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Titlebook: Euro-Par 2019: Parallel Processing; 25th International C Ramin Yahyapour Conference proceedings 2019 Springer Nature Switzerland AG 2019 ar

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書目名稱Euro-Par 2019: Parallel Processing
副標(biāo)題25th International C
編輯Ramin Yahyapour
視頻videohttp://file.papertrans.cn/317/316542/316542.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Euro-Par 2019: Parallel Processing; 25th International C Ramin Yahyapour Conference proceedings 2019 Springer Nature Switzerland AG 2019 ar
描述.This book constitutes the proceedings of the 25th International Conference on Parallel and Distributed Computing, Euro-Par 2019, held in G?ttingen, Germany, in August 2019. ..The 36 full papers presented in this volume were carefully reviewed and selected from 142 submissions. They deal with parallel and distributed computing in general, focusing on support tools and environments; performance and power modeling, prediction and evaluation; scheduling and load balancing; high performance architectures and compilers; data management, analytics and deep learning; cluster and cloud computing; distributed systems and algorithms; parallel and distributed programming, interfaces, and languages; multicore and manycore parallelism; theory and algorithms for parallel computation and networking; parallel numerical methods and applications; accelerator computing; algorithms and systems for bioinformatics; and algorithms and systems for digital humanities. ?.
出版日期Conference proceedings 2019
關(guān)鍵詞artificial intelligence; clustering; computer architecture; computer systems; CUDA; data communication sy
版次1
doihttps://doi.org/10.1007/978-3-030-29400-7
isbn_softcover978-3-030-29399-4
isbn_ebook978-3-030-29400-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2019
The information of publication is updating

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Towards Portable Online Prediction of Network Utilization Using MPI-Level Monitoringe applications. A key ingredient to make this possible is an accurate prediction of the future network utilization, enabling the runtime to plan the background operations in advance, such as to avoid competing with the application for network bandwidth. In this paper, we propose a portable deep lear
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Combining Checkpointing and Data Compression to Accelerate Adjoint-Based Optimization Problems available computers. Data compression is an effective strategy to reduce this memory requirement by a certain factor, particularly if some loss in accuracy is acceptable. A popular alternative is checkpointing, where data is stored at selected points in time, and values at other times are recompute
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Linear Time Algorithms for Multiple Cluster Scheduling and Multiple Strip Packingatio better than 2 unless .. In this paper, we present an algorithm with approximation ratio 2 and running time . for both problems for . (and running time . for .). While a 2 approximation was known before, the running time of the algorithm is at least . in the worst case. Therefore, an . algorithm
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Scheduling on Two Unbounded Resources with Communication Costswe consider a platform with two types of machines, each containing an unbounded number of elements. We want to execute an application represented as a Directed Acyclic Graph (DAG) on this platform. Each task of the application has two possible execution times, depending on the type of machine it is
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