High performance parallelism pearls : multicore and many-core programming approaches
著者
書誌事項
High performance parallelism pearls : multicore and many-core programming approaches
Morgan Kaufmann/Elsevier, c2015
- [v. 1] : pbk
- v. 2 : pbk
大学図書館所蔵 件 / 全5件
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[v. 1] : pbk548-84-1911//1030202000526,
v. 2 : pbk548-84-1911//2030202000667 -
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注記
Includes bibliographical references and index
内容説明・目次
- 巻冊次
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[v. 1] : pbk ISBN 9780128021187
内容説明
High Performance Parallelism Pearls shows how to leverage parallelism on processors and coprocessors with the same programming - illustrating the most effective ways to better tap the computational potential of systems with Intel Xeon Phi coprocessors and Intel Xeon processors or other multicore processors. The book includes examples of successful programming efforts, drawn from across industries and domains such as chemistry, engineering, and environmental science. 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 these powerful systems, but also how to leverage parallelism across these heterogeneous systems.
目次
1. Introduction2. Towards an efficient Godunov's scheme on Phi3. Better Concurrency and SIMD on HBM4. Case Study: Analyzing and Optimizing Concurrency5. Plesiochronous Phasing Barriers6. Parallel Evaluation of Fault Tree Expressions7. Deep-learning and Numerical Optimization8. Optimizing Gather/Scatter Patterns9. A many core implementation of the direct N-body problem10. N-body Methods on Intel (R) Xeon Phi (TM) Coprocessors11. Dynamic Load Balancing using OpenMP 4.012. Concurrent Kernel Offloading13. Heterogeneous Computing with MPI14. Power Analysis on the Intel (R) Xeon Phi (TM) Coprocessor15. Integrating Intel Xeon Phis into a Cluster16. Native File systems17. NWChem: Quantum Chemistry Simulations at Scale18. Efficient nested parallelism on large scale system19. Performance optimization of Black-Scholes pricing20. Host and Coprocessor Data Transfer through the COI21. High Performance Ray Tracing with Embree22. Portable and Perform with OpenCL23. Characterization and Auto-tuning of 3DFD.24. Profiling-guided optimization of cache performance25. Heterogeneous MPI optimization with ITAC26. Scalable Out-of-core Solvers on a Cluster27. Sparse matrix-vector multiplication: parallelization and vectorization28. Morton Order Improves Performance
- 巻冊次
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v. 2 : pbk ISBN 9780128038192
内容説明
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.
目次
Introduction
Numerical Weather Prediction Optimization
WRF Goddard Microphysics Scheme Optimization
Pairwise DNA Sequence Alignment Optimization
Accelerated Structural Bioinformatics for Drug Discovery
Amber PME Molecular Dynamics Optimization
Low-Latency Solutions for Financial Services Applications
Parallel Numerical Methods in Finance
Wilson Dslash Kernel from Lattice QCD Optimization
Cosmic Microwave Background Analysis: Nested Parallelism
Visual Search Optimization
Radio Frequency Ray Tracing
Exploring Use of the Reserved Core
High Performance Python Offloading
Fast Matrix Computations on Heterogeneous Streams
MPI-3 Shared Memory Programming Introduction
Coarse-Grained OpenMP for Scalable Hybrid Parallelism
Exploiting Multilevel Parallelism in Quantum Simulations
OpenCL: There and Back Again
OpenMP Versus OpenCL: Difference in Performance?
Prefetch Tuning Optimizations
SIMD Functions Via OpenMP
Vectorization Advice
Portable Explicit Vectorization Intrinsics
Power Analysis for Applications and Data Centers
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