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Array expansion

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P. FeautrierAuthors Info & Claims

ICS '88: Proceedings of the 2nd international conference on Supercomputing

Pages 429 - 441

https://doi.org/10.1145/55364.55406

Published: 01 June 1988 Publication History

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Abstract

A common problem in restructuring programs for vector or parallel execution is the suppression of false dependencies which originate in the reuse of the same memory cell for unrelated values. The method is simple and well understood in the case of scalars. This paper gives the general solution for the case of arrays. The expansion is done in two steps: first, modify all definitions of the offending array in order to obtain the single assignment property. Then, reconstruct the original data flow by adapting all uses of the array. This is done with the help of a new algorithm for solving parametric integer programs. The technique is quite general and may be used for other purposes, including program checking, collecting array predicates, etc…

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Mezdour LKadem KMerouani MHaichour AAmarasinghe SBaghdadi RVerbrugge CLhoták OShen X(2023)A Deep Learning Model for Loop InterchangeProceedings of the 32nd ACM SIGPLAN International Conference on Compiler Construction10.1145/3578360.3580257(50-60)Online publication date: 17-Feb-2023
https://dl.acm.org/doi/10.1145/3578360.3580257
Quislant RFernandez IGutierrez EPlata O(2023)Time series analysis acceleration with advanced vectorization extensionsThe Journal of Supercomputing10.1007/s11227-023-05060-279:9(10178-10207)Online publication date: 2-Feb-2023
https://doi.org/10.1007/s11227-023-05060-2
Herholz PTang XSchneider TKamil SPanozzo DSorkine-Hornung O(2022)Sparsity-Specific Code Optimization using Expression TreesACM Transactions on Graphics10.1145/352048441:5(1-19)Online publication date: 13-May-2022
https://dl.acm.org/doi/10.1145/3520484
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A common problem in restructuring programs for vector or parallel execution is the suppression of false dependencies which originate in the reuse of the same memory cell for unrelated values. The method is simple and well understood in the case of ...
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ICS '88: Proceedings of the 2nd international conference on Supercomputing

June 1988

679 pages

ISBN:0897912721

DOI:10.1145/55364

Editor:
J. Lenfant
Rennes

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

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Published: 01 June 1988

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Mezdour LKadem KMerouani MHaichour AAmarasinghe SBaghdadi RVerbrugge CLhoták OShen X(2023)A Deep Learning Model for Loop InterchangeProceedings of the 32nd ACM SIGPLAN International Conference on Compiler Construction10.1145/3578360.3580257(50-60)Online publication date: 17-Feb-2023
https://dl.acm.org/doi/10.1145/3578360.3580257
Quislant RFernandez IGutierrez EPlata O(2023)Time series analysis acceleration with advanced vectorization extensionsThe Journal of Supercomputing10.1007/s11227-023-05060-279:9(10178-10207)Online publication date: 2-Feb-2023
https://doi.org/10.1007/s11227-023-05060-2
Herholz PTang XSchneider TKamil SPanozzo DSorkine-Hornung O(2022)Sparsity-Specific Code Optimization using Expression TreesACM Transactions on Graphics10.1145/352048441:5(1-19)Online publication date: 13-May-2022
https://dl.acm.org/doi/10.1145/3520484
Quislant RFernandez ISerralvo EGutierrez EPlata O(2022)Exploiting Vector Extennsions to Accelerate Time Series Analysis2022 30th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP)10.1109/PDP55904.2022.00017(55-62)Online publication date: Mar-2022
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Moses WChelini LZhao RZinenko O(2021)Polygeist: Raising C to Polyhedral MLIR2021 30th International Conference on Parallel Architectures and Compilation Techniques (PACT)10.1109/PACT52795.2021.00011(45-59)Online publication date: Sep-2021
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Pailoor SWang XShacham HDillig I(2020)Automated policy synthesis for system call sandboxingProceedings of the ACM on Programming Languages10.1145/34282034:OOPSLA(1-26)Online publication date: 13-Nov-2020
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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
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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
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Fernandez IVillegas AGutierrez EPlata O(2019)Accelerating time series motif discovery in the Intel Xeon Phi KNL processorThe Journal of Supercomputing10.1007/s11227-019-02923-5Online publication date: 10-Jun-2019
https://doi.org/10.1007/s11227-019-02923-5
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L-shaped coprime array structures for DOA estimation

Array pattern optimization for a steerable circular isotropic antenna array using the firefly algorithm

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Array expansion

L-shaped coprime array structures for DOA estimation

Array pattern optimization for a steerable circular isotropic antenna array using the firefly algorithm

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