並行科學計算
弗雷德裏克·馬古雷斯(Frédéric Magoulès),弗朗索瓦-澤維爾·魯(Fran?ois-Xavier Roux),鄒秦萌
- 出版商: 電子工業
- 出版日期: 2026-03-01
- 售價: $588
- 貴賓價: 9.5 折 $558
- 語言: 簡體中文
- 頁數: 212
- ISBN: 7121524465
- ISBN-13: 9787121524462
-
相關分類:
工程數學 Engineering-mathematics
- 此書翻譯自: Parallel Scientific Computing (Iste) (Hardcover)
立即出貨 (庫存 < 3)
買這商品的人也買了...
-
離散時間訊號處理 (Discrete-Time Signal Processing, 3/e)$800$760 -
$447數據驅動的科學和工程:機器學習、動力系統與控制詳解 -
$504ANSYS2020 多物理耦合場有限元分析從入門到精通 -
$759計算機圖形學原理及實踐, 3/e (進階篇) -
$294數值方法 -
機器學習與振動信號處理$354$336 -
$453神經網絡與深度學習 — 基於 MATLAB 的模擬與實現 -
$351數學物理方法 -- 使用 MATLAB 建模與模擬 -
$402MATLAB 圖形學基礎 -
$407不焦慮的數學思想:讓人人能開竅 -
$657Python 深度學習實戰 -
概率論沈思錄$1,079$1,025 -
$382虛擬模擬 -
合成生物學智能化設計與應用$774$735 -
系統模擬基礎教程 (基於 Python 語言)$539$512 -
應用泛函分析$354$336 -
$468Grasshopper 參數化技術:從基礎建模到數字設計 -
$414計算力學 -
從線性代數到量子計算$599$569 -
$894人工智能大模型數學基礎 -
數學物理方程:從常微分方程到偏微分方程$468$444 -
人工智能驅動的機械故障診斷技術及應用$594$564 -
$538人工智能數學方法(基礎篇) -
COMSOL 多物理場仿真從入門到工程實戰$708$672 -
$714計算機視覺:YOLO 目標檢測原理與實踐
商品描述
並行科學計算是高性能計算的一種基本實現方法,提供底層數學邏輯和實現算法。線性方程組求解問題是工程領域的核心問題,本書系統介紹大型稀疏線性方程組的並行求解方法,包括並行體系結構、編程模型、數值代數等基礎知識,線性方程組的直接求解法和間接求解法,以及相關並行算法和區域分解算法。本書可以幫助讀者高效學習並行算法,從而快速解決工程實踐中的線性方程組求解問題。本書適合信息與計算科學相關專業的本科高年級學生、研究生閱讀,也可作為從事相關工作的科研和工程技術人員的參考用書。
目錄大綱
第 1 章 計算機體系結構 ······························································.1
1.1 不同類型的並行 ·······························································.1
1.1.1 重疊、並發和並行 ·····················································.1
1.1.2 算術邏輯單元中的空間並行與時間並行 ··························.3
1.1.3 並行與內存······························································.5
1.2 存儲設備體系結構 ····························································.5
1.2.1 多體交錯式內存 ························································.6
1.2.2 多級存儲·································································.7
1.2.3 分布式存儲·····························································.11
1.3 混合體系結構 ··································································12
1.3.1 GPU 加速器 ·····························································12
1.3.2 混合計算機······························································13
第 2 章 並行化與編程模型 ···························································15
2.1 並行化 ···········································································15
2.2 性能指標 ········································································17
2.2.1 並行度····································································17
2.2.2 負載平衡·································································18
2.2.3 粒度·······································································19
2.2.4 可擴展性·································································19
2.3 數據並行 ········································································20
2.3.1 循環·······································································20
2.3.2 依賴性····································································21
2.3.3 依賴性示例······························································22
2.3.4 歸約運算·································································24
2.3.5 嵌套循環·································································25
2.3.6 OpenMP ··································································29
2.4 案例分析:向量化 ····························································31
2.4.1 向量計算機和向量化 ··················································31
2.4.2 依賴性····································································32
2.4.3 歸約運算·································································33
2.4.4 流水線運算······························································34
2.5 消息傳遞 ········································································36
2.5.1 消息傳遞編程 ···························································36
2.5.2 並行環境管理 ···························································36
2.5.3 點對點通信······························································37
2.5.4 聚合通信·································································38
第 3 章 並行算法概念 ·································································41
3.1 並行循環算法 ··································································41
3.1.1 歸約算法的基本原理 ··················································41
3.1.2 歸約算法的開銷和穩定性 ············································42
3.1.3 循環歸約·································································44
3.2 矩陣乘法的數據分布 ·························································45
3.2.1 行算法和列算法 ························································45
3.2.2 分塊算法·································································47
3.2.3 分布式算法······························································50
3.2.4 算法實現·································································51
第 4 章 矩陣計算基礎 ·································································55
4.1 線性代數回顧 ··································································55
4.1.1 向量空間、點積、正交投影 ·········································55
4.1.2 線性映射與矩陣 ························································58
4.2 矩陣性質 ········································································61
4.2.1 特殊矩陣、特征值、特征向量 ······································61
4.2.2 矩陣範數·································································63
4.2.3 基變換····································································65
4.2.4 矩陣的條件數 ···························································66
第 5 章 稀疏矩陣 ·······································································71
5.1 稀疏矩陣的起源 ·······························································71
5.2 稀疏矩陣的並行構建:共享存儲···········································75
5.3 稀疏矩陣的分塊並行構建:分布式存儲 ··································75
第 6 章 用 LU 分解法求解線性方程組·············································78
6.1 線性方程組求解 ·······························································78
6.1.1 直接法····································································78
6.1.2 疊代法····································································79
6.2 LU 分解的原理 ·································································81
6.3 高斯消元法 ·····································································84
6.4 高斯-若爾當消元法 ···························································86
6.5 對稱矩陣的 Crout 分解和楚列斯基分解 ··································91
第 7 章 稠密矩陣 LU 分解的並行化················································94
7.1 分塊分解 ········································································94
7.2 在 MPI 編程環境中實現分塊分解 ··········································98
7.3 前向-後向替換法的並行化 ···············································.102
第 8 章 稀疏矩陣的 LU 分解 ······················································.104
8.1 分解後的矩陣結構 ·························································.104
8.2 符號分解與重新編號 ······················································.107
8.3 消去樹 ········································································.110
8.4 消去樹與依賴性 ····························································.115
8.5 嵌套剖分 ·····································································.116
8.6 前向-後向替換 ······························································.120
第 9 章 對稱正定矩陣的 Krylov 法·············································.123
9.1 Krylov 子空間基礎 ·························································.123
9.1.1 Krylov 子空間························································.123
9.1.2 Arnoldi 基的構建····················································.125
9.2 對稱矩陣 Lanczos 基的構建 ·············································.127
9.3 Lanczos 法 ··································································.128
9.4 共軛梯度法 ··································································.132
9.5 與梯度法的對比 ····························································.136
9.6 對稱正定矩陣的預處理 ···················································.138
第 10 章 任意矩陣的正交化方法 ················································.141
10.1 GMRES 法 ·································································.141
10.2 面向對稱矩陣的 MINRES 法 ···········································.148
10.3 ORTHODIR 法 ····························································.151
10.4 非對稱矩陣的預處理 ·····················································.152
第 11 章 非對稱矩陣的雙正交化方法··········································.154
11.1 非對稱矩陣雙正交基的構建 ············································.154
11.2 非對稱 Lanczos 法 ·······················································.158
11.3 雙共軛梯度法 ······························································.159
11.4 準極小殘量法 ······························································.163
11.5 穩定雙共軛梯度法 ························································.167
第 12 章 Krylov 法的並行化 ·····················································.173
12.1 稠密矩陣-向量乘法的並行化 ··········································.173
12.2 稀疏矩陣-向量乘法:按頂點劃分·····································.174
12.3 稀疏矩陣-向量乘法:按元素劃分·····································.176
12.3.1 區域分解原理概述 ················································.176
12.3.2 矩陣-向量乘法 ·····················································.177
12.3.3 數據通信 ····························································.178
12.4 點積的並行化······························································.179
12.5 Krylov 法的並行化小結··················································.180
第 13 章 並行預處理方法 ·························································.182
13.1 不完全分解法······························································.182
13.1.1 原理 ··································································.182
13.1.2 並行化 ·······························································.184
13.2 舒爾補法····································································.186
13.2.1 局部最優預處理 ···················································.186
13.2.2 舒爾補法的原理 ···················································.187
13.2.3 舒爾補法的性質 ···················································.189
13.3 代數多重網格······························································.191
13.3.1 基於投影的預處理 ················································.191
13.3.2 粗糙網格的代數構建 ·············································.193
13.3.3 代數多重網格法 ···················································.195
13.4 加性施瓦茨預處理法 ·····················································.196
13.4.1 重疊原理 ····························································.196
13.4.2 乘性方法與加性方法 ·············································.198
13.4.3 加性 Schwarz 預處理法···········································.198
結語························································································.201
