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计算机科学丛书:高性能科学与工程计算

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《计算机科学丛书:高性能科学与工程计算》从工程实践的角度介绍了高性能计算的相关知识。主要内容包括现代处理器的体系结构、为读者理解当前体系结构和代码中的性能潜力和局限提供了坚实的理论基础。接下来讨论了高性能计算中的关键问题,包括串行优化、并行、OpenMP、MPI、混合程序设计技术。作者根据自身的研究也提出了一些前沿问题的解决方案,如编写有效的C++代码、GPU编程等。

Catalogue

Introduction to High Performance Computing for Scientists and Engineers
出版者的话
译者序

前言
缩略词
第1章 当代处理器
1.1 存储程序的计算机体系结构
1.2 基于高速缓存的通用微处理器体系结构
1.2.1 性能指标和基准测试
1.2.2 晶体管:摩尔定律
1.2.3 流水线
1.2.4 超标量
1.2.5 SIMD
1.3 存储层次
1.3.1 高速缓存
1.3.2 高速缓存映射
1.3.3 预取
1.4 多核处理器
1.5 多线程处理器
1.6 向量处理器
1.6.1 设计原理
1.6.2 最高性能估计
1.6.3 程序设计
习题
第2章 串行代码基本优化技术
2.1 标量剖析
2.1.1 基于函数和代码行的程序剖析
2.1.2 硬件性能计数器
2.1.3 手工代码插入
2.2 优化常识
2.2.1 少做工作
2.2.2 避免耗时运算
2.2.3 缩减工作集
2.3 小方法,大改进
2.3.1 消除常用子表达式
2.3.2 避免分支
2.3.3 使用SIMD指令集
2.4 编译器作用
2.4.1 通用优化选项
2.4.2 内联
2.4.3 别名
2.4.4 计算准确性
2.4.5 寄存器优化
2.4.6 利用编译日志
2.5 C++优化
2.5.1 临时变量
2.5.2 动态内存管理
2.5.3 循环与迭代器
习题
第3章 数据访存优化
3.1 平衡分析与lightspeed评估
3.1.1 基于带宽的性能建模
3.1.2 STREAM 基准测试
3.2 存储顺序
3.3 案例分析:Jacobi算法
3.4 案例分析:稠密矩阵转置
3.5 算法分类和访存优化
3.5.1 O(N)/O(N)
3.5.2 O(N2)/O(N2)
3.5.3 O(N3)/O(N2)
3.6 案例分析:稀疏矩阵向量乘
3.6.1 稀疏矩阵的存储机制
3.6.2 JDS sMVM优化
习题
第4章 并行计算机
4.1 并行计算模式分类
4.2 共享存储计算机
4.2.1 cache一致性
4.2.2 UMA
4.2.3 ccNUMA
4.3 分布式存储计算机
4.4 混合型系统
4.5 网络
4.5.1 网络的基本性能特征
4.5.2 总线
4.5.3 交换网络和胖树网络
4.5.4 Mesh 网络
4.5.5 混合网络
习题
第5章 并行性基础
5.1 为什么并行化
5.2 并行性
5.2.1 数据并行性
5.2.2 功能并行性
5.3 并行扩展性
5.3.1 限制并行执行的因素
5.3.2 可扩展性指标
5.3.3 简单可扩展性定律
5.3.4 并行效率
5.3.5 串行性能与强可扩展性
5.3.6 改进的性能模型
5.3.7 选择正确的扩展性基准
5.3.8 案例分析:低速处理器计算机能否变得更快
5.3.9 负载不均衡
习题
第6章 使用OpenMP进行共享存储并行编程
6.1 OpenMP简介
6.1.1 并行执行
6.1.2 数据作用域
6.1.3 循环的OpenMP工作共享
6.1.4 同步
6.1.5 归约
6.1.6 循环调度
6.1.7 任务
6.1.8 其他方面
6.2 案例分析:OpenMP并行实现Jacobi算法
6.3 高级OpenMP:波前并行化
习题
第7章 高效OpenMP编程
7.1 OpenMP程序性能分析
7.2 性能缺陷
7.2.1 减轻Open MP共享区开销
7.2.2 决定短循环的OpenMP开销
7.2.3 串行化
7.2.4 伪共享
7.3 案例分析:并行稀疏矩阵向量乘
习题
第8章 ccNUMA体系结构的局部性优化
8.1 ccNUMA的局部访问
8.1.1 首次访问方式分配页面
8.1.2 通过其他方式的局部性访问
8.2 案例分析:稀疏MVM的ccNUMA优化
8.3 页面布局缺陷
8.3.1 非NUMA友好的OpenMP调度
8.3.2 文件系统高速缓存
8.4 C++中的ccNUMA问题
8.4.1 对象数组
8.4.2 标准模板库
习题
第9章 使用MPI进行分布式存储并行内存编程
9.1 消息传递
9.2 MPI简介
9.2.1 一个简单例子
9.2.2 消息和点对点通信
9.2.3 集合通信
9.2.4 非阻塞点对点通信
9.2.5 虚拟拓扑
9.3 实例:Jacobi解法器的MPI并行
9.3.1 MPI实现
9.3.2 性能特征
习题
第10章 高效MPI编程
10.1 MPI性能工具
10.2 通信参数
10.3 同步、串行化和竞争
10.3.1 隐式串行化和同步
10.3.2 竞争
10.4 降低通信开销
10.4.1 最优化区域分解
10.4.2 聚合消息
10.4.3 非阻塞与异步通信
10.4.4 集合通信
10.5 理解节点内点对点通信
习题
第11章 MPI与OpenMP混合编程
11.1 基本MPI/OpenMP混合编程模型
11.1.1 向量模式实现
11.1.2 任务模式实现
11.1.3 案例分析:混合Jacobi解法器
11.2 MPI线程交互分类
11.3 混合分解及映射
11.3.1 每个节点一个MPI进程
11.3.2 每个插槽一个MPI进程
11.3.3 每个插槽多个MPI进程
11.4 混合编程的优势和劣势
11.4.1 改善的收敛速度
11.4.2 共享高速缓存中的数据重用
11.4.3 利用额外级别的并行性
11.4.4 重叠MPI通信和计算
11.4.5 减少MPI开销
11.4.6 多级别开销
11.4.7 向量模式下批量同步通信
附录A 多核环境中的拓扑和亲缘性
A.1 拓扑
A.2 线程和进程分布
A.2.1 外部亲缘性工具
A.2.2 程序控制亲缘性
A.3 非页面首次访问分配策略
附录B 习题解答
参考文献

Introduction

Georg Hager和Gerhaid Wellein在本书中为科学家和工程师循序渐进地介绍了高性能计算知识。本书的风格和讲解方法十分易读并容易理解。
二十多年前提出的计算建模和模拟的概念已经成为理论研究和实验研究之外的第三种科学研究方法,软件、数学模型和算法是科学计算领域的关键核心。并行硬件的发展十分迅猛,特别是以指数速度增长的处理器性能以及处理器体系结构和超级计算机系统设计的研究。当计算建模和模拟成为科学研究的第三种方法后,复杂软件及其生态系统将会处于本研究领域的核心地位。
在应用层,科学必须展现为数学模型,并进一步表达为算法和对应的软件代码。相应地,大部分科学基金也在转向这样的项目,即需要领域科学家、计算机科学家及应用数学家协同合作,从原始科学构想到最终可执行软件的研究。这样的项目也需要数学库、协议和系统软件等这些需要花费数年开发并需要持久维护的大规模底层架构的支持,这些软件通常比最初设计的硬件平台甚至是设计和开发人员存活更长时间。
本书覆盖了当代处理器体系结构的基础知识,以及为科学计算程序有效地利用硬件特性进行串行优化的基本技术。作者讨论了数据移动中的关键问题并辅以实例,并以简单易读的方式介绍了高性能计算中的重要问题。书中还讨论了共享存储、非一致访问以及分布式存储的并行化方法。除此之外,还重点介绍了常用的并行编程模型,例如.OpenMP、MPI以及混合编程方法。
我们生活在一个高效利用超级计算机系统进行大规模高性能计算的时代。本书对并行理论、优化技术、体系结构和现代高性能计算系统软件等方面进行了介绍,特别是对科学和工程问题的关注使得本书成为一本独特的教材,因此我强烈向科学家和工程师推荐此书,本书可以作为一本优秀的参考书,我相信本书会令大多数读者受益。
Jack Dongarra
美国田纳西大学

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