Abstract
This article describes automatic parallelization techniques in the SUIF (Stanford University Intermediate Format) compiler that result in good multiprocessor performance for array-based numerical programs. Parallelizing compilers for multiprocessors face many hurdles. However, SUIF's robust analysis and memory optimization techniques enabled speedups on three fourths of the NAS and SPECfp95 benchmark programs.
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