高性能计算机上的数值线性代数（英文影印版）
出版时间：2011年版
内容简介
　　the purpose of this book is to unify anddocument in one place many of the techniques and much of thecurrent understanding about solving systems of linear equations onvector and parallel computers. this book is not a textbook，but itis meant to provide a fast entrance to the world of vector andparallel processing for these linear algebra applications. weintend this book to be used by three groups of readers： graduatestudents， researchers working in computational science， andnumerical analysts. as such， we hope this book can serve both as areference and as a supplement to a teaching text on aspects ofscientific computation. the book is divided into five major parts： （1） introduction toterms and concepts， including an overview of the state of the artfor high-performance computers and a discussion of performanceevaluation （chapters 1-4）; （2） direct solution of dense matrixproblems （chapter 5）; （3） direct solution of sparse systems ofequations （chapter 6）; （4） iterative solution of sparse systems ofequations （chapters 7-9）; and （5） iterative solution of sparseeigenvalue problems （chapters 10-11）. any book that attempts tocover these topics must necessarily be somewhat out of date beforeit appears， because the area is in a state of flux. we havepurposely avoided highly detailed descriptions of popular machinesand have tried instead to focus on concepts as much as possible;nevertheless， to make the description more concrete， we do point tospecific computers.
目录
about the authors
preface
introduction
1 high-performance computing
　1.1 trends in computer design
　1.2 traditional computers and their limitations
　1.3 parallelism within a single processor
　　1.3.1 multiple functional units
　　1.3.2 pipelining
　　1.3.3 overlapping
　　1.3.4 risc
　　1.3.5 vliw
　　1.3.6 vector instructions
　　1.3.7 chaining
　　1.3.8 memory-to-memory and register-to-registerorganizations
　　1.3.9 register set
　　1.3.10 stripmining
　　1.3.11 reconfigurable vector registers
　　1.3.12 memory organization
　1.4 data organization
　　1.4.1 main memory
　　1.4.2 cache
　　1.4.3 local memory
　1.5 memory management
　1.6 parallelism through multiple pipes or multipleprocessors
　1.7 message passing
　1.8 virtual shared memory
　　1.8.1 routing
　1.9 interconnection topology
　　1.9.1 crossbar switch
　　1.9.2 timeshared bus
　　1.9.3 ring connection
　　1.9.4 mesh connection
　　1.9.5 hypercube
　　1.9.6 multi-staged network
　1.10 programming techniques
　1.11 trends: network-based computing
2 overview of current high-performance computers
　2.1 supercomputers
　2.2 risc-based processors
　2.3 parallel processors
　……
3 implementation details and overhead
4 performance: analysis, modeling, and measurements
5 building blocks in linear algebra
6 direct solution of sparse linear systems
7 krylov subspaces: projection
8 iterative methods for linear systems
9 preconditioning and parallel preconditioning
10 linear eigenvalue problems ax=λχ
11 the generalized eigenproblem
bibliography
index