Reinventing HPC

Deep Learning Day at ISC 2017

ISC 2017 is excited to bring users, as well as academic and industry leaders, to spend a full day together on Wednesday, June 21, to discuss the recent advances in artificial intelligence based on deep learning technology.

The overwhelming success of deep learning has triggered a race to build larger artificial neural networks, using growing amounts of training data in order to allow computers to take on more complex tasks. Such work will challenge the computational feasibility of deep learning of this magnitude, requiring massive data throughput and compute power. Hence, implementing deep learning at scale has become an emerging topic for the high performance computing community. 

Two keynotes, along with a series of talks, will give attendees up-to-date insights on the rapid development in deep learning and also demonstrate how this technology can be enabled with HPC. Also discussed will be how the computational demands of deep learning will affect current and future HPC infrastructure.    

The principal topic areas include: 

  1. How deep learning is changing the HPC landscape
  2. HPC and big data for autonomous driving and connected vehicles
  3. Future challenges for deep learning and HPC


Chairs - Dr.-Ing. Janis Keuper & Dr. Damian Borth

  • “Janis
  • “Damian


We have lined up a range of speakers from industry, academia, and the vendor community to share their expertise in this area. The current list includes:

Janis Keuper, ITWM (Program Co-Chair)
Damian Borth, German Research Center for Artificial Intelligence (Program Co-Chair)
Zeynep Akata, Amsterdam Machine Learning Lab, University of Amsterdam (Keynoter)
Brian van Essen, LLNL
Costas Bekas, IBM Research Zurich
René Wies, BMW Group
Kai Demtröder, BMW Group
Marco Pennachiotti, BMW Group
Mario Tokarz, BMW Group
Naveen Rao, Intel Data Center Group
Achim Noller, Bosch
Gunter Röth, NVIDIA
Mayank Daga, Advanced Micro Devices

Check out the full program here.


The Student Cluster Competition and Deep Learning

On the same day, student teams participating in the student cluster competition (SCC), will compete on an image-recognition task using TensorFlow, a popular open source library used for machine learning. The specific details of the task will be published online soon.

Attendees are encouraged to visit the SCC during session breaks to witness the graduate, undergraduate and even some high-school students grapple with real world machine learning problems.

The SCC is organized by ISC High Performance and the HPC Advisory Council.