Presentation
OpenMP Common Core: Learning Parallelization of Real Applications from the Ground-Up
Event Type
Tutorial
Parallel Applications
Programming Models & Languages
Scientific Software Development
TimeSunday, June 16th9am - 1pm
LocationAnalog 1
DescriptionAs HPC continues to move towards a model of multicore and accelerator programming, a detailed understanding of shared-memory models and how best to use accelerators has never been more important. OpenMP is the de facto standard for writing multithreaded code to take advantage of shared memory platforms, but to make optimal use of it can be incredibly complex.
With a specification running to over 500 pages, OpenMP has grown into an intimidating API viewed by many as for “experts only”. This tutorial will focus on the 16 most widely used constructs that make up the ‘OpenMP common core’. We will present a unique, productivity-oriented approach by introducing its usage based on common motifs in scientific code, and how each one will be parallelized. This will enable attendees to focus on the parallelization of components and how components combine in real applications.
Attendees will use active learning through a carefully selected set of exercises, building knowledge on parallelization of key motifs (e.g. matrix multiplication, map reduce) that are valid across multiple scientific codes in everything from CFD to Molecular Simulation.
Attendees will need to bring their own laptop with an OpenMP compiler installed (more information at www.openmp.org).
With a specification running to over 500 pages, OpenMP has grown into an intimidating API viewed by many as for “experts only”. This tutorial will focus on the 16 most widely used constructs that make up the ‘OpenMP common core’. We will present a unique, productivity-oriented approach by introducing its usage based on common motifs in scientific code, and how each one will be parallelized. This will enable attendees to focus on the parallelization of components and how components combine in real applications.
Attendees will use active learning through a carefully selected set of exercises, building knowledge on parallelization of key motifs (e.g. matrix multiplication, map reduce) that are valid across multiple scientific codes in everything from CFD to Molecular Simulation.
Attendees will need to bring their own laptop with an OpenMP compiler installed (more information at www.openmp.org).
Content Level 50% beginner, 35% intermediate, 15% advanced.
Target AudienceHPC programmers with little/no formal software development training. Knowledge of sequential programming in C or Fortran is necessary. As C examples will be used, some knowledge of C programming is beneficial but not necessary. We also welcome HPC educators to attend and try out this new approach to HPC training.
PrerequisitesPlease bring a laptop that has an OpenMP compliant compiler installed.
Necessary: familiarity with sequential programming in C or Fortran. Attendees will be presented with C example codes.
Optional: An OpenACC compliant compiler to test conversion from OpenACC to OpenMP.
Authors
Professor of Applied Mathematics and Statistics, and of Computer Science
