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POSC—a partitioning and optimizing SISAL compiler

Authors:

David CannAuthors Info & Claims

ACM SIGARCH Computer Architecture News, Volume 18, Issue 3b

Pages 148 - 164

https://doi.org/10.1145/255129.255152

Published: 01 June 1990 Publication History

Abstract

Single-assignment languages like SISAL offer parallelism at all levels—among arbitrary operations, conditionals, loop iterations, and function calls. All control and data dependencies are local, and can be easily determined from the program. Various studies of SISAL programs have shown that they contain massive amounts of potential parallelism. There are two major challenges in converting this potential parallelism into real speedup on multiprocessor systems. First, it is important to carefully select the useful parallelism in a SISAL program, so as to obtain good speedup by trading off parallelism with overhead. Second, it is important to do sequential optimizations, so that the sequential components (tasks) of the SISAL program have comparable execution times with sequential languages such as Fortran, Pascal and C. The POSC compiler system described in this paper addresses both issues by integrating previous work on efficient sequential implementation of SISAL programs with previous work on selecting the useful parallelism in a SISAL program. The combined approach is validated by real speedup measurements on a Sequent Balance multiprocessor.

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POSC—a partitioning and optimizing SISAL compiler

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Publication History

Published: 01 June 1990

Published in SIGARCH Volume 18, Issue 3b

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Cited By

Aubrey-Jones TFischer B(2016)Synthesizing MPI Implementations from Functional Data-Parallel ProgramsInternational Journal of Parallel Programming10.1007/s10766-015-0359-444:3(552-573)Online publication date: 1-Jun-2016
https://dl.acm.org/doi/10.1007/s10766-015-0359-4
Armstrong TWozniak JWilde MFoster IDamkroger TDongarra J(2014)Compiler techniques for massively scalable implicit task parallelismProceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis10.1109/SC.2014.30(299-310)Online publication date: 16-Nov-2014
https://dl.acm.org/doi/10.1109/SC.2014.30
Mitschele-Thiel A(2006)The DSPL project — An overviewHigh-Performance Computing and Networking10.1007/BFb0046686(594-599)Online publication date: 2-Feb-2006
https://doi.org/10.1007/BFb0046686
Mitschele-Thiel A(1999)Integrating model-based optimization and program transformation to generate efficient parallel programsJournal of Systems Architecture: the EUROMICRO Journal10.1016/S1383-7621(98)00018-645:6-7(465-482)Online publication date: 1-Jan-1999
https://dl.acm.org/doi/10.1016/S1383-7621%2898%2900018-6
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Denning PDennis J(2010)The resurgence of parallelismCommunications of the ACM10.1145/1743546.174356053:6(30-32)Online publication date: 1-Jun-2010
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Wolfe M(2006)Engineering a data dependence testConcurrency: Practice and Experience10.1002/cpe.43300507065:7(603-622)Online publication date: 25-Oct-2006
https://doi.org/10.1002/cpe.4330050706
Beckmann C(1996)Generating Self-Scheduling Code for Nonloop ParallelismJournal of Parallel and Distributed Computing10.1006/jpdc.1996.016139:2(126-145)Online publication date: 15-Dec-1996
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Böhm ANajjar WShankar BRoh LWolfe AMangione-Smith W(1993)An evaluation of bottom-up and top-down thread generation techniquesProceedings of the 26th annual international symposium on Microarchitecture10.5555/255235.255270(118-127)Online publication date: 1-Dec-1993
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Mitschele-Thiel A(1993)The DSPL programming environmentProceedings of Workshop on Programming Models for Massively Parallel Computers10.1109/PMMP.1993.315556(35-42)Online publication date: 1993
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