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Titlebook: Applied Parallel and Scientific Computing; 11th International C Pekka Manninen,Per ?ster Conference proceedings 2013 Springer-Verlag Berlin

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發(fā)表于 2025-3-21 16:33:01 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Applied Parallel and Scientific Computing
期刊簡(jiǎn)稱11th International C
影響因子2023Pekka Manninen,Per ?ster
視頻videohttp://file.papertrans.cn/161/160021/160021.mp4
發(fā)行地址High quality selected papers.Unique visibility.State of the art research
學(xué)科分類Lecture Notes in Computer Science
圖書封面Titlebook: Applied Parallel and Scientific Computing; 11th International C Pekka Manninen,Per ?ster Conference proceedings 2013 Springer-Verlag Berlin
影響因子.This volume constitutes the refereed proceedings of the 11th International Conference on Applied Parallel and Scientific Computing, PARA 2012, held in Helsinki, Finland, in June 2012. The 35 revised full papers presented were selected from numerous submissions and are organized in five technical sessions covering the topics of advances in HPC applications, parallel algorithms, performance analyses and optimization, application of parallel computing in industry and engineering, and HPC interval methods. In addition, three of the topical minisymposia are described by a corresponding overview article on the minisymposia topic. In order to cover the state-of-the-art of the field, at the end of the book a set of abstracts describe some of the conference talks not elaborated into full articles..
Pindex Conference proceedings 2013
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書目名稱Applied Parallel and Scientific Computing影響因子(影響力)




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https://doi.org/10.1007/978-3-642-72748-1orm of a short set of articles for each of the talks presented. The work presented here was carried out under either the DEISA (receiving funding through the EU FP7 project RI-22291) or PRACE-2IP (receiving funding from the EU FP7 Programme (FP7/2007-2013) under grant agreement no RI-283493) projects.
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https://doi.org/10.1007/978-3-642-51137-0fficiency in memory and runtime on multicore CPU and GPU-equipped computers. Our methods are shown to be much more efficient than the direct method to compute the inverse of a nonsingular dense matrix, yielding up to 12 times faster performance on the CPU.
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https://doi.org/10.1007/978-3-642-36803-5exascale computing; graphics processing units; parallel algorithms; performance evaluation; solver; algor
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978-3-642-36802-8Springer-Verlag Berlin Heidelberg 2013
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Computational Physics on Graphics Processing Unitseview, we discuss advances made in the field of computational physics, focusing on classical molecular dynamics and quantum simulations for electronic structure calculations using the density functional theory, wave function techniques and quantum field theory.
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Time Propagation of Many-Body Quantum States on Graphics Processing Units model with exact diagonalization. We discretize the time into small steps and expand the time evolution operator into a Taylor series. An algorithm for calculating the time evolution on a GPU is given and tested on a 1D lattice to observe spin-charge separation.
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