for Matrix Analysis and Applications and Journal of Parallel and Distributed Computing. Prior to joining LLNL in 1998, she was a staff member in the Center for Supercomputing Research and Development at the University of Illinois at Urbana-Champaign (1985-1995) and in the Central Institute of Applied Mathematics at the Research Centre Jülich, Germany (1983-1985). She earned her Ph.D. in Computer Science at the University of Illinois at Urbana-Champaign in 1995 and a Diplom in mathematics at the Ruhr-University Bochum, Germany, in 1983.

John Shalf is Department Head for Computer Science Lawrence Berkeley National Laboratory, and recently was deputy director of Hardware Technology for the DOE Exascale Computing Project. Shalf is a coauthor of over 80 publications in the field of parallel computing software and HPC technology, including three best papers and the widely cited report “The Landscape of Parallel Computing Research: A View from Berkeley” (with David Patterson and others). Prior to coming to Berkeley Laboratory, John worked at the National Center for Supercomputing Applications and the Max Planck Institute for Gravitation Physics/Albert Einstein Institute (AEI) where he was a co-creator of the Cactus Computational Toolkit.

Cristiano Malossi is Manager of the AI Automation group at IBM Research - Zurich. The group focuses on creating solutions for scalable AI model development and deployment on Cloud and High-Performance on-prem systems. Since 2017 Cristiano is coordinator of the FET-H2020 OPRECOMP project, with focus on low-power/low-energy computing paradigms based on approximation and transprecision. Cristiano is a recipient of the 2016 IPDPS Best Paper Award and the 2015 ACM Gordon Bell Prize. Since 2015 he is also member of ACM and SIAM societies, and he is part of Technical Program committee of top conferences, including SC, ISC, and DATE. Before IBM, Cristiano graduated from the Swiss Federal Institute of Technology in Lausanne (EPFL) in Lausanne with a PhD in applied mathematics. In 2013, his thesis granted him the IBM Research Prize for Scientific Computing. Cristiano has also a B.Sc. in Aerospace Engineering and a M.Sc. in Aeronautical Engineering from the Politecnico di Milano (Italy).

Luca Benini holds the chair of digital Circuits and systems at ETHZ and is Full Professor at the Universitá di Bologna. Dr. Benini's research interests are in energy-efficient system design for embedded and high-performance computing. He is also active in the area of energy-efficient smart sensors and ultra-low power VLSI design. He was a co-recipient of the GAUSS Award at ISC 2016 for his work on energy-efficient schedulers for HPC. He has published more than 800 papers, five books and several book chapters. He is a Fellow of the IEEE and the ACM and a member of the Academia Europaea. He is the recipient of the 2016 IEEE CAS Mac Van Valkenburg award.

Norbert Wehn holds the chair for Microelectronic System Design in the department of Electrical Engineering and Information Technology at the University of Kaiserslautern. He received his Diploma and PhD from the TU Darmstadt in Germany. He is associate editor of various journals and member of several scientific industrial advisory boards. He has more than 350 publications in various fields of microelectronic system design and holds 20 patents. His special research interests are VLSI-architectures for mobile communication, forward error correction techniques, low-power techniques, advanced SoC and memory architectures, 3D integration, reliability issues in SoC, IoT and hardware accelerators for big data applications.

Roger Woods has held the chair of Digital Systems at Queen’s University of Belfast since 2003. He has an established record of research into embedded and computing systems, particularly field programmable gate arrays (FPGAs) and has published over 240 papers. He is on the advisory board to the IEEE Signal Processing Society Technical Committee on the Design and Implementation of Signal Processing Systems and a member of the UK’s research council ICT Strategic Advisory Team advising on future computing. He is a programme committee member of numerous technology conferences, e.g. FPL, FPT, SIPS and ARC. He has had a portfolio of research funding of nearly £6M over the past 5 years and recently, was successful in securing funding to establish a £2.1M Tier-2 HPC centre called Kelvin-2 at Queen’s University. He is a co-founder and Chief Scientist of Analytics Engines Ltd., a 23-person company involved in producing data analytics solutions.

Andrew Emerson graduated in Chemistry from the University of Southampton (UK) in 1987. He stayed in Southampton to study for a doctorate in computational chemistry which was awarded in 1991. After many years in research in the UK and Italy in the field of molecular dynamics, he joined in 2000 the Cineca supercomputer centre located in Bologna, Italy as an applications specialist. He currently works at Cineca in the high level support team and in a number of European projects, including PRACE, and gives courses on computational chemistry and parallel computing. In 1997 he was awarded the title “Young Scientist of the Year” by the British Liquid Crystal society. He is married with one child and lives in Bologna.

Frank K.Gürkaynak obtained his B.Sc. and M.Sc. degrees from the Istanbul Technical University, and his Ph.D. degree from the Integrated Systems Laboratory of ETH Zurich. Since 2008 he is with the Microelectronics Design Center of ETH Zurich, involved in research and teaching on the design and test of digital integrated circuits and is a member of the PULP project. He actively contribute to research in the following fields: Ultra-low-power processor design, design and test of digital integrated circuits and system design, cryptographic Hardware and Open Source Hardware.

Alberto Bosio received the PhD in Computer Engineering from the Politecnico di Torino, Italy in 2006. From 2007 to 2018 he was an Associate Professor at LIRMM - University of Montpellier in France. Hi is now a Full Professor the INL – Ecole Centrale de Lyon, France. His research interests include Approximate Computing, In-Memory Computing, Test and Diagnosis of Digital circuits and systems and Reliability. He co-authored 1 book, 3 patents 35 journals, and over 120 conference papers. He is the chair of the ETTTC. He is a member of the IEEE.

Dimitrios Nikolopoulos is the John W. Hancock Professor of Engineering, Professor in Computer Science and Professor (by courtesy) in Electrical and Computer Engineering at Virginia Tech. His current research interests are in virtualization technologies for scalable computing and memory management for large-scale heterogeneous systems. Nikolopoulos has led numerous collaborative research and technology transfer efforts in these areas. He is a recipient of major faculty investigator awards (NSF, DOE, Royal Society, SFI), industry awards (IBM), and nine Best Paper awards from ACM and the IEEE. He received BEng (1996), MSc (1997) and PhD (2000) degrees from the University of Patras.

Dr. Christos Bouganis received the M.Eng degree in Computer Engineering and Informatics from University of Patras Greece in 1998, the MSc degree in Communications and Signal Processing in 1999 and the Ph.D. degree in 2004 both from Imperial College London. He joined the Department of Electrical and Electronic Engineering as academic faculty in 2007. He is currently a Reader in Intelligent Digital Systems with the Department of Electrical and Electronic Engineering, the Director of Postgraduate Studies of the department and leads the Intelligent Digital Systems Lab (iDSL). His research inlcudes the theory and practice of reconfigurable computing and design automation, mainly targeting digital signal processing algorithms. His work is currently focused on Machine Learning, Computer Vision and Image Processing, Markov Chain Monte Carlo Systems, and computing with unreliable hardware. He currently serves on the program committees of many international conferences, including FCCM, FPL, FPT, DATE, SPPRA, and VLSI-SoC and is an editorial board member of IET Computers and Digital Techniques and Journal of Systems Architecture.

Enrique S. Quintana-Ortí received the bachelor and Ph.D. degrees in computer sciences from the Universidad Politecnica de Valencia, Spain, in 1992 and 1996, respectively. Currently, he is a Professor in Computer Architecture in the Universidad Jaume I, Castellón, Spain. He has published more than 200 papers in international conferences and journals, and has contributed to software libraries like PLiC/SLICOT, MAGMA, FLARE, BLIS and libflame for control theory and parallel linear algebra. He has also been member of the programme committe for around 100 international conferences. In 2008 Enrique received an NVIDIA professor partnership award for his contributions to the acceleration of dense linear algebra kernels on graphics processors, and he also received two awards from NASA for his contributions to fault-tolerant dense linear algebra libraries for space vehicles. Recently, he has participated/participates in EU projects on parallel programming, such as TEXT, INTERTWinE, and energy efficiency such as EXA2GREEN and OPRECOMP. His current research interests include parallel programming, linear algebra, energy consumption, transprecision computing and bioinformatics as well as advanced architectures and hardware accelerators.

Jonathan is currently a staff computer architecture researcher focusing on next generation architectures for Big Data beyond exascale. Jonathan also has served as a technical advisor to many start-up companies, and has given talks ranging from C++ parallel runtimes to debating exascale memory architectures at Supercomputing. Jonathan Beard received a BS (Biology) and BA (International Studies) in 2005 from the Louisiana State University, MS (Bioinformatics) in 2010 from The Johns Hopkins University, and a PhD in Computer Science from Washington University in St. Louis in 2015. Jonathan served as a U.S. Army Officer where he served in roles ranging from medical administrator, to Aide-de-Camp, to acting director of the medical informatics department for the U.S. Army in Europe. Jonathan's research interests also include online modeling of stream/data-flow parallel systems and extremely heterogeneous systems.

Jeffrey (Jeff) Young is a research scientist in Georgia Tech's School of Computer Science and the managing director of the Arm HPC User Group. His main research interests include investigating scheduling and data movement for accelerators like GPU and Xeon Phi and working to model and map algorithms to high-performance architectures. He is currently working on a collaborative research program that is focused on mapping bandwidth-intensive algorithms to 3D stacked memories like Hybrid Memory Cube (HMC) and High Bandwidth Memory (HBM) and on performing near-memory computation on devices like FPGAs and GPUs. He received his PhD in computer engineering in 2013 from Georgia Tech's ECE department.

Roxana Rusitoru is a Senior Research Engineer in Arm’s Research division, working in Software and Large Scale Systems. She joined Arm in 2012 after obtaining an MEng degree in Computing (Software Engineering) from Imperial College London in optimising unstructured mesh CFD applications on multicores via machine learning and code transformation. At Arm, amongst others, she has worked on Linux kernel optimizations aimed at HPC and sensitivity studies aimed to showcase Arm AArch64 microprocessor characteristics suitable for HPC. Most recently, she has been working on power-aware scheduling at OS level for heterogeneous cores and methodologies to identify representative sub-sections from multi-threaded applications. Some of her research interests are software performance optimization and next-gen heterogeneous architectures. Roxana has been a part of the Mont-Blanc 1 and 2 projects, and is now leading the Software ecosystem in Mont-Blanc 3, in addition to technical contributions.

Oscar Hernandez has a Phd in Computer Science and recently joined NVIDIA/Mellanox in 2021 after working 12 years at Oak Ridge National Laboratory (ORNL) where he was a senior staff member of the Programming Systems Group, which does research on programming models, compilers and tools that are deployed at supercomputers like Summit and Frontier at the Leadership Computing Facility (OLCF). At ORNL he helped standardize parallel languages and APIs for accelerated nodes such as OpenACC/OpenMP and communication libraries and frameworks like OpenSHMEM and UCX. He also worked for the Exascale Computing Project where he led different efforts to deploy these technologies on Exascale systems. He also worked closely with application teams including the CAAR, INCITE and ALCC projects and on many projects funded by DOE, DoD, NSF, and Industrial Partners in the Oil & Gas industry.Oscar has a lot of experience giving tutorials in different venues, like Supercomputing, ISC, ECP Annual Meeting and NSF.

Andrew Younge is a R&D Computer Scientist at Sandia National Laboratories with the Scalable System Software group. His research interests include High Performance Computing, Virtualization, Distributed Systems, and energy efficient computing. The central focal point of Andrew’s work is to improve the usability and efficiency of supercomputing system software. Andrew has a Ph.D in Computer Science from Indiana University, where he was the Persistent Systems fellow and a member of the FutureGrid project, an NSF-funded experimental cyberinfrastructure test-bed. Over the years, Andrew has held visiting positions at the MITRE Corporation, the University of Southern California / Information Sciences Institute, and the University of Maryland, College Park. He received his Bachelors and Masters of Science from the Computer Science Department at Rochester Institute of Technology (RIT) in 2008 and 2010, respectively.

RuQing (G) Xu is a 2nd year postgrad in physics now in the University of Tokyo. (https://qsl.r-xu.dns-cloud.net). I'm primarily working on computational sciences in a solid state physics context, with special focus on variational wavefunction optimization and tensor network methods. As a result, my work is very sensitive to the performance of linear algebra libraries (BLAS-level, LAPACK-level, sparse LAPACK-level, etc.). I got to know BLIS and Arm on HPC when trying to optimize our variational quantum solver on supercomputer Fugaku. Experience working with Arm processors turned out to be smooth and fruitful, with our lab program accelerated up to ~6x and BLIS on SVE almost production-ready. Apart from performance libraries, I'm a keen user of programming language Julia. Wrappers for BLIS and TBLIS are made to exploit flexibility of BLIS framework as well as Julia language itself. Improving Julia ecosystem on aarch64 is yet another thing I want to contribute to in the coming few years.

Yuetsu Kodama is a senior scientist at RIKEN CCS (Center for Computational Science) from 2015. He received the B.E., M.E. and Ph.D degree in engineering from the University of Tokyo in 1986, 1988 and 2003, respectively. He was a professor at University of Tsukuba in 2011-2015, a senior researcher at AIST (National Institute of Advanced Industrial Science and Technology) in 2000-2011 and a senior researcher at ETL (Electrotechnical Laboratory) in 1988-1999. He has been engaged in the research on parallel computer architecture. He is a member of IEEE CS, IEICE and IPSJ.

Stephen Messenger is a Senior HPC specialist Solutions Architect for AWS. He has worked with HPC and Cloud technology for the last 15 years, working on many different projects from personal clusters that fit under a desk, to some of the largest Super Computers in the world. He is still slightly amazed that anyone will pay him for tinkering with computers. When Stephen is not working he enjoys spending time mountain biking, in the New Forest or the South Downs in England.

Srinath Vadlamani, Ph.D. is an HPC Field Application Engineer with Arm. Inc. He specializes in scientific application efficacy on HPC systems with a focus on Arm enabled systems. Current interests include computation/communication overlap strategies and threading strategies. Srinath is part of the US Fortran Programming Language Standards Technical Committee.

Miwako Tsuji received master and PhD degrees from Information Science and Technology, Hokkaido University. From 2007 to 2013, she was working in University of Hokkaido, University of Tokyo, University of Tsukuba and Universite de Versailles Saint-Quentin-en-Yvelines. She is a research scientist at RIKEN Center for Computational Science. She was a member of the flagship 2020 project, which had conducted the disign and development of the supercomputer Fugaku during the full period of the project. Her current research interests are programming model and performance model of the large-scale high performance computing. She is a coauthor of the ACM Gordon Bell Prize in 2011.

After studying physics at the Bergische Universitat Wuppertal, Stepan Nassyr joined the Juelich Supercomputing Centre in July 2017 to work on his PhD dealing with future ARM-based supercomputer architectures. As part of the application oriented technology group at the Juelich Supercomputing Centre he has worked extensively with the ARM ecosystem and the ARM SVE extension, focusing mostly on hand-written assembly kernels and the requirements to the microarchitecture and memory architecture to effectively exploit the available compute capabilities in the context of HPC applications. Aside from his PhD, he is also administering a small ARM-based cluster at the JSC and has experience with a number of ARM-based HPC architectures, including Marvell ThunderX2, Huawei Kunpeng 920 and Fujitsu's A64FX.

tbd

Andrei Poenaru is a final-year PhD Student with the High Performance Computing Group at the University of Bristol. His research is centred around advanced and future architectures for HPC, and he has been involved in several studies aiming to characterise performance and evaluate portability across diverse modern architectures. His current projects are focused on vectorisation in the context of Arm SVE and upcoming Arm-based high-performance processors.

John is Arm's Director for HPC Engineering. He leads a worldwide team of HPC experts focused on making Arm a win for HPC and vice versa.

Jeff Hammond is a Principal Architect at NVIDIA, where he focuses on parallel programming models for GPUs and ARM CPUs. He has contributed to NWChem since 2006.

I am a Computational Physicists in the domain of Material Sciences, with a education in Theoretical High Energy Physics. My present research interests are related to the conception, development, and implementation of new theoretical algorithms and methods exploiting advanced computing resources, enabling large-scale computation in diverse areas in Solid-State physics, Quantum Chemistry, and Electronic Structure calculations with applications in Life-Sciences and Biology.

Miquel Moreto is a Ramon y Cajal Fellow at the Computer Architecture Departament (DAC) at the Universitat Politecnica de Catalunya-Barcelona Tech (UPC), where he teaches Computer Architecture. He is leading the High Performance Domain Specific Architectures team at the Barcelona Supercomputing Center (BSC). He received the BSc, MSc, and PhD from the UPC. His PhD thesis advisors were Mateo Valero (UPC) and Francisco J. Cazorla (BSC). During his PhD, he interned at IBM T. J. Watson Research Center for 4 months, and visited the Universities of Edinburgh and Cantabria for 3 months. After finishing the PhD, he spent 15 months at the International Computer Science Institute (ICSI), affiliated with UC Berkeley, as a Fulbright Postdoctoral Research Fellowship Holder during 2011 and 2012. Finally, he spent 2 months in Arm Research (Cambridge, UK) as a Visiting Professor in 2017.

Hatem Ltaief is a principal research scientist with the Extreme Computing Research Center, King Abdullah University of Science and Technology, Saudi Arabia. His research interests include parallel numerical algorithms, parallel programming models, and performance optimizations for multicore architectures and hardware accelerators.

"Bine Brank is a PhD student at Juelich Supercomputing Centre. After obtaining his Master's degree in Computer Simulation from the University of Wuppertal, he has joined the application-oriented technology development team at JSC. There, he is working in the context of Mont-Blanc 2020 and the European Processor Initiative project. The main topic of his dissertation is SIMD parallelisation with a focus on Arm's SVE. This includes porting of applications to Arm architectures as well as evaluation of compiler's auto-vectorisation capabilities. "

Eva Siegmann has a PhD in applied mathematics. She has extensive experience in the field of high-performance computing with special focus on simulations in the field of pharmaceutical engineering. Beginning of this year Eva joined the Stony Brook University where she is the lead research scientist in the Ookami project. Ookami is testbed which provides researchers with state-of-the-art hardware, including Fujitsu A64FX processors.

Sarat Sreepathi is a Computer Scientist interested in interdisciplinary research at the intersection of High Performance Computing and domain sciences. He is a member of the Computational Earth Sciences Group in the Computational Sciences and Engineering Division at Oak Ridge National Laboratory. He received his Ph.D. in Computer Science from North Carolina State University. He is the Chair of the OLCF User Group Executive Board and serves on the NERSC User Group Executive Committee. He co-leads the Performance group for the Energy Exascale Earth System Model. He is also a member of Exascale Computing Project (ECP) application teams (Climate: E3SM-MMF and Nuclear Fusion: XGC) .

Thomas Chen is a researcher scientist whose primary interests lie in machine learning and high-performance computing. He serves on the U.S. Technology Policy Committee of the Association for Computing Machinery. As much of his work lies at the nexus of artificial intelligence and earth science, he is also an active early-career scientist member of the European Geosciences Union and the American Geophysical Union. He particularly enjoys using Python to conduct research that has real-world impacts. Previously, Thomas has presented work at a number of conferences, workshops, and meetings, from NeurIPS workshops, to Applied Machine Learning Days, to the Open Data Science Conference, to Machine Learning Week Europe.

Craig Prunty, SiPearl VP Marketing & Business Development, joined SiPearl in May 2020. Prior to SiPearl, Craig was Marketing Director for Marvell Semiconductor’s Server Processor Business Unit in Santa Clara, California. His 20+ years in the Semiconductor industry include sales, marketing, and technical roles with Cavium, AppliedMicro (AMCC), Lockheed-Martin, and Unisys. Craig holds a B.S. in Mathematics from Lewis & Clark College in Portland, Oregon, and an MS in Electrical Engineering from San Diego State University.

Dr. Julien Bigot is a CEA Researcher at Maison de la Simulation. His main research interest is related to programming models and software engineering issues for HPC applications. During his Ph.D. Thesis (2007-2010) at IRISA Rennes and ENS Lyon, he proposed a HPC-dedicated software component model based on assembly compilation for hardware adaptation. He applied this approach to real life applications such as a MapReduce skeleton, a parallel FFT code and the extreme-scale plasma simulation code Gysela5D. Since 2014, he holds a permanent CEA researcher position at Maison de la Simulation. There, he conducts research on the separation of concern between optimization and algorithm in HPC codes. He also leads the development of the PDI library used for code modularization to support separation of concern between IO optimization and the main code as well as integration of codes in complex workflows.

Bruno Raffin is Research Director at Inria and leader of the DataMove team. He led the development of the FlowVR/Melissa middleware for large-scale data-flow oriented parallel applications, used for scientific visualization, computational steering, in situ analytics for large-scale parallel applications. He also worked on parallel algorithms and cache-efficient parallel data structures (cache oblivious mesh layouts, parallel adaptive sorting), strategies for task-based programming of multi-CPU and multi-GPU machines. Bruno Raffin accounts for more than 60 international publications, advice 16 PhD students. Bruno Raffin has been involved in more than 30 program committees of international conferences. He was responsible for INRIA of more than 15 national and European grants and was the co-founder of the Icatis start-up company (2004-2008). He leads the INRIA Integrated Project Lab focused on the convergence between HPC, AI and Big Data (2018-2021).

Dr. Leonardo Bautista Gomez is a Senior Research Scientist at the Barcelona Supercomputing Center where he work on resilience and scalability for high-performance computing and machine learning. He was awarded the 2016 IEEE TCSC Award for Excellence in Scalable Computing (Early Career Researcher). Before moving to BSC he was a Postdoctoral researcher for 3 years at the Argonne National Laboratory, where he investigated data corruption detection techniques and error propagation. Prior to that, he did his PhD. in resilience for supercomputers at the Tokyo Institute of Technology. He developed a scalable multilevel checkpointing library called Fault Tolerance Interface (FTI) to guarantee application resilience at extreme scale. For this work, he was awarded the 2011 ACM/IEEE George Michael Memorial High-Performance Computing Ph.D. Fellow at Supercomputing Conference 2011 (SC11), Honorable Mention. Before moving to Tokyo Tech, he graduated in Master for Distributed Systems from the Paris 6 University.

Wouter Klijn completed a MSc in Artificial Intelligence from the University of Groningen in the Netherlands. His Master thesis was on the information content of cell species in a 3 layer model of a cortical micro-column. He currently is a software architect in the Simlab Neuroscience at the Forschungzentrum Jülich with a focus on in Artificial Intelligence, information theory of neural networks, big data real-time streaming systems and development of complex HPC processing pipelines. He is responsible for science and use case management in the Human Brain Project, an EU Flagship Project and ICEI, the Interactive Computing E-Infrastructure for the Human Brain Project. He is currently creating the science and software infrastructure architecture for the HBP. He also works with advanced HPC oriented AI solutions and multiple neural simulators. His modelling work is focused on self-organizing dynamics of extremely large neural networks with a 2d spatial structure.

Charles Gueunet joined Kitware in February 2016. For the first three years, he worked on his PhD on the topic of “High Performance Level-set based Topological Data Analysis”, and became one of the main contributors of the Topology ToolKit (TTK). After defending in February 2019, Charles joined the Scientific Visualization team at Kitware. He now works on various projects involving parallel programming, discrete geometry and data analysis algorithms.

Sai Narasimhamurthy PhD is currently Managing Principal Engineer, Seagate (formerly Lead Researcher, Emerging Tech, Xyratex) working on Research and Development for next generation storage systems and responsible for EU R&D for the Seagate Systems business. Sai currently also holds the position of vice-chair of industry for the ETP4HPC organisation and leads the storage and I/O working group for developing ETP4HPC’s Strategic Research Agenda (SRA). He has also actively led and contributed to many European led HPC and Cloud research initiatives currently coordinating and providing technical leadership for SAGE and Sage2 consortia. Previously, Sai was CTO and Co-founder at 4Blox, inc, a venture capital backed storage infrastructure software company in California addressing IP SAN(Storage Area Network) performance issues

Dr Achim Basermann is head of the department “High-Performance Computing” at German Aerospace Center’s (DLR) Simulation and Software Technology institute and German Research Foundation (DFG) review board member in computer science, topic “Massively Parallel and Data Intensive Systems”. In 2019, he became chairman of the strategy commission for national high-performance computing (NHR) in Germany. He coordinated the application workpackage in the European Grid computing project NextGRID (2004-2007), the pre- and postprocessing activities in the European Exascale computing project CRESTA (2011-2014) and the algorithmic research in the Exascale computing projects ESSEX I and II (2013-2018) of DFG. In 1995, he obtained his Ph.D. in Electrical Engineering from RWTH Aachen followed by a postdoctoral position in Computer Science at Research Centre Jülich GmbH, Central Institute for Applied Mathematics. From 1997 to 2009 he led a team of HPC application experts at the C&C Research Laboratories, NEC Europe Ltd., in Sankt Augustin, Germany and contributed to the Japanese Earth Simulator project. Current research is focussed on massively parallel linear algebra algorithms, partitioning methods, optimization tools in the area of computational fluid dynamics for many-core architectures and GPGPU clusters, high-performance data analytics and quantum computing.

Matthieu Dorier graduated with a PhD from Ecole Normale Supérieure de Rennes, France, In 2014, and followed with a two-year postdoc at Argonne National Laboratory. Since 2017, Matthieu is a software development specialist at Argonne. His work revolves around data management for HPC, including parallel and distributed storage, data services, workflows, in situ analysis and visualization.

Amal Gueroudji is a PhD student at Maison de la simulation. Holder of a research Master and an Engineering degree in Computer Systems (2014-2019) from the Higher National School of computer science (ESI ex INI Alger). During her Masters(2019), she worked on the Tiramisu polyhedral compiler with the Commit team at MIT-CSAIL laboratory. She mainly worked on CPU/GPU communication optimization and code generation automation. Since April 2020, Amal is a PhD student working on code coupling of high performance simulation to task-based in situ analytics, namely MPI codes with DASK.

Dr Tiago Quintino is a Senior Analyst and Team Leader for Development of Production Services at ECMWF. He and his team develop high-throughput specialist software that supports ECMWF’s operational meteorological forecast model, systems for acquisition of incoming observations, management of direct model output, perpetual archival of weather observations and forecast data, and post-processing, generation and dissemination of meteorological products. His team also develops cloud meteorological and climate data provisioning services (Data-as-a-Service) in support of ECMWF’s cloud activities. Dr Quintino’s career spans 20 years researching numerical algorithms and developing high performance scientific software in the areas of Aerospace and Numerical Weather Prediction. Lately, his research focuses on scalable data handling algorithms for generation of meteorological forecast products, optimising their workloads and I/O of massive data-sets.

Prof. Dr. Dirk Pleiter is professor for HPC at KTH, director of the PDC Center for High Performance Computing and senior researcher at Forschungszentrum Jülich. He is the principal investigator of various European research and innovation projects including Maestro. Furthermore, he acts as technical coordinator of the ICEI project, which as part of the Human Brain Project works on providing a productively used federated European HPC, cloud and storage infrastructure. In the past he played a leading role in several projects for developing massively-parallel special purpose computers, including QPACE, and recently worked on Arm-based processor architectures.

Dr. Alejandro Ribés graduated in computer science (bachelor’s and master’s) from the Universitat Jaume I, Castelló (ES). He later graduated, from Université de Nice Sophia-Antipolis (FR), in a master in image processing and computer vision. Alejandro Ribés also holds a Ph.D. in multispectral imaging applied to fine art paintings, from the Ecole Nationale Supérieure des Télécommunications (FR). He later was a postdoctoral fellow at the CEA laboratory in Orsay (FR), working on parallel MRI reconstruction. During this postdoc he was appointed as a lecturer at the Computer Science Department of Ecole Polytechnique, Palaiseau, France, where he taught for two years. Alejandro also worked in MRI technology, during more than two years, as a visiting scholar at the National Yang-Ming University, Taipei, Taiwan. In 2009, Alejandro Ribés became a Research Scientist at the R&D department of EDF. In December 2016, he became Principal Research Scientist. He recently introduced AI based methods on the context of advanced numerical simulation, especially deep neural networks trained using GPU clusters. From 2013, Alejandro Ribés also collaborates with Sorbonne Université (FR).

Dr. Virginie Grandgirard received the PhD degree in mathematics and applications from Besancon University, France, in 1999. She then obtained the Habilitation à Diriger des Recherches in 2016. She is presently researcher with CEA, France. She is one of the main developer of the 5D non-linear gyrokinetic semi-Lagrangian code GYSELA used for plasma turbulence simulations. This code is highly parallelized up to hundreds of thousands cores. Her research interests focus on numerical methods for Vlasov equations, high performance computing and tokamak plasma turbulence. She has co-authored 50 publications in peer-reviewed journals.

Yuuichi ASAHI received the PhD degree from Tokyo Tech, in 2015. He is a researcher in Japan atomic energy agency (JAEA), Japan. He has focused on the nonlinear plasma turbulence by means of gyrokinetic simulations. High performance computing and large scale data management are key ingredients for these simulations. His current interests include accelerating the gyrokinetic simulation codes for more complicated physics, and analysing the large scale simulation results with machine learning methods.

Johannes Doerfert is a researcher in the Argonne Leadership Computing Facility at the Argonne National Laboratory. He develops LLVM and Clang enhancements that enable compiler optimization for parallel programs. Johannes is also part of several ongoing efforts to make compiler software ready for exascale computing. He is an active member of the OpenMP Language Committee and already organized various LLVM related workshops and conferences, including the LLVM Performance Workshops @ CGO, and the EuroLLVM in 2017. Johannes received his Ph.D. in Computer Science from Saarland University in 2018.

Anja works at the Center for Information Services and High Performance Computing at TU Dresden. A considerable part of her job role is to develop a range of courses and resources to enable users to work with the cluster. In addition, she is doing a PhD at the German Climate Research Center in Hamburg as an external member. The main topic is Compiler Optimization in High-Performance Computing with an aim to improve weather forecasting and climate modeling. The goal of her PhD is to study the compiler for deficits in terms of performance when translating HPC applications and to understand the limitations of compilers in making the necessary optimizations. These insights can then be incorporated into the compiler for future automatic compiler optimization. Automatic program transformation using source-to-source instrumentation of parallel programs will prepare HPC applications for future performance analysis.

Sameer Shende serves as the Director of the Performance Research Laboratory at the University of Oregon and the President and Director of ParaTools, Inc. He serves as the lead developer of the TAU Performance System, Program Database Toolkit (PDT), HPCLinux, and Extreme-Scale Scientific Software Stack (E4S.io). His research interests include performance instrumentation, compiler optimizations, measurement, and analysis tools for HPC. He leads the SDK project for the Exascale Computing Project (ECP), in the Programming Models and Runtime (PMR) area at the University of Oregon to provide ECP Software Technology (ST) products in a container environment for HPC. He has served as the chair of the Performance Measurement, Modeling, and Tools track at SC17 and the co-chair for the technical program at the ICPP 2018 conferences.

Jeremy Bennett founded in 2008 Embecosm. He is an expert on hardware modeling and embedded software development. Previously Dr Bennett was Vice President of ARC International plc, following their acquisition of Tenison Design where he had been CEO and CTO. Dr Bennett is author of the popular textbook, “Introduction to Compiling Techniques” (McGraw-Hill 1990, 1995, 2003) and holds an MA and PhD in Computer Science from Cambridge University.

Shintaro Iwasaki is a Named Fellow at Argonne National Laboratory. He received his Ph.D. degree from the University of Tokyo in 2020. His research interests include parallel programming languages, compiler optimizations, parallel runtime systems, and scheduling techniques. He is leading the development of a lightweight user-level threading library called Argobots and an OpenMP runtime library over Argobots, BOLT. He is also working on MPI + lightweight threads (such as Argobots + MPICH or Open MPI). For details, see https://www.mcs.anl.gov/~iwasaki/

Ernesto Su is a Senior Staff Engineer and a project lead for the Parallel Optimization team of the Intel Compilers, with a focus on OpenMP parallelization and offloading. He holds a BS degree from Columbia University and MS & Ph.D. degrees from UIUC.

Xinmin Tian is a Senior Principal Engineer and a compiler architect at Intel Corporation. He is serving as Intel representative at OpenMP ARB and driving DPC++ optimizations, OpenMP vectorization, parallelization and offloading technologies for current and future Intel architectures.

Valentin Clement is a Software Engineer in the Programming Systems Group at Oak Ridge National Laboratory. His research currently focuses on LLVM-base compiler projects. He is mainly contributing to Flang and OpenACC support for LLVM.

Arnamoy received his PhD from University of Toronto and currently working in the Heterogeneous compiler lab in Huawei, Canada as a research engineer. He is broadly interested in the area of performance enhancement through compiler optimization, cloud computing and machine learning guided optimizations. He has been actively contributing in the LLVM Flang project (especially for the driver and semantic analysis for OpenMP).

Saiyed is a Senior SDE in AMD’s GPU Compiler organization based out of Bangalore, India. There, he is part of AOMP team lead by Greg Rodgers where he focuses mainly on OpenMP frontend development and upstreaming. He obtained PhD from BITS Pilani India, where he designed a Domain Specific Language for Clustering and its Parallelizing Compiler. In this DSL, data scientists write sequential code and the compiler generates corresponding distributed memory parallel MPI C++ code. He also proposed a Virtual Machine for this compiler to abstract multiple target parallel architectures. He has published at multiple International Journals and Conferences and love teaching parallel programming.

Dr. Tobias Grosser is a Reader in Compilers and Runtime Systems at Edinburgh. He is known for his research on optimizing compilers and his contributions to open-source software. As author and development lead of the LLVM polyhedral loop optimizer Polly [27], Tobias Grosser made advanced polyhedral loop optimizations available in production-grade compilers. To coordinate the industry interest in polyhedral compilation, Tobias Grosser co-founded the Polly Labs research organization and currently works with Arjun Pitchanathan on integrating a state-of-the-art polyhedral library into LLVM/MLIR. Tobias also collaborates closely with the LLVM community on advancing the new MLIR software stack and he introduced with LLHD [39], an open-source compilation stack for hardware design that brings the innovation speed of software compilers to the hardware design world. Tobias Grosser has received a Google Ph.D. Fellowship and a Swiss National Science Foundation Career Award.

Jeff Sandoval is a senior compiler tech lead at HPE in Bloomington, Minnesota. He specializes on compiler and runtime library implementation for both the OpenMP and OpenACC programming models, targeting a variety of CPU and GPU processors. Jeff holds a PhD in computer science from Rice University and a BS in computer science from Michigan Technological University.

Christian is a Specialist Solutions Architect with AWS. With a 10 year journey rooted in the HPC parts of the german automotive industry, Christian Kniep started to support CAE applications and VR installations. When told at a conference that HPC can not learn anything from the emerging Cloud and BigData companies, he became curious and was leading the containerization effort of the cloud-stack at Playstation Now followed by working at Docker Inc as a Technical Account Manager to help push the adoption forward and be part of the innovation instead of an external bystander. At AWS he is helping customers to adopt the cloud efficiently.

Shane Canon joined NERSC in 2000 to serve as a system administrator for the PDSF cluster. While working with PDSF he gained experience in cluster administration, batch systems, parallel file systems and the Linux kernel. In 2005, Shane left LBNL to take a position as Group Leader at Oak Ridge National Laboratory. One of the more significant accomplishments while at ORNL was architecting the 10 petabyte Spider File System. In 2008, Shane returned to NERSC to lead the Data Systems Group. More recently Shane has focused on enabling data intensive applications on HPC platforms and engaging with bioinformatics applications. Shane joined the Data & Analytics Services group in 2016 to focus on these topics. Shane is involved in a number of projects outside of NERSC. He is the Production Lead on the KBase project which is developing a platform to enable predictive biology. Shane has a Ph.D in Physics from Duke University and B.S. in Physics from Auburn University.

Andrew J. Younge is a Senior Member of Technical Staff in the Scalable System Software department at Sandia National Laboratories. He currently serves as the Lead PI for the Supercontainers project under the DOE Exascale Computing Project and is a key contributor to the Astra system, the world's first supercomputer based on the Arm processor deployed under Sandia's Vanguard program. Prior to joining Sandia, Andrew held visiting positions at the MITRE Corporation, the University of Southern California's Information Sciences Institute, and the University of Maryland, College Park. He received his PhD in computer science from Indiana University in 2016. His research interests include high performance computing, virtualization, distributed systems, and energy efficient computing. The focus of his research is on improving the usability and efficiency of system software for supercomputing systems.

Eduardo is a performance engineer at Red Hat, working on the OpenShift performance & latency sensitive applications. Eduardo is also a Computer Science PhD student at Universidad del Valle, Cali, Colombia, working on containerized distributed systems for research computing, with high focus on automated workflows and DevOps. His research interests include High Performance Computing, Distributed systems, Dependency management, Linux containers and most recently, Container orchestration. Over the past 5 years Eduardo has focused on enabling researchers to build and deploy performance sensitive applications with containers on distributed environments.

Abdulrahman Azab works at the Department of Research Computing, University of Oslo, Norway. In addition he is a senior lecturer at the Department of Computer Engineering and Control Systems, Mansoura University, Egypt. He is leading the Containers-for-HPC service at PRACE (Partnership for Advanced Computing in Europe). Abdulrahman is also the Norwegian sub-project manager at NeIC/Tryggve (Collaboration on Sensitive Data in the Nordics). Abdulrahman is leading the sensitive data working group in both EOSC-hub and EOSC-Nordic (EOSC: European Open Science Cloud). His research interests are: High Performance Computing, High Throughput Computing, High Availability Computing, Linux Containers, Cloud Computing, Cyber Security, Control systems, and Bioinformatics.

He has experience working with High-Performance Computing Systems at International Centre for Integrated Mountain Development where is involvement was with Atmosphere Initiative and SERVIR-NASA Projects. Mr Upadhyaya also collects experience working with International Seabed Authority, UNDP and Election Commission of Nepal. Mr Upadhyaya is a recipient of a full grant to attend International Super Computing Conference 2017, Germany and a first recipient of Inclusivity Grant to attend Super Computing Conference 2017, USA.

Michael Kuhn is a junior professor for Parallel Computing and I/O at Otto von Guericke University Magdeburg. He conducts research in the area of high performance I/O with a special focus on I/O interfaces and data reduction techniques. Other interests of his include file systems and high performance computing in general. Michael is the principal investigator of the CoSEMoS project funded by the German Research Foundation (DFG). Moreover, he is the lead developer of the JULEA storage framework and received a 2019 R&D 100 award for his contributions to the Spack package manager. He regularly offers lectures and courses related to HPC and parallel I/O.

I studied physics at the University of Göttingen. For my PhD I focused on numerical simulations of Earth's magnetic field, which brought me in contact with high performance and parallel computing. After a stay at the MPI for Solar System Research I moved to computational biophysics. Since 2004 I am working at the Max Planck Institute for Biophysical Chemistry in the lab of Helmut Grubmüller. I am interested in method development, high performance computing, and atomistic biomolecular simulations.