HPC USER FORUM ISV PANEL April 2010 Dearborn, MI

Transcript:HPC USER FORUM ISV PANEL April 2010 Dearborn, MI:
HPC USER FORUM ISV PANEL April 2010 Dearborn, MI Panel Members Moderators Alex Akkerman, Ford Motor Company Sharan Kalwani, KAUST Participants Steve Feldman, CD-adapco Matt Dunbar, Simulia Uwe Schramm, Altair Engineering Li Zhang, Livermore Software Technology Corporation Barbara Hutchings, ANSYS, Inc. Martin McNamee, MSC Software Panel Format 4 Questions Provided ahead of time 2 minutes per question for each participant Follow-up and Audience after each participant had a chance to comment Q1. Applications Scalability….. Please share with the audience, briefly – the issues surrounding Applications Scalability and how is this being addressed? Our solvers scale reasonably well to 512 cores or more with very large problems. Very few actually use this many on one analysis today Primary solver bottlenecks- Memory bandwidth Unbalanced work loads Untapped speed potentials Parallel Meshing Parallel post-processing Parallel I/O Different algorithms, re-evaluation of methods Q1. Applications Scalability….. Fundamental limitations on scalability remain scalar sections of code (Amdahl’s law) and load balance Solution is still developer time and effort which is being invested Looking at ways to improve developer efficiency through use of better programming models (primarily from Intel and Microsoft) Past programming model changes were either too limited (OpenMP), too immature, or simply ineffective Newer models driven by need to bring multi-core execution to commodity applications have more promise Q1. Applications Scalability….. We’re talking finite element solver applications Two classes of solvers Interative schemes Matrix inversion schemes Issues: Scalability, Quality, Repeatability, Data transfer, Hardware configurations, Hardware access Addressed: Optimal domain decomposition, Computational methods that scale well, Solver architecture, Focus on certain hardware, Partnerships Q1. Applications Scalability….. Consistency Data summation order for different MPI causes errors – LS-DYNA uses fixed order. Modified/refined model decomposes in different way changing results – ‘Cut lines’ are preserved from 1st run. Scalability Scaling for 128 processors not always good. Hybrid LS-DYNA runs SMP within processor and MPP between processors. Results consistent with increased # SMP threads. Simple command line to execute. Q1. Applications Scalability….. Q1. Applications Scalability….. Solver scaling continues to expand CFD to 1000, Structures to 100 Especially key to accelerating transients Need to address the scalar bottlenecks Across full simulation process (meshing, I/O, certain solver physics, visualization) Hybrid parallel algorithms for multi-core/mixed-core Distributed/shared memory, OpenMP vs. MPI Support for latest communication technologies QDR IB, iWARP for 10gigE, etc. Q1. Applications Scalability….. Hybrid parallel model Shared memory parallel within a compute node (multi and many cores) Distributed memory parallel across