Automatic and interactive parallelization
Automatic and interactive parallelization
Compile-time support for efficient data race detection in shared-memory parallel programs
PADD '93 Proceedings of the 1993 ACM/ONR workshop on Parallel and distributed debugging
PLDI '95 Proceedings of the ACM SIGPLAN 1995 conference on Programming language design and implementation
Symbolic array dataflow analysis for array privatization and program parallelization
Supercomputing '95 Proceedings of the 1995 ACM/IEEE conference on Supercomputing
Detecting coarse-grain parallelism using an interprocedural parallelizing compiler
Supercomputing '95 Proceedings of the 1995 ACM/IEEE conference on Supercomputing
Automatic array privatization and demand-driven symbolic analysis
Automatic array privatization and demand-driven symbolic analysis
Experience with efficient array data flow analysis for array privatization
PPOPP '97 Proceedings of the sixth ACM SIGPLAN symposium on Principles and practice of parallel programming
Parallelizing compiler techniques based on linear inequalities
Parallelizing compiler techniques based on linear inequalities
On the Automatic Parallelization of the Perfect Benchmarks®
IEEE Transactions on Parallel and Distributed Systems
Simplification of array access patterns for compiler optimizations
PLDI '98 Proceedings of the ACM SIGPLAN 1998 conference on Programming language design and implementation
Predicated array data-flow analysis for run-time parallelization
ICS '98 Proceedings of the 12th international conference on Supercomputing
Measuring the effectiveness of automatic parallelization in SUIF
ICS '98 Proceedings of the 12th international conference on Supercomputing
Constraint-based array dependence analysis
ACM Transactions on Programming Languages and Systems (TOPLAS)
SUIF Explorer: an interactive and interprocedural parallelizer
Proceedings of the seventh ACM SIGPLAN symposium on Principles and practice of parallel programming
Evaluation of predicated array data-flow analysis for automatic parallelization
Proceedings of the seventh ACM SIGPLAN symposium on Principles and practice of parallel programming
Parallel Programming with Polaris
Computer
Performance Analysis of Parallelizing Compilers on the Perfect Benchmarks Programs
IEEE Transactions on Parallel and Distributed Systems
Runtime Support and Compilation Methods for User-Specified Irregular Data Distributions
IEEE Transactions on Parallel and Distributed Systems
Proceedings of the 6th International Workshop on Languages and Compilers for Parallel Computing
Interprocedural Analysis for Parallelization
LCPC '95 Proceedings of the 8th International Workshop on Languages and Compilers for Parallel Computing
Symbolic analysis techniques for effective automatic parallelization
Symbolic analysis techniques for effective automatic parallelization
Practical techniques to augment dependence analysis in the presence of symbolic terms
Practical techniques to augment dependence analysis in the presence of symbolic terms
Proceedings of the 14th international conference on Architectural support for programming languages and operating systems
Paragon: collaborative speculative loop execution on GPU and CPU
Proceedings of the 5th Annual Workshop on General Purpose Processing with Graphics Processing Units
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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.