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Titlebook: Algorithms and Architectures for Parallel Processing; ICA3PP 2016 Collocat Jesus Carretero,Javier Garcia-Blas,José Gracia Conference procee

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期刊全称Algorithms and Architectures for Parallel Processing
期刊简称ICA3PP 2016 Collocat
影响因子2023Jesus Carretero,Javier Garcia-Blas,José Gracia
视频video
发行地址Includes supplementary material:
学科分类Lecture Notes in Computer Science
图书封面Titlebook: Algorithms and Architectures for Parallel Processing; ICA3PP 2016 Collocat Jesus Carretero,Javier Garcia-Blas,José Gracia Conference procee
影响因子.This book constitutes the refereed workshop proceedings of the 16th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2016, held in Granada, Spain, in December 2016. The 30 full papers presented were carefully reviewed and selected from 58 submissions. They cover many dimensions of parallel algorithms and architectures, encompassing fundamental theoretical approaches, practical experimental projects, and commercial components and systems trying to push beyond the limits of existing technologies, including experimental efforts, innovative systems, and investigations that identify weaknesses in existing parallel processing technology..
Pindex Conference proceedings 2016
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Ins Eingemachte der Datenanalyse,g in mind that OpenACC is designed to be used without extensive knowledge about parallel programming. Our results show that the compilers are on their way to a reasonable maturity, presenting different strengths and weaknesses.
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https://doi.org/10.1007/978-3-658-16082-1e regions. Optimal parameters in the method are obtained by minimizing the prediction-error entropy. Experimental results show that the proposed method can yield an improvement compared with some state-of-the-art methods.
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https://doi.org/10.1007/978-3-658-32433-9hat data can be used by unauthorised users and improving corporative e-governance. We use an eToken with elliptic curve cryptography that performs a robust operation of the system and prevents from being falsified, duplicated or manipulated.
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Tuning the Blocksize for Dense Linear Algebra Factorization Routines with the Roofline Modellti-block computational kernels. An experimental evaluation validates the method and shows its convenience. We remark that the results obtained can be extended to other computational kernels similar to Gauss-Jordan elimination such as, e.g., matrix factorizations and the solution of linear least squares problems.
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