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Titlebook: Vector and Parallel Processing - VECPAR‘96; Second International José M. L. M. Palma,Jack Dongarra Conference proceedings 1997 Springer-Ver

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書目名稱Vector and Parallel Processing - VECPAR‘96
副標(biāo)題Second International
編輯José M. L. M. Palma,Jack Dongarra
視頻videohttp://file.papertrans.cn/981/980854/980854.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Vector and Parallel Processing - VECPAR‘96; Second International José M. L. M. Palma,Jack Dongarra Conference proceedings 1997 Springer-Ver
描述This book constitutes a carefully arranged selection of revised full papers chosen from the presentations given at the Second International Conference on Vector and Parallel Processing - Systems and Applications, VECPAR‘96, held in Porto, Portugal, in September 1996..Besides 10 invited papers by internationally leading experts, 17 papers were accepted from the submitted conference papers for inclusion in this documentation following a second round of refereeing. A broad spectrum of topics and applications for which parallelism contributes to progress is covered, among them parallel linear algebra, computational fluid dynamics, data parallelism, implementational issues, optimization, finite element computations, simulation, and visualisation.
出版日期Conference proceedings 1997
關(guān)鍵詞Algorithmische Mathematik; Parallele Lineare Algebra; computational fluid dynamics; computational mathe
版次1
doihttps://doi.org/10.1007/3-540-62828-2
isbn_softcover978-3-540-62828-6
isbn_ebook978-3-540-68699-6Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 1997
The information of publication is updating

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Irregular data-parallel objects in C++,s. The implementation of irregular algorithms requires a programming effort to project the irregular data structures onto regular structures. We first propose in this paper a classification of existing data-parallel languages. We briefly describe their irregular and dynamic aspects, and derive diffe
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,ProHos-1 — A vector processor for the efficient estimation of higher-order moments,on of higher-order moments of sampled data taken from real systems. For applications that require real-time processing, the performance achieved by common microprocessors or digital signal processors is not good enough to carry out the large number of calculations needed for their estimation. This p
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The use of computational kernels in full and sparse linear solvers, efficient code design on high-pportant for both simplifying application software development and improving reliability..This is illustrated by considering the solution of full and sparse linear systems. We describe successive layers of computational kernels such as the BLAS, the sparse BLAS, blocked algorithms for factorizing ful
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Parallel implementation of a symmetric eigensolver based on the Yau and Lu method,bspace decomposition method for dense symmetric matrices followed by numerical results and work in progress of a distributed-memory implementation. We expect that the algorithm‘s heavy reliance on matrix-matrix multiplication, coupled with FFT should yield a highly parallelizable algorithm. We prese
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