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AUTOMATIC PARALLELIZATION FOR A CLASS OF REGULAR COMPUTATIONS
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AUTOMATIC PARALLELIZATION FOR A CLASS OF REGULAR COMPUTATIONS
Author:AL CHEN X ET (EN)
A introductory fragment is available
Language of a book: Английский
Publisher: Gardners Books

    The automatic generation of parallel code from high level sequential description is of key importance to the wide spread use of high performance machine architectures. This text considers (in detail) the theory and practical realization of automatic mapping of algorithms generated from systems of uniform recurrence equations (do-lccps) onto fixed size architectures with defined communication primitives. Experimental results of the mapping scheme and its implementation are given.Contents:Survey and Analysis of Partitioning and MappingImprovements to Some Existing Partitioning and Mapping MethodsA Methodology of Partitioning and Mapping for Given (N-1)-D Regular ArraysOptimal Mapping onto Lower-Dimensional Regular ArraysThe Structure of Parallel ProgramsParallel Code GenerationExperimental Results and DiscussionsConclusionBibliographyReadership: Postgraduate students and researchers in academics & industry, compiler writers, computer scientists and electrical engineers.Key Features:Introduces the most recently developed kernel methodsDiscusses fundamental kernel design principlesSurveys the most important kernels for structured dataContains an in-depth discussion of kernels for graphs

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