001     916420
005     20250822121410.0
037 _ _ |a FZJ-2022-06220
041 _ _ |a English
100 1 _ |a Herten, Andreas
|0 P:(DE-Juel1)145478
|b 0
|e Corresponding author
|u fzj
111 2 _ |a JUWELS Booster Tuning and Scaling Workshop 2022
|c online
|d 2022-03-07 - 2022-03-11
|w Germany
245 _ _ |a JUWELS Booster Tuning and Scaling Workshop 2022
260 _ _ |c 2022
336 7 _ |a CONFERENCE
|2 BibTeX
336 7 _ |a conferenceObject
|2 DRIVER
336 7 _ |a Event
|2 DataCite
336 7 _ |a Conference / Event
|b event
|m event
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|s 1671692845_17992
|2 PUB:(DE-HGF)
336 7 _ |a OTHER
|2 ORCID
336 7 _ |a Generic
|0 31
|2 EndNote
500 _ _ |a Indico: https://indico-jsc.fz-juelich.de/event/266/other-view?view=standard
520 _ _ |a The Booster module of the JUWELS supercomputer at JSC consists of 936 compute nodes, each equipped with 4 NVIDIA A100 GPUs and providing a peak performance of over 70 PFLOP/s. Per node, 4 InfiniBand HDR200 adapters are installed, providing 800 GBit/s of network bandwidth per node. The system is in production since end of 2020 and used by many researchers for advanced simulations at large scales.This workshop will focus on applications already enabled for a few GPUs, with the goal to improve scaling and performance on many GPUs.Dedicated lectures will present state-of-the-art tools and techniques for efficient multi-GPU computing; while the main focus is on interactive hands-on sessions together with mentors, in which the applications of the participants will be analyzed and optimized.
536 _ _ |a 5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs) and Research Groups (POF4-511)
|0 G:(DE-HGF)POF4-5112
|c POF4-511
|f POF IV
|x 0
536 _ _ |a 5122 - Future Computing & Big Data Systems (POF4-512)
|0 G:(DE-HGF)POF4-5122
|c POF4-512
|f POF IV
|x 1
536 _ _ |a 5121 - Supercomputing & Big Data Facilities (POF4-512)
|0 G:(DE-HGF)POF4-5121
|c POF4-512
|f POF IV
|x 2
536 _ _ |a ATML-X-DEV - ATML Accelerating Devices (ATML-X-DEV)
|0 G:(DE-Juel-1)ATML-X-DEV
|c ATML-X-DEV
|x 3
856 4 _ |u https://www.fz-juelich.de/en/ias/jsc/news/events/training-courses/2022/jwb-tuning-2022
909 C O |o oai:juser.fz-juelich.de:916420
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910 1 _ |a Forschungszentrum Jülich
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|6 P:(DE-Juel1)145478
913 1 _ |a DE-HGF
|b Key Technologies
|l Engineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action
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|0 G:(DE-HGF)POF4-511
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-500
|4 G:(DE-HGF)POF
|v Enabling Computational- & Data-Intensive Science and Engineering
|9 G:(DE-HGF)POF4-5112
|x 0
913 1 _ |a DE-HGF
|b Key Technologies
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|v Supercomputing & Big Data Infrastructures
|9 G:(DE-HGF)POF4-5122
|x 1
913 1 _ |a DE-HGF
|b Key Technologies
|l Engineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action
|1 G:(DE-HGF)POF4-510
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|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-500
|4 G:(DE-HGF)POF
|v Supercomputing & Big Data Infrastructures
|9 G:(DE-HGF)POF4-5121
|x 2
914 1 _ |y 2022
920 1 _ |0 I:(DE-Juel1)JSC-20090406
|k JSC
|l Jülich Supercomputing Center
|x 0
980 _ _ |a event
980 _ _ |a VDB
980 _ _ |a I:(DE-Juel1)JSC-20090406
980 _ _ |a UNRESTRICTED


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