Partitioning and Mapping Algorithms into Fixed Size Systolic Arrays
IEEE Transactions on Computers
Systolic array synthesis by static analysis of program dependencies
Volume I: Parallel architectures on PARLE: Parallel Architectures and Languages Europe
Deriving fully efficient systolic arrays by quasi-linear allocation functions
PARLE '91 Proceedings on Parallel architectures and languages Europe : volume I: parallel architectures and algorithms: volume I: parallel architectures and algorithms
Time Optimal Linear Schedules for Algorithms with Uniform Dependencies
IEEE Transactions on Computers
Mapping matrix multiplication algorithm onto fault-tolerant systolic array
Computers & Mathematics with Applications
Reducing the number of processors elements in systolic arrays for matrix multiplication
SEPADS'12/EDUCATION'12 Proceedings of the 11th WSEAS international conference on Software Engineering, Parallel and Distributed Systems, and proceedings of the 9th WSEAS international conference on Engineering Education
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The space-time mapping of the dependency matrix of an algorithm may be used to study proposed systolic array implementations. In this paper we consider nested loop structures and use the space-time mapping approach to examine six objective functions, processor pipelining rate, computation time, throughput, number of processing elements, geometric area and space utilization. An elementary expression for each of these objective functions is derived which depends only on the space-time transformation and the size of loops. Moreover, several necessary and sufficient conditions for optimizing individual objective function are provided.