Book description
Optimizing HPC Applications with Intel® Cluster Tools takes the reader on a tour of the fast-growing area of high performance computing and the optimization of hybrid programs. These programs typically combine distributed memory and shared memory programming models and use the Message Passing Interface (MPI) and OpenMP for multi-threading to achieve the ultimate goal of high performance at low power consumption on enterprise-class workstations and compute clusters.
The book focuses on optimization for clusters consisting of the Intel® Xeon processor, but the optimization methodologies also apply to the Intel® Xeon Phi™ coprocessor and heterogeneous clusters mixing both architectures. Besides the tutorial and reference content, the authors address and refute many myths and misconceptions surrounding the topic. The text is augmented and enriched by descriptions of real-life situations.
Table of contents
- Cover
- Title
- Copyright
- About ApressOpen
- Dedication
- Contents at a Glance
- Contents
- About the Authors
- About the Technical Reviewers
- Acknowledgments
- Foreword
- Introduction
- Chapter 1: No Time to Read This Book?
- Chapter 2: Overview of Platform Architectures
- Chapter 3: Top-Down Software Optimization
- Chapter 4: Addressing System Bottlenecks
-
Chapter 5: Addressing Application Bottlenecks: Distributed Memory
- Algorithm for Optimizing MPI Performance
- Comprehending the Underlying MPI Performance
- Doing Initial Performance Analysis
- Getting an Overview of Scalability and Performance
- Choosing the Optimization Objective
- Dealing with Load Imbalance
- Optimizing MPI Performance
- Using Advanced Analysis Techniques
- Summary
- References
- Chapter 6: Addressing Application Bottlenecks: Shared Memory
- Chapter 7: Addressing Application Bottlenecks: Microarchitecture
- Chapter 8: Application Design Considerations
- Index
Product information
- Title: Optimizing HPC Applications with Intel® Cluster Tools
- Author(s):
- Release date: October 2014
- Publisher(s): Apress
- ISBN: 9781430264972
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