High Performance Computing: Programming and Applications (Hardcover)

John Levesque, Gene Wagenbreth

  • 出版商: CRC
  • 出版日期: 2010-12-14
  • 售價: $2,880
  • 貴賓價: 9.5$2,736
  • 語言: 英文
  • 頁數: 244
  • 裝訂: Hardcover
  • ISBN: 1420077058
  • ISBN-13: 9781420077056
  • 相關分類: C 程式語言程式語言
  • 立即出貨 (庫存 < 3)

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商品描述

High Performance Computing: Programming and Applications presents techniques that address new performance issues in the programming of high performance computing (HPC) applications. Omitting tedious details, the book discusses hardware architecture concepts and programming techniques that are the most pertinent to application developers for achieving high performance. Even though the text concentrates on C and Fortran, the techniques described can be applied to other languages, such as C++ and Java.

Drawing on their experience with chips from AMD and systems, interconnects, and software from Cray Inc., the authors explore the problems that create bottlenecks in attaining good performance. They cover techniques that pertain to each of the three levels of parallelism:

1. Message passing between the nodes
2. Shared memory parallelism on the nodes or the multiple instruction, multiple data (MIMD) units on the accelerator
3. Vectorization on the inner level

After discussing architectural and software challenges, the book outlines a strategy for porting and optimizing an existing application to a large massively parallel processor (MPP) system. With a look toward the future, it also introduces the use of general purpose graphics processing units (GPGPUs) for carrying out HPC computations. A companion website at www.hybridmulticoreoptimization.com contains all the examples from the book, along with updated timing results on the latest released processors.

商品描述(中文翻譯)

《高性能計算:編程與應用》介紹了解決高性能計算(HPC)應用程序編程中的新性能問題的技術。本書省略了冗長的細節,討論了對應用程序開發人員實現高性能最相關的硬件架構概念和編程技術。儘管文本集中在C和Fortran上,但所描述的技術也可以應用於其他語言,如C++和Java。

作者們根據他們在AMD芯片和Cray Inc.系統、互連和軟件方面的經驗,探討了影響性能的瓶頸問題。他們涵蓋了與三個級別的並行性相關的技術:

1. 节点之间的消息传递
2. 节点上的共享内存并行性或加速器上的多指令多数据(MIMD)单元
3. 内部层次的向量化

在討論了架構和軟件挑戰之後,本書概述了將現有應用程序移植和優化到大型大規模並行處理器(MPP)系統的策略。為了展望未來,它還介紹了使用通用圖形處理器(GPGPU)進行HPC計算。附帶網站www.hybridmulticoreoptimization.com包含了本書中的所有示例,以及最新發布的處理器的更新計時結果。