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

✍ Scribed by James Reinders, James Jeffers

• Publisher: Morgan Kaufmann
• Year: 2014
• Tongue: English
• Leaves: 520
• Edition: 1
• Category: Library

✦ Synopsis

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 Phi™
• Examples from multiple vertical domains illustrating parallel optimizations to modernize real-world codes
• Source code available for download to facilitate further exploration

✦ Table of Contents

Content:
Front Matter, Pages i-ii
Copyright, Page iv
Contributors, Pages xv-xxxvii
Acknowledgments, Page xxxix
Foreword, Pages xli-xliii
Preface, Page xlv
Chapter 1 - Introduction, Pages 1-5
Chapter 2 - From “Correct” to “Correct & Efficient”: A Hydro2D Case Study with Godunov’s Scheme, Pages 7-42
Chapter 3 - Better Concurrency and SIMD on HBM, Pages 43-67
Chapter 4 - Optimizing for Reacting Navier-Stokes Equations, Pages 69-85
Chapter 5 - Plesiochronous Phasing Barriers, Pages 87-115
Chapter 6 - Parallel Evaluation of Fault Tree Expressions, Pages 117-128
Chapter 7 - Deep-Learning Numerical Optimization, Pages 129-142
Chapter 8 - Optimizing Gather/Scatter Patterns, Pages 143-157
Chapter 9 - A Many-Core Implementation of the Direct N-Body Problem, Pages 159-174
Chapter 10 - N-Body Methods, Pages 175-183
Chapter 11 - Dynamic Load Balancing Using OpenMP 4.0, Pages 185-200
Chapter 12 - Concurrent Kernel Offloading, Pages 201-223
Chapter 13 - Heterogeneous Computing with MPI, Pages 225-238
Chapter 14 - Power Analysis on the Intel® Xeon Phi™ Coprocessor, Pages 239-253
Chapter 15 - Integrating Intel Xeon Phi Coprocessors into a Cluster Environment, Pages 255-276
Chapter 16 - Supporting Cluster File Systems on Intel® Xeon Phi™ Coprocessors, Pages 277-286
Chapter 17 - NWChem: Quantum Chemistry Simulations at Scale, Pages 287-306
Chapter 18 - Efficient Nested Parallelism on Large-Scale Systems, Pages 307-318
Chapter 19 - Performance Optimization of Black-Scholes Pricing, Pages 319-340
Chapter 20 - Data Transfer Using the Intel COI Library, Pages 341-348
Chapter 21 - High-Performance Ray Tracing, Pages 349-358
Chapter 22 - Portable Performance with OpenCL, Pages 359-375
Chapter 23 - Characterization and Optimization Methodology Applied to Stencil Computations, Pages 377-396
Chapter 24 - Profiling-Guided Optimization, Pages 397-423
Chapter 25 - Heterogeneous MPI application optimization with ITAC, Pages 425-441
Chapter 26 - Scalable Out-of-Core Solvers on a Cluster, Pages 443-455
Chapter 27 - Sparse Matrix-Vector Multiplication: Parallelization and Vectorization, Pages 457-476
Chapter 28 - Morton Order Improves Performance, Pages 477-490
Author Index, Pages 491-493
Subject Index, Pages 495-502