Lecture (Other)

FZJ-2024-07562

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png GPU Programming Part 2: Advanced GPU Programming

Meinke, J. (Corresponding author)FZJ* ; Herten, A. (Corresponding author)FZJ* ; Hrywniak, M.FZJ* ; Kraus, J.FZJ* ; Badwaik, J.FZJ* ; Haghighi Mood, K.FZJ*

2024

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Please use a persistent id in citations: doi:10.34734/FZJ-2024-07562

Abstract: GPU-accelerated computing drives current scientific research. Writing fast numeric algorithms for GPUs offers high application performance by offloading compute-intensive portions of the code to a GPU.This advanced course consists of modules providing more in-depth coverage of multi-GPU programming, modern CUDA concepts, CUDA Fortran, and portable programming models such as OpenACC and C++ parallel STL algorithms.Topics covered will includeA) Advanced Multi-GPU Programming with MPIB) Advanced Multi-GPU Programming with NCCL and NVSHMEMC) Advanced and Modern CUDA Concepts (Cooperative Groups, CUDA Graphs, CUB Primitives, Modern C++ Programming)D) CUDA FortranE) GPU Programming with Abstractions (OpenACC, Standard Language Programming (pSTL))

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Contributing Institute(s):

1. Jülich Supercomputing Center (JSC)

Research Program(s):

1. 5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511) (POF4-511)
2. 5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs) and Research Groups (POF4-511) (POF4-511)
3. 5122 - Future Computing & Big Data Systems (POF4-512) (POF4-512)
4. ATML-X-DEV - ATML Accelerating Devices (ATML-X-DEV) (ATML-X-DEV)

Appears in the scientific report 2024

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Database coverage:

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