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Titlebook: OpenMP: Portable Multi-Level Parallelism on Modern Systems; 16th International W Kent Milfeld,Bronis R. de Supinski,Jannis Klinkenb Confere

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書目名稱OpenMP: Portable Multi-Level Parallelism on Modern Systems
副標題16th International W
編輯Kent Milfeld,Bronis R. de Supinski,Jannis Klinkenb
視頻videohttp://file.papertrans.cn/702/701929/701929.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: OpenMP: Portable Multi-Level Parallelism on Modern Systems; 16th International W Kent Milfeld,Bronis R. de Supinski,Jannis Klinkenb Confere
描述.This book constitutes the proceedings of the 16th International Workshop on OpenMP, IWOMP 2020, held in Austin, TX, USA, in September 2020.?The conference was held virtually due to the COVID-19 pandemic...The 21 full papers presented in this volume were carefully reviewed and selected for inclusion in this book. The papers are organized in topical sections named: performance methodologies; applications; OpenMP extensions; performance studies; tools; NUMA; compilation techniques; heterogeneous computing; and memory..The chapters ‘A Case Study on Addressing Complex Load Imbalance in OpenMP’ and ‘A Study of Memory Anomalies in OpenMP Applications’ are available open access under a Creative Commons Attribution 4.0 License via link.springer.com..
出版日期Conference proceedings 2020
關鍵詞computer programming; distributed computer systems; embedded systems; field programmable gate array; fpg
版次1
doihttps://doi.org/10.1007/978-3-030-58144-2
isbn_softcover978-3-030-58143-5
isbn_ebook978-3-030-58144-2Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2020
The information of publication is updating

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0302-9743 penMP’ and ‘A Study of Memory Anomalies in OpenMP Applications’ are available open access under a Creative Commons Attribution 4.0 License via link.springer.com..978-3-030-58143-5978-3-030-58144-2Series ISSN 0302-9743 Series E-ISSN 1611-3349
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Evaluating the Efficiency of OpenMP Tasking for Unbalanced Computation on Diverse CPU Architecturestures. We measure parallel efficiency to examine each implementation’s performance in response to varying task granularity. We find that most implementations achieve over 90% efficiency using all available cores for tasks of .(100.) instructions, and the best even manage tasks of .(10.) instructions well.
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0302-9743 ?The conference was held virtually due to the COVID-19 pandemic...The 21 full papers presented in this volume were carefully reviewed and selected for inclusion in this book. The papers are organized in topical sections named: performance methodologies; applications; OpenMP extensions; performance s
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