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Titlebook: Euro-Par 2021: Parallel Processing Workshops; Euro-Par 2021 Intern Ricardo Chaves,Dora B. Heras,Laura Ricci Conference proceedings 2022 Spr

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发表于 2025-3-21 16:17:00 | 显示全部楼层 |阅读模式
书目名称Euro-Par 2021: Parallel Processing Workshops
副标题Euro-Par 2021 Intern
编辑Ricardo Chaves,Dora B. Heras,Laura Ricci
视频video
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Euro-Par 2021: Parallel Processing Workshops; Euro-Par 2021 Intern Ricardo Chaves,Dora B. Heras,Laura Ricci Conference proceedings 2022 Spr
描述This book constitutes revised selected papers from the workshops held at the 27th International Conference on Parallel and Distributed Computing, Euro-Par 2021, which took place in Portugal, in August 2021. The workshops were held virtually due to the coronavirus pandemic..The 39 full papers presented in this volume were carefully reviewed and selected from numerous submissions. The papers cover all aspects of parallel and distributed processing. These range from theory to practice, from small to the largest parallel and distributed systems and infrastructures, from fundamental computational problems to full-edged applications, from architecture, compiler, language and interface design and implementation to tools, support infrastructures, and application performance aspects..
出版日期Conference proceedings 2022
关键词computer hardware; computer networks; computer programming; computer science; computer systems; databases
版次1
doihttps://doi.org/10.1007/978-3-031-06156-1
isbn_softcover978-3-031-06155-4
isbn_ebook978-3-031-06156-1Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2022
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,Einführung in die erste Auflage,hat improves the performance of stream-based Java applications. The approach enables the effective usage of Java for HPC applications, due to data locality improvements (i.e., support for efficient data layouts), without losing the object-oriented view of data in the code. The approach extends the J
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https://doi.org/10.1007/978-3-663-09711-2e flexible and thus have many practical applications. In this paper we present the results of our attempt to use the recent advancements in Reinforcement Learning to automate the management of resources in a compute cloud environment. We describe a new approach to self-adaptation of autonomous manag
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,Die Sternkunde der Naturvölker,heoretic approach where players tend to achieve a solution by reaching a Nash equilibrium. We propose a fully distributed algorithm based on applying the Spatial Prisoner’s Dilemma (SPD) game and a phenomenon of collective behavior of players participating in the game composed of two classes of auto
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https://doi.org/10.1007/978-3-0348-6519-7omputational complexity and big memory requirements, which exceed the capacity of small devices for inference. Knowledge distillation is an efficient approach to compress a large deep model (a teacher model) to a compact model (a student model). Existing online knowledge distillation methods typical
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