Poster (After Call)

FZJ-2020-00114

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Tasking Meets GPUs:Fighting Deadlocks and Other Monsters

Morgenstern, L. (Corresponding author)FZJ* ; Beckmann, A.FZJ* ; Kabadshow, I.FZJ* ; Werner -> Werner, M.

2019

Please use a persistent id in citations: http://hdl.handle.net/2128/23824

Abstract: Task parallelism is omnipresent these days; whether in data mining or machine learning, for matrix factorization or even molecular dynamics. Despite the successof task parallelism on CPUs, there is currently no performant way to exploit task parallelism of synchronization-critical algorithms on GPUs.Hence, our goal is the development of a task-based programming model to exploit fine-grained task parallelism on heterogeneous hardware.

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Contributing Institute(s):

1. Jülich Supercomputing Center (JSC)

Research Program(s):

1. 511 - Computational Science and Mathematical Methods (POF3-511) (POF3-511)
2. PhD no Grant - Doktorand ohne besondere Förderung (PHD-NO-GRANT-20170405) (PHD-NO-GRANT-20170405)

Appears in the scientific report 2019

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Database coverage:

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