An approach for code generation in the Sparse Polyhedral Framework

Persistent Link:
http://hdl.handle.net/10150/615800
Title:
An approach for code generation in the Sparse Polyhedral Framework
Author:
Strout, Michelle Mills; LaMielle, Alan ( 0000-0002-0217-5918 ) ; Carter, Larry; Ferrante, Jeanne; Kreaseck, Barbara; Olschanowsky, Catherine
Affiliation:
Computer Science Department, University of Arizona
Issue Date:
2016-04
Publisher:
ELSEVIER SCIENCE BV
Citation:
An approach for code generation in the Sparse Polyhedral Framework 2016, 53:32 Parallel Computing
Journal:
Parallel Computing
Rights:
Copyright © 2016 Elsevier B.V. All rights reserved.
Collection Information:
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
Abstract:
Applications that manipulate sparse data structures contain memory reference patterns that are unknown at compile time due to indirect accesses such as A[B[i]]. To exploit parallelism and improve locality in such applications, prior work has developed a number of Run-Time Reordering Transformations (RTRTs). This paper presents the Sparse Polyhedral Framework (SPF) for specifying RTRTs and compositions thereof and algorithms for automatically generating efficient inspector and executor code to implement such transformations. Experimental results indicate that the performance of automatically generated inspectors and executors competes with the performance of hand-written ones when further optimization is done.
Note:
Available online 4 March 2016. 24 month embargo.
ISSN:
0167-8191
DOI:
10.1016/j.parco.2016.02.004
Keywords:
Inspector/executor strategies; Runtime reordering transformations; Sparse Polyhedral Framework
Version:
Final accepted manuscript
Sponsors:
We thank Jon Roelofs for his implementation of the IEGenCC tool, which converts C programs into the specification format IEGen expects as input. We thank Christopher Krieger, Andrew Stone, Tomofumi Yuki, and anonymous reviewers for their careful reading and suggestions. This work was sponsored by NSF CAREER Grant CCF-0746693, DOE Early Career Grant DE-SC3956, the CSCAPES Institute DOE Grant 7F-00323, and the CACHE project DOE Grant DE-SC04030.
Additional Links:
http://linkinghub.elsevier.com/retrieve/pii/S0167819116000557

Full metadata record

DC FieldValue Language
dc.contributor.authorStrout, Michelle Millsen
dc.contributor.authorLaMielle, Alanen
dc.contributor.authorCarter, Larryen
dc.contributor.authorFerrante, Jeanneen
dc.contributor.authorKreaseck, Barbaraen
dc.contributor.authorOlschanowsky, Catherineen
dc.date.accessioned2016-07-08T01:06:34Z-
dc.date.available2016-07-08T01:06:34Z-
dc.date.issued2016-04-
dc.identifier.citationAn approach for code generation in the Sparse Polyhedral Framework 2016, 53:32 Parallel Computingen
dc.identifier.issn0167-8191-
dc.identifier.doi10.1016/j.parco.2016.02.004-
dc.identifier.urihttp://hdl.handle.net/10150/615800-
dc.description.abstractApplications that manipulate sparse data structures contain memory reference patterns that are unknown at compile time due to indirect accesses such as A[B[i]]. To exploit parallelism and improve locality in such applications, prior work has developed a number of Run-Time Reordering Transformations (RTRTs). This paper presents the Sparse Polyhedral Framework (SPF) for specifying RTRTs and compositions thereof and algorithms for automatically generating efficient inspector and executor code to implement such transformations. Experimental results indicate that the performance of automatically generated inspectors and executors competes with the performance of hand-written ones when further optimization is done.en
dc.description.sponsorshipWe thank Jon Roelofs for his implementation of the IEGenCC tool, which converts C programs into the specification format IEGen expects as input. We thank Christopher Krieger, Andrew Stone, Tomofumi Yuki, and anonymous reviewers for their careful reading and suggestions. This work was sponsored by NSF CAREER Grant CCF-0746693, DOE Early Career Grant DE-SC3956, the CSCAPES Institute DOE Grant 7F-00323, and the CACHE project DOE Grant DE-SC04030.en
dc.language.isoenen
dc.publisherELSEVIER SCIENCE BVen
dc.relation.urlhttp://linkinghub.elsevier.com/retrieve/pii/S0167819116000557en
dc.rightsCopyright © 2016 Elsevier B.V. All rights reserved.en
dc.subjectInspector/executor strategiesen
dc.subjectRuntime reordering transformationsen
dc.subjectSparse Polyhedral Frameworken
dc.titleAn approach for code generation in the Sparse Polyhedral Frameworken
dc.typeArticleen
dc.contributor.departmentComputer Science Department, University of Arizonaen
dc.identifier.journalParallel Computingen
dc.description.noteAvailable online 4 March 2016. 24 month embargo.en
dc.description.collectioninformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.en
dc.eprint.versionFinal accepted manuscripten
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