PETRA: Performance Evaluation Tool for Modern Parallelizing Compilers.
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| Title: | PETRA: Performance Evaluation Tool for Modern Parallelizing Compilers. |
|---|---|
| Authors: | Mustafa, Dheya1 dmustaf@purdue.edu, Eigenmann, Rudolf1 eigenman@purdue.edu |
| Source: | International Journal of Parallel Programming. Aug2015, Vol. 43 Issue 4, p549-571. 23p. |
| Subjects: | Parallelizing compilers, Performance evaluation, Sequential processing (Computer science), Multicore processors, Program transformation |
| Abstract: | This paper describes PETRA: a portable performance evaluation tool for parallelizing compilers and their individual techniques. Automatic parallelization of sequential programs combined with performance tuning is an important alternative to manual parallelization for exploiting the performance potential of today's multicores. Given the renewed interest in autoparallelization, this paper aims at a comprehensive evaluation, identifying strengths and weaknesses in the underlying techniques. The findings allow engineers to make informed decisions about techniques to include in industrial products and direct researchers to potential improvements. We present an experimental methodology and a fully automated implementation for comprehensively evaluating the effectiveness of parallelizing compilers and their underlying optimization techniques. The methodology is the first to (1) include automatic tuning, (2) measure the performance contributions of individual techniques at multiple optimization levels, and (3) quantify the interactions of compiler optimizations. The results will also help close the gap between research compilers and industrial compilers, which are still far behind. We applied the proposed methodology using PETRA on five modern parallelizing compilers and their tuning capabilities, illustrating several use cases and applications for the evaluation tool. We report speedups, parallel coverage, and the number of parallel loops, using the NAS Benchmarks as a program suite. We found parallelizers to be reasonably successful in about half of the given science-engineering programs. An important finding is also that some techniques substitute each other. Furthermore, we found that automatic tuning can lead to significant additional performance and sometimes matches or outperforms hand-parallelized programs. Advanced versions of some of the techniques identified as most successful in previous generations of compilers are also most important today, while other techniques have risen significantly in impact. Finally, we analyze specific reasons for the measured performance and the potential for improvement of automatic parallelization. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Parallel Programming is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 101894630 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: PETRA: Performance Evaluation Tool for Modern Parallelizing Compilers. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Mustafa%2C+Dheya%22">Mustafa, Dheya</searchLink><relatesTo>1</relatesTo><i> dmustaf@purdue.edu</i><br /><searchLink fieldCode="AR" term="%22Eigenmann%2C+Rudolf%22">Eigenmann, Rudolf</searchLink><relatesTo>1</relatesTo><i> eigenman@purdue.edu</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Parallel+Programming%22">International Journal of Parallel Programming</searchLink>. Aug2015, Vol. 43 Issue 4, p549-571. 23p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Parallelizing+compilers%22">Parallelizing compilers</searchLink><br /><searchLink fieldCode="DE" term="%22Performance+evaluation%22">Performance evaluation</searchLink><br /><searchLink fieldCode="DE" term="%22Sequential+processing+%28Computer+science%29%22">Sequential processing (Computer science)</searchLink><br /><searchLink fieldCode="DE" term="%22Multicore+processors%22">Multicore processors</searchLink><br /><searchLink fieldCode="DE" term="%22Program+transformation%22">Program transformation</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This paper describes PETRA: a portable performance evaluation tool for parallelizing compilers and their individual techniques. Automatic parallelization of sequential programs combined with performance tuning is an important alternative to manual parallelization for exploiting the performance potential of today's multicores. Given the renewed interest in autoparallelization, this paper aims at a comprehensive evaluation, identifying strengths and weaknesses in the underlying techniques. The findings allow engineers to make informed decisions about techniques to include in industrial products and direct researchers to potential improvements. We present an experimental methodology and a fully automated implementation for comprehensively evaluating the effectiveness of parallelizing compilers and their underlying optimization techniques. The methodology is the first to (1) include automatic tuning, (2) measure the performance contributions of individual techniques at multiple optimization levels, and (3) quantify the interactions of compiler optimizations. The results will also help close the gap between research compilers and industrial compilers, which are still far behind. We applied the proposed methodology using PETRA on five modern parallelizing compilers and their tuning capabilities, illustrating several use cases and applications for the evaluation tool. We report speedups, parallel coverage, and the number of parallel loops, using the NAS Benchmarks as a program suite. We found parallelizers to be reasonably successful in about half of the given science-engineering programs. An important finding is also that some techniques substitute each other. Furthermore, we found that automatic tuning can lead to significant additional performance and sometimes matches or outperforms hand-parallelized programs. Advanced versions of some of the techniques identified as most successful in previous generations of compilers are also most important today, while other techniques have risen significantly in impact. Finally, we analyze specific reasons for the measured performance and the potential for improvement of automatic parallelization. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Journal of Parallel Programming is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s10766-014-0307-8 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 23 StartPage: 549 Subjects: – SubjectFull: Parallelizing compilers Type: general – SubjectFull: Performance evaluation Type: general – SubjectFull: Sequential processing (Computer science) Type: general – SubjectFull: Multicore processors Type: general – SubjectFull: Program transformation Type: general Titles: – TitleFull: PETRA: Performance Evaluation Tool for Modern Parallelizing Compilers. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Mustafa, Dheya – PersonEntity: Name: NameFull: Eigenmann, Rudolf IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 08 Text: Aug2015 Type: published Y: 2015 Identifiers: – Type: issn-print Value: 08857458 Numbering: – Type: volume Value: 43 – Type: issue Value: 4 Titles: – TitleFull: International Journal of Parallel Programming Type: main |
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