High Performance Parallelism Pearls Volume Two: Multicore and Many-core Programming Approaches

✍ Scribed by Jeffers, Jim; Reinders, James

• Publisher: Morgan Kaufman
• Year: 2015
• Tongue: English
• Leaves: 544
• Edition: First edition
• Category: Library

✦ Synopsis

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.

• Promotes write-once, run-anywhere coding, showing how to code for high performance on multicore processors and Xeon Phi
• Examples from multiple vertical domains illustrating real-world use of Xeon Phi coprocessors
• Source code available for download to facilitate further exploration

✦ Table of Contents

Content:
Front Matter,Copyright,Contributors,Acknowledgments,Foreword,PrefaceEntitled to full textChapter 1 - Introduction, Pages 1-5
Chapter 2 - Numerical Weather Prediction Optimization, Pages 7-23
Chapter 3 - WRF Goddard Microphysics Scheme Optimization, Pages 25-41
Chapter 4 - Pairwise DNA Sequence Alignment Optimization, Pages 43-54
Chapter 5 - Accelerated Structural Bioinformatics for Drug Discovery, Pages 55-72
Chapter 6 - Amber PME Molecular Dynamics Optimization, Pages 73-89
Chapter 7 - Low-Latency Solutions for Financial Services Applications, Pages 91-111
Chapter 8 - Parallel Numerical Methods in Finance, Pages 113-137
Chapter 9 - Wilson Dslash Kernel From Lattice QCD Optimization, Pages 139-170
Chapter 10 - Cosmic Microwave Background Analysis: Nested Parallelism in Practice, Pages 171-190
Chapter 11 - Visual Search Optimization, Pages 191-209
Chapter 12 - Radio Frequency Ray Tracing, Pages 211-227
Chapter 13 - Exploring Use of the Reserved Core, Pages 229-242
Chapter 14 - High Performance Python Offloading, Pages 243-269
Chapter 15 - Fast Matrix Computations on Heterogeneous Streams, Pages 271-304
Chapter 16 - MPI-3 Shared Memory Programming Introduction, Pages 305-319
Chapter 17 - Coarse-Grained OpenMP for Scalable Hybrid Parallelism, Pages 321-334
Chapter 18 - Exploiting Multilevel Parallelism in Quantum Simulations, Pages 335-354
Chapter 19 - OpenCL: There and Back Again, Pages 355-378
Chapter 20 - OpenMP Versus OpenCL: Difference in Performance?, Pages 379-399
Chapter 21 - Prefetch Tuning Optimizations, Pages 401-419
Chapter 22 - SIMD Functions Via OpenMP, Pages 421-440
Chapter 23 - Vectorization Advice, Pages 441-462
Chapter 24 - Portable Explicit Vectorization Intrinsics, Pages 463-485
Chapter 25 - Power Analysis for Applications and Data Centers, Pages 487-510
Author Index, Pages 511-512
Subject Index, Pages 513-523