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제목 : High Performance Parallelism Pearls Volume Two
새책정가 : 80,910원 판매가격 : 35,000원
ISBN : 9780128038192 출판일 : 2015/8/3
저 자 : Jim Jeffers 출판사 : MK
책상태 : AAA급(새책)
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High Performance Parallelism Pearls Volume 2 offers another set of examples that demonstrate how to leverage parallelism. Similar to Volume 1, the techniques included here explain how to use processors and coprocessors with the same programming ?? illustrating the most effective ways to combine Xeon Phi coprocessors with Xeon and other multicore processors. The book includes examples of successful programming efforts, drawn from across industries and domains such as biomed, genetics, finance, manufacturing, imaging, and more. Each chapter in this edited work includes detailed explanations of the programming techniques used, while showing high performance results on both Intel Xeon Phi coprocessors and multicore processors. Learn from dozens of new examples and case studies illustrating "success stories" demonstrating not just the features of Xeon-powered systems, but also how to leverage parallelism across these heterogeneous systems.

목 차 :
IntroductionNumerical Weather Prediction OptimizationWRF Goddard Microphysics Scheme OptimizationPairwise DNA Sequence Alignment OptimizationAccelerated Structural Bioinformatics for Drug DiscoveryAmber PME Molecular Dynamics OptimizationLow-Latency Solutions for Financial Services ApplicationsParallel Numerical Methods in FinanceWilson Dslash Kernel from Lattice QCD OptimizationCosmic Microwave Background Analysis: Nested ParallelismVisual Search OptimizationRadio Frequency Ray TracingExploring Use of the Reserved CoreHigh Performance Python OffloadingFast Matrix Computations on Heterogeneous StreamsMPI-3 Shared Memory Programming IntroductionCoarse-Grained OpenMP for Scalable Hybrid ParallelismExploiting Multilevel Parallelism in Quantum SimulationsOpenCL: There and Back AgainOpenMP Versus OpenCL: Difference in Performance?Prefetch Tuning OptimizationsSIMD Functions Via OpenMPVectorization AdvicePortable Explicit Vectorization IntrinsicsPower Analysis for Applications and Data Centers
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