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Communication optimization and code generation for distributed memory machines

Authors:

Saman P. Amarasinghe,

Monica S. LamAuthors Info & Claims

ACM SIGPLAN Notices, Volume 28, Issue 6

Pages 126 - 138

https://doi.org/10.1145/173262.155102

Published: 01 June 1993 Publication History

Abstract

This paper presents several algorithms to solve code generation and optimization problems specific to machines with distributed address spaces. Given a description of how the computation is to be partitioned across the processors in a machine, our algorithms produce an SPMD (single program multiple data) program to be run on each processor. Our compiler generated the necessary receive and send instructions, optimizes the communication by eliminating redundant communication and aggregating small messages into large messages, allocates space locally on each processor, and translates global data addresses to local addresses.

Our techniques are based on an exact data-flow analysis on individual array element accesses. Unlike data dependence analysis, this analysis determines if two dynamic instances refer to the same value, and not just to the same location. Using this information, our compiler can handle more flexible data decompositions and find more opportunities for communication optimization than systems based on data dependence analysis.

Our technique is based on a uniform framework, where data decompositions, computation decompositions and the data flow information are all represented as systems of linear inequalities. We show that the problems of communication code generation, local memory management, message aggregation and redundant data communication elimination can all be solved by projecting polyhedra represented by sets of inequalities onto lower dimensional spaces.

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Cited By

Narmour LYuki TRajopadhye S(2025)Maximal Simplification of Polyhedral ReductionsProceedings of the ACM on Programming Languages10.1145/37048399:POPL(67-94)Online publication date: 9-Jan-2025
https://doi.org/10.1145/3704839
Willis BShrivastava AMack JDave SChakrabarti CBrunhaver J(2024)Cyclebite: Extracting Task Graphs From Unstructured Compute-ProgramsIEEE Transactions on Computers10.1109/TC.2023.332750473:1(221-234)Online publication date: 1-Jan-2024
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Yadav RAiken AKjolstad FJhala RDillig I(2022)DISTAL: the distributed tensor algebra compilerProceedings of the 43rd ACM SIGPLAN International Conference on Programming Language Design and Implementation10.1145/3519939.3523437(286-300)Online publication date: 9-Jun-2022
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Communication optimization and code generation for distributed memory machines

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Information & Contributors

Information

Published In

cover image ACM SIGPLAN Notices

ACM SIGPLAN Notices Volume 28, Issue 6

June 1993

313 pages

ISSN:0362-1340

EISSN:1558-1160

DOI:10.1145/173262

Editor:
Richard Wexelblat
IDA/CSED, Alexandria, VA

Issue’s Table of Contents

PLDI '93: Proceedings of the ACM SIGPLAN 1993 conference on Programming language design and implementation
August 1993
313 pages
ISBN:0897915984
DOI:10.1145/155090
Editor:
Robert Cartwright
Rice Univ., Houston, TX

Copyright © 1993 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 June 1993

Published in SIGPLAN Volume 28, Issue 6

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Cited By

Narmour LYuki TRajopadhye S(2025)Maximal Simplification of Polyhedral ReductionsProceedings of the ACM on Programming Languages10.1145/37048399:POPL(67-94)Online publication date: 9-Jan-2025
https://doi.org/10.1145/3704839
Willis BShrivastava AMack JDave SChakrabarti CBrunhaver J(2024)Cyclebite: Extracting Task Graphs From Unstructured Compute-ProgramsIEEE Transactions on Computers10.1109/TC.2023.332750473:1(221-234)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TC.2023.3327504
Yadav RAiken AKjolstad FJhala RDillig I(2022)DISTAL: the distributed tensor algebra compilerProceedings of the 43rd ACM SIGPLAN International Conference on Programming Language Design and Implementation10.1145/3519939.3523437(286-300)Online publication date: 9-Jun-2022
https://dl.acm.org/doi/10.1145/3519939.3523437
Baghdadi RRay JRomdhane MDel Sozzo EAkkas AZhang YSuriana PKamil SAmarasinghe SKandemir MJimborean AMoseley T(2019)Tiramisu: a polyhedral compiler for expressing fast and portable codeProceedings of the 2019 IEEE/ACM International Symposium on Code Generation and Optimization10.5555/3314872.3314896(193-205)Online publication date: 16-Feb-2019
https://dl.acm.org/doi/10.5555/3314872.3314896
Baghdadi RRay JRomdhane MSozzo EAkkas AZhang YSuriana PKamil SAmarasinghe S(2019)Tiramisu: A Polyhedral Compiler for Expressing Fast and Portable Code2019 IEEE/ACM International Symposium on Code Generation and Optimization (CGO)10.1109/CGO.2019.8661197(193-205)Online publication date: Feb-2019
https://doi.org/10.1109/CGO.2019.8661197
Plebani PSalnitri MVitali M(2018)Fog Computing and Data as a Service: A Goal-Based Modeling Approach to Enable Effective Data MovementsAdvanced Information Systems Engineering10.1007/978-3-319-91563-0_13(203-219)Online publication date: 11-Jun-2018
https://dl.acm.org/doi/10.1007/978-3-319-91563-0_13
Moreton-Fernandez AGonzalez-Escribano ALlanos D(2015)On the run-time cost of distributed-memory communications generated using the polyhedral model2015 International Conference on High Performance Computing & Simulation (HPCS)10.1109/HPCSim.2015.7237034(151-159)Online publication date: Jul-2015
https://doi.org/10.1109/HPCSim.2015.7237034
Ancourt CPetrisor TIrigoin FLenormand E(2013)Automatic Generation of Communications for Redundant Multi-dimensional Data Parallel Redistributions2013 IEEE 10th International Conference on High Performance Computing and Communications & 2013 IEEE International Conference on Embedded and Ubiquitous Computing10.1109/HPCC.and.EUC.2013.116(800-811)Online publication date: Nov-2013
https://doi.org/10.1109/HPCC.and.EUC.2013.116
Choudhary AKandemir M(2010)Compilation for Distributed Memory ArchitecturesThe Compiler Design Handbook10.1201/9781420040579.ch11Online publication date: 7-Mar-2010
https://doi.org/10.1201/9781420040579.ch11
Kandemir MZhang YMuralidhara SOzturk ONarayanan SHenkel JParameswaran S(2009)Slicing based code parallelization for minimizing inter-processor communicationProceedings of the 2009 international conference on Compilers, architecture, and synthesis for embedded systems10.1145/1629395.1629409(87-96)Online publication date: 11-Oct-2009
https://dl.acm.org/doi/10.1145/1629395.1629409
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