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Titlebook: Matrix Computations on Systolic-Type Arrays; Jaime H. Moreno,Tomás Lang Book 1992 Springer Science+Business Media New York 1992 algorithm.

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发表于 2025-3-21 18:17:00 | 显示全部楼层 |阅读模式
书目名称Matrix Computations on Systolic-Type Arrays
编辑Jaime H. Moreno,Tomás Lang
视频video
丛书名称The Springer International Series in Engineering and Computer Science
图书封面Titlebook: Matrix Computations on Systolic-Type Arrays;  Jaime H. Moreno,Tomás Lang Book 1992 Springer Science+Business Media New York 1992 algorithm.
描述.Matrix Computations on Systolic-Type Arrays. provides aframework which permits a good understanding of the features andlimitations of processor arrays for matrix algorithms. It describesthe tradeoffs among the characteristics of these systems, such asinternal storage and communication bandwidth, and the impact onoverall performance and cost. A system which allows for the analysisof methods for the design/mapping of matrix algorithms is alsopresented. This method identifies stages in the design/mapping processand the capabilities required at each stage. ..Matrix Computations on Systolic-Type Arrays. provides a muchneeded description of the area of processor arrays for matrixalgorithms and of the methods used to derive those arrays. The ideasdeveloped here reduce the space of solutions in the design/mappingprocess by establishing clear criteria to select among possibleoptions as well as by .a-priori. rejection of alternatives whichare not adequate (but which are considered in other approaches). Theend result is a method which is more specific than other techniquespreviously available (suitable for a class of matrix algorithms) butwhich is more systematic, better defined and more eff
出版日期Book 1992
关键词algorithm; algorithms; communication; processor; tables
版次1
doihttps://doi.org/10.1007/978-1-4615-3610-9
isbn_softcover978-1-4613-6604-1
isbn_ebook978-1-4615-3610-9Series ISSN 0893-3405
issn_series 0893-3405
copyrightSpringer Science+Business Media New York 1992
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发表于 2025-3-21 20:24:52 | 显示全部楼层
Regularization of Matrix Algorithms,e description of an algorithm is successively transformed and made suitable for an implementation. In this chapter, we examine some issues regarding these transformational techniques. Moreover, we focus on the method that is the main topic of this book and introduce the regularization process in it.
发表于 2025-3-22 03:02:37 | 显示全部楼层
Partitioned Realizations Using Cut-and-Pile, process of realizing the multimesh graph of an algorithm with large or variable-size matrices. In this case, a cost-effective structure requires partitioning the algorithm into subproblems that fit an array with fewer cells.
发表于 2025-3-22 07:40:57 | 显示全部楼层
Linear Pseudosystolic Array for Matrix Algorithms,e lower bandwidth requirements and better utilization, and are more suitable to incorporate fault-tolerant features than two-dimensional arrays. Based on these facts, it is of interest to look into the architecture of a class-specific linear computing structure.
发表于 2025-3-22 10:17:27 | 显示全部楼层
Systolic-Type Arrays for Matrix Algorithms,tolic-type arrays, and discuss the relationship among the size of matrices and arrays. Based on the concepts described here, the following chapters will present a method to implement matrix algorithms in systolic-type arrays.
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发表于 2025-3-23 00:41:18 | 显示全部楼层
0893-3405 ssor arrays for matrix algorithms. It describesthe tradeoffs among the characteristics of these systems, such asinternal storage and communication bandwidth, and the impact onoverall performance and cost. A system which allows for the analysisof methods for the design/mapping of matrix algorithms is
发表于 2025-3-23 01:47:26 | 显示全部楼层
Mapping Matrix Algorithms,ication-specific indicates that the processing elements and the interconnection structure are basically well-suited for the class of matrix algorithms. However, since the underlying generality is achieved by having a large variety of features, it becomes necessary to adapt the method to those features.
发表于 2025-3-23 08:48:15 | 显示全部楼层
Summary And Further Research,In this book we have described a method for the implementation of matrix computations on application-specific processor arrays, which includes capabilities to evaluate the implementations. The method is suitable for the realization of . structures as well as for mapping algorithms onto . arrays.
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