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000916372 0247_ $$2doi$$a10.5281/ZENODO.6603470
000916372 037__ $$aFZJ-2022-06173
000916372 041__ $$aEnglish
000916372 1001_ $$00000-0002-5699-1793$$aGarcia de Gonzalo, Simon$$b0
000916372 1112_ $$aISC High Performance 2022$$cHamburg$$d2022-05-29 - 2022-05-29$$gISC22$$wGermany
000916372 245__ $$aEfficient Distributed GPU Programming for Exascale
000916372 260__ $$c2022
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000916372 520__ $$aOver the past years, GPUs became ubiquitous in HPC installations around the world. Today, they provide the majority of performance of some of the largest supercomputers (e.g. Summit, Sierra, JUWELS Booster). This trend continues in the pre-exascale and exascale systems (LUMI, Leonardo; Perlmutter, Frontier): GPUs are chosen as the core computing devices to enter this next era of HPC. To take advantage of future GPU-accelerated systems with tens of thousands of devices, application developers need to have the propers skills and tools to understand, manage, and optimize distributed GPU applications. In this tutorial, participants will learn techniques to efficiently program large-scale multi-GPU systems. While programming multiple GPUs with MPI is explained in detail, advanced tuning techniques and complementary programming models like NCCL and NVSHMEM are presented as well. Tools for analysis are shown and used to motivate and implement performance optimizations. The tutorial is a combination of lectures and hands-on exercises, using Europe's fastest supercomputer, JUWELS Booster with NVIDIA GPUs, for interactive learning and discovery.
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000916372 536__ $$0G:(DE-HGF)POF4-5111$$a5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511)$$cPOF4-511$$fPOF IV$$x2
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000916372 7001_ $$0P:(DE-Juel1)188270$$aOden, Lena$$b1$$ufzj
000916372 7001_ $$0P:(DE-Juel1)145478$$aHerten, Andreas$$b2$$eCorresponding author
000916372 7001_ $$0P:(DE-Juel1)180799$$aHrywniak, Markus$$b3
000916372 7001_ $$0P:(DE-Juel1)137023$$aKraus, Jiri$$b4
000916372 773__ $$a10.5281/ZENODO.6603470
000916372 8564_ $$uhttps://github.com/FZJ-JSC/tutorial-multi-gpu/tree/v2.0-isc22
000916372 909CO $$ooai:juser.fz-juelich.de:916372$$pVDB
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000916372 9131_ $$0G:(DE-HGF)POF4-511$$1G:(DE-HGF)POF4-510$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5112$$aDE-HGF$$bKey Technologies$$lEngineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action$$vEnabling Computational- & Data-Intensive Science and Engineering$$x1
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000916372 9141_ $$y2022
000916372 9201_ $$0I:(DE-Juel1)JSC-20090406$$kJSC$$lJülich Supercomputing Center$$x0
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