High Performance Parallelism Pearls Volume One

  • ID: 2986216
  • Book
  • 600 Pages
  • Elsevier Science and Technology
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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.

  • Promotes consistent standards-based programming, showing in detail how to code for high performance on multicore processors and Intel® Xeon PhiT
  • Examples from multiple vertical domains illustrating parallel optimizations to modernize real-world codes
  • Source code available for download to facilitate further exploration

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  1. Introduction
  2. Towards an efficient Godunov's scheme  on Phi
  3. Better Concurrency and SIMD on HBM
  4. Case Study: Analyzing and Optimizing Concurrency
  5. Plesiochronous Phasing Barriers
  6. Parallel Evaluation of Fault Tree Expressions
  7. Deep-learning and Numerical Optimization
  8. Optimizing Gather/Scatter Patterns
  9. A many core implementation of the direct N-body problem
  10. N-body Methods on Intel® Xeon PhiT Coprocessors
  11. Dynamic Load Balancing using OpenMP 4.0
  12. Concurrent Kernel Offloading
  13. Heterogeneous Computing with MPI
  14. Power Analysis on the Intel® Xeon PhiT Coprocessor
  15. Integrating Intel Xeon Phis into a Cluster
  16. Native File systems
  17. NWChem: Quantum Chemistry Simulations at Scale
  18. Efficient nested parallelism on large scale system
  19. Performance optimization of Black-Scholes pricing
  20. Host and Coprocessor Data Transfer through the COI
  21. High Performance Ray Tracing with Embree
  22. Portable and Perform with OpenCL
  23. Characterization and Auto-tuning of 3DFD.
  24. Profiling-guided optimization of cache performance
  25. Heterogeneous MPI optimization with ITAC
  26. Scalable Out-of-core Solvers on a Cluster
  27. Sparse matrix-vector multiplication: parallelization and vectorization
  28. Morton Order Improves Performance
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Reinders, James
James Reinders is a senior engineer who joined Intel Corporation in 1989 and has contributed to projects including the world's first TeraFLOP supercomputer (ASCI Red), as well as compilers and architecture work for a number of Intel processors and parallel systems. James has been a driver behind the development of Intel as a major provider of software development products, and serves as their chief software evangelist. James has published numerous articles, contributed to several books and is widely interviewed on parallelism. James has managed software development groups, customer service and consulting teams, business development and marketing teams. James is sought after to keynote on parallel programming, and is the author/co-author of three books currently in print including Structured Parallel Programming, published by Morgan Kaufmann in 2012.
Jeffers, James
Jim Jeffers was the primary strategic planner and one of the first full-time employees on the program that became Intel ® MIC. He served as lead SW Engineering Manager on the program and formed and launched the SW development team. As the program evolved, he became the workloads (applications) and SW performance team manager. He has some of the deepest insight into the market, architecture and programming usages of the MIC product line. He has been a developer and development manager for embedded and high performance systems for close to 30 years.
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