Software Optimization for High Performance Computing: Creating Faster Applications (HP Professional Series)

Prentice Hall, 2000 — 377 p. This book is written for programmers who want to get high performance from the software they write. The optimization techniques discussed are applicable to all computers, but are of most interest to designers of software for high performance computers, since they are most concerned with high performance. The main focus is on UNIX, though since Windows NT is now being used on high performance servers, there is limited coverage on this. Single processor and parallel performance is discussed. Contents Introduction. Hardware Overview-Your Work Area. Processors: The Core of High Performance Computing. Data Storage. An Overview of Parallel Processing. Software Techniques-The Tools. How the Compiler Can Help and Hinder Performances. Predicting and Measuring Performance. Is High Performance Computing Language Dependent Parallel Processing-An Algorithmic Approach. Applications-Using The Tools. High Performance Libraries. Mathematical Kernels: The Building Blocks of High Performance. Faster Solutions for Systems of Equations. High Performance Algorithms and Approaches for Signal Processing. Index.

The hands-on guide to high-performance coding and algorithm optimization.

This hands-on guide to software optimization introduces state-of-the-art solutions for every key aspect of software performance – both code-based and algorithm-based.

Two leading HP software performance experts offer comparative optimization strategies for RISC and for the new Explicitly Parallel Instruction Computing (EPIC) design used in Intel IA-64 processors. Using many practical examples, they offer specific techniques for:

• Predicting and measuring performance – and identifying your best optimization opportunities
• Storage optimization: cache, system memory, virtual memory, and I/0
• Parallel processing: distributed-memory and shared-memory (SMP and ccNUMA)
• Compilers and loop optimization
• Enhancing parallelism: compiler directives, threads, and message passing
• Mathematical libraries and algorithms

  Whether you're a developer, ISV, or technical researcher, if you need to optimize high-performance software on today's leading processors, one book delivers the advanced techniques and code examples you need: Software Optimization for High Performance Computing.

This is the most hands-on guide to writing high-performance software. Using many practical examples, two of Hewlett-Packard's leading software performance experts review both code-based and algorithm-based techniques. This book addresses every key factor that impacts software performance, from mathematical libraries to compilers to underlying hardware.The authors review the role of processor design in software performance, covering each leading approach, and offering comparative optimization strategies for CISC, RISC, vector and Long Instruction Word computing, and the new Explicitly Parallel Instruction Computing (EPIC) design used by Intel/HP IA-64 processors. They address storage devices, including cache and system memory; and review each leading approach to parallel processing, including distributed memory and shared memory (UMA and NUMA) designs. The book includes detailed chapters on compiler optimization; profiling and timing code; algorithmic approaches to parallelism such as compiler directives, threads, and message passing. It also demonstrates powerful techniques for enhancing performance through the use of mathematical libraries, mathematical kernels, and equation-solving techniques such as LU decomposition. Aimed at programmers who want to get high-performance from the software they write, this text provides a hands-on book for high-performance code and algorithm optimization