Designing High-Performance Scalable Middleware for HPC, AI, and Data Science in Exascale Systems and Clouds

Designing High-Performance Scalable Middleware for HPC, AI, and Data Science in Exascale Systems and Clouds

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Intro

1 of 29

1 of 29

Intro

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Designing High-Performance Scalable Middleware for HPC, AI, and Data Science in Exascale Systems and Clouds

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  1. 1 Intro
  2. 2 Supporting Programming Models for Multi-Petaflop and Exaflop Systems: Challenges
  3. 3 Designing (MPX) Programming Models at Exascale
  4. 4 Overview of the MVAPICH2 Project
  5. 5 MVAPICH2 Release Timeline and Downloads
  6. 6 Architecture of MVAPICH2 Software Family for HPC, DL/ML, and Data Science
  7. 7 Highlights of MVAPICH2 2.3.6-GA Release
  8. 8 Startup Performance on TACC Frontera
  9. 9 Performance of Collectives with SHARP on TACC Frontera
  10. 10 Performance Engineering Applications using MVAPICH2 and TAU
  11. 11 Overview of Some of the MVAPICH2-X Features
  12. 12 Impact of DC Transport Protocol on Neuron
  13. 13 Cooperative Rendezvous Protocols
  14. 14 Benefits of the New Asynchronous Progress Design: Broadwell + InfiniBand
  15. 15 Shared Address Space (XPMEM)-based Collectives Design
  16. 16 MVAPICH2-GDR 2.3.6
  17. 17 Highlights of some MVAPICH2-GDR Features for HPC, DL, ML and Data Science
  18. 18 MVAPICH2-GDR with CUDA-aware MPI Support
  19. 19 Performance with On-the-fly Compression Support in MVAPICH2-GDR
  20. 20 Collectives Performance on DGX2-A100 - Small Message
  21. 21 MVAPICH2 (MPI)-driven Infrastructure for ML/DL Training
  22. 22 Distributed TensorFlow on ORNL Summit 1,536 GPUS
  23. 23 Distributed TensorFlow on TACC Frontera (2048 CPU nodes)
  24. 24 PyTorch, Horovod and DeepSpeed at Scale: Training ResNet-50 on 256 V100 GPUs
  25. 25 Dask Architecture
  26. 26 Benchmark #1: Sum of cupy Array and its Transpose (12)
  27. 27 Benchmark #2: cuDF Merge (TACC Frontera GPU Subsystem)
  28. 28 MVAPICH2-GDR Upcoming Features for HPC and DL
  29. 29 Funding Acknowledgments

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