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Excerpt from Synthesizing Linear-Array Algorithms From Nested for Loop Algorithms
We will study linear systolic arrays in this paper, as linear arrays are attractive for their bounded i/o requirements and a simple global clock whose rate is independent of the size of the array. We will consider the important class of algorithms structured as (depth) p nested for loops. Vlsi implementation of such algorithms were studied before, but it is our goal to present a systematic method for transforming them into linear arrays.
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Synthesizing Linear-Array Algorithms From Nested for Loop Algorithms
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Paperback. Condition: New. Print on Demand. This book explores a systematic method for designing and analyzing linear-array algorithms, which are efficiently implemented using systolic arrays. Systolic arrays are integrated circuits containing many simple processors arranged in a regular pattern with localized interconnections. The author presents a method for mapping nested loop algorithms into linear arrays, and demonstrates necessary and sufficient conditions for correct mappings. The conditions encompass several different aspects of the design, including data dependency constraints, preservation of nonsingularity of the mapping, prevention of data contention, and simplicity of processor hardware. Using this methodology, the author investigates linear array implementations of several algorithms, including matrix multiplication, L-U decomposition, and a version of the transitive closure algorithm. Furthermore, they analyze time and storage complexity of linear array implementations, and provide tight bounds on the time complexity of linear array implementations for particular algorithms. This book will be of interest to researchers in computer science and engineering, as well as to practitioners interested in the design and analysis of systolic arrays. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book. print-on-demand item. Seller Inventory # 9781334537820_0
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