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<p><b>Abstract</b>—This paper presents the results of an experiment to measure empirically the remaining opportunities for exploiting loop-level parallelism that are missed by the Stanford SUIF compiler, a state-of-the-art automatic parallelization system targeting shared-memory multiprocessor architectures. For the purposes of this experiment, we have developed a run-time parallelization test called the Extended Lazy Privatizing Doall (ELPD) test, which is able to simultaneously test multiple loops in a loop nest. The ELPD test identifies a specific type of parallelism where each iteration of the loop being tested accesses independent data, possibly by making some of the data private to each processor. For 29 programs in three benchmark suites, the ELPD test was executed at run time for each candidate loop left unparallelized by the SUIF compiler to identify which of these loops could safely execute in parallel for the given program input. The results of this experiment point to two main requirements for improving the effectiveness of parallelizing compiler technology: incorporating control flow tests into analysis and extracting low-cost run-time parallelization tests from analysis results.</p>
Parallelizing compilers, shared-memory multiprocessors, data dependence analysis, array privatization, run-time parallelization.
Sungdo Moon, Mary W. Hall, Byoungro So, "Evaluating Automatic Parallelization in SUIF", IEEE Transactions on Parallel & Distributed Systems, vol. 11, no. , pp. 36-49, January 2000, doi:10.1109/71.824639
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