Issue No. 12 - December (1996 vol. 29)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/2.546613
M.W. Hall , USC Inf. Scis. Inst., Marina del Rey, CA, USA
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.
mathematics computing, parallelising compilers, multiprocessing systems, performance evaluation, optimising compilers, benchmark programs, multiprocessor performance, SUIF compiler, automatic parallelization techniques, Stanford University Intermediate Format compiler, array-based numerical programs, parallelizing compilers, memory optimization techniques, robust analysis techniques, speedups, NAS, SPECfp95, Parallel processing, Phased arrays, Program processors, Information analysis, Concurrent computing, Privatization, Throughput, Multiprocessing systems, Cache memory, Programming profession
E. Bugnion et al., "Maximizing multiprocessor performance with the SUIF compiler," in Computer, vol. 29, no. , pp. 84,85,86,87,88,89, 1996.