深入理解并行编程

Name: 深入理解并行编程
Availability: InStock
Rating: 8.8 (46 reviews)
ISBN: 9787121315084

[美] Paul E.Mckenney（保罗·E·麦肯尼)

出版社

电子工业出版社

出版时间

2017-07-01

ISBN

9787121315084

评分

★★★★★

标签

工业技术

书籍介绍

《深入理解并行编程》首先以霍金提出的两个理论物理限制为引子，解释了多核并行计算兴起的原因，并从硬件的角度阐述并行编程的难题。接着，《深入理解并行编程》以常见的计数器为例，探讨其不同的实现方法及适用场景。在这些实现方法中，除了介绍常见的锁以外，《深入理解并行编程》还重点介绍了RCU的使用及其原理，以及实现RCU的基础：内存屏障。最后，《深入理解并行编程》还介绍了并行软件的验证，以及并行实时计算等内容。《深入理解并行编程》适合于对并行编程有兴趣的大学生、研究生，以及需要对项目进行深度性能优化的软硬件工程师，特别值得一提的是，《深入理解并行编程》对操作系统内核工程师也很有价值。

作者简介

Paul E. McKenney is the core contributor of Linux kernel .

AI导读

核心看点

从硬件视角剖析并行编程难题
深度解析RCU机制与内存屏障
涵盖并行软件验证与实时计算

读者共识

内容经典深刻，值得反复研读
排版存在瑕疵，阅读体验略差
作者功力深厚，被誉为大师之作

精彩摘录

"Therefore, if you wish to argue that parallel programming will remain as difficult as it is currently perceived by many to be, it is you who bears the burden of proof, keeping in mind the many centuries of counter-examples in a variety of fields of endeavor."
"the primary goals of parallel pro- gramming are performance, productivity, and gener- ality."
"This book is intended primarily for developers working near the bottom of the stack, where performance and generality are paramount concerns."
"It is important to keep in mind that parallelism is but one way to improve performance. Other well- known approaches include the following, in roughly increasing order of difficulty: 1. Run multiple instances of a sequential applica- tion. 2. Construct the application to make use of exist- ing paral"
"Most people have an intuitive understanding that passing messages between systems is considerably more expensive than performing simple calcula- tions within the confines of a single system. How- ever, it is not always so clear that communicat- ing among threads within the confines of a single share"
"shared-memory parallel programs must normally deal with no obstacle worse than a cache miss, while a distributed parallel program will typically incur the larger network communication latencies."
"3.3.3 Light, Not Electrons Although the speed of light would be a hard limit, the fact is that semiconductor devices are limited by the speed of electrons rather than that of light, given that electrons in semiconductor materials move at between 3% and 30% of the speed of light in a vacuum."