Synthesizing nested loop algorithms using nonlinear transformation method

FOR-loops are the main source of parallelism in programs. A nonlinear transformation algorithm for parallelizing the execution of FOR-loop models is proposed. It is shown that by the mapping of nonlinear transformation, iterations of FOR-loops can be executed in a parallel form. The algorithm is use...

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Bibliographic Details
Published inIEEE transactions on parallel and distributed systems Vol. 2; no. 3; pp. 304 - 317
Main Authors Sheu, J.-P., Chang, C.-Y.
Format Journal Article
LanguageEnglish
Published IEEE 01.07.1991
Subjects
Algorithm design and analysis
Councils
Data analysis
Discrete Fourier transforms
High level languages
Matrix decomposition
Parallel processing
Partitioning algorithms
Systolic arrays
Very large scale integration
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ISSN1045-9219
DOI10.1109/71.86106

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Summary:FOR-loops are the main source of parallelism in programs. A nonlinear transformation algorithm for parallelizing the execution of FOR-loop models is proposed. It is shown that by the mapping of nonlinear transformation, iterations of FOR-loops can be executed in a parallel form. The algorithm is useful in exploiting the parallelism of FOR-loops with one or more partitions on the innermost loop. Algorithms to partition and map the nested FOR-loops onto fixed size systolic arrays are discussed. Based on the time and space mapping schemes, all the iterations of FOR-loops can be correctly executed on the array processors in a parallel form.< >
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ISSN:1045-9219
DOI:10.1109/71.86106