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

AMUSE

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書目名稱Euro-Par 2021: Parallel Processing Workshops年度引用學(xué)科排名




書目名稱Euro-Par 2021: Parallel Processing Workshops讀者反饋




書目名稱Euro-Par 2021: Parallel Processing Workshops讀者反饋學(xué)科排名

Talkative

,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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Commonplace

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

Commonplace

,Die Sternkunde der Naturv?lker,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

mutineer

印第安人

PAD416

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