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An evaluation of coarse grain dataflow code generation strategies

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4 Author(s)
Bohm, W. ; Dept. of Comput. Sci., Colorado State Univ., Fort Collins, CO, USA ; Najjar, W. ; Shankar, B. ; Roh, L.

Presents top-down and bottom-up methods for generating coarse grain dataflow or multithreaded code, and evaluates their effectiveness. The top-down technique generates clusters directly from the intermediate data dependence graph used for compiler optimizations. Bottom-up techniques coalesce fine-grain dataflow code into clusters. We measure the resulting number of clusters executed, cluster size, and number of inputs per cluster, for Livermore and Purdue benchmarks. The top-down method executes less clusters and instructions, but incurs a higher number of matches per cluster, which exemplifies the need for efficient matching of more than two inputs per cluster.

Published in:

Programming Models for Massively Parallel Computers, 1993. Proceedings

Date of Conference:

20-20 Sept. 1993