Exploring the structure of the space of compilation sequences using randomized search algorithms.
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| Title: | Exploring the structure of the space of compilation sequences using randomized search algorithms. |
|---|---|
| Authors: | Cooper, Keith1, Grosul, Alexander1, Harvey, Timothy1, Reeves, Steve1, Subramanian, Devika1, Torczon, Linda1, Waterman, Todd1 |
| Source: | Journal of Supercomputing. May2006, Vol. 36 Issue 2, p135-151. 17p. 7 Charts, 6 Graphs. |
| Subjects: | Optimizing compilers, Compilers (Computer programs), Systems software, Supercomputers, Computers, High performance computing, Parallel processing, Computer programming, Algorithms |
| Abstract: | Modern optimizing compilers apply a fixed sequence of optimizations, which we call a compilation sequence, to each program that they compile. These compilers let the user modify their behavior in a small number of specified ways, using command-line flags (e.g.,-O1,-O2,...). For five years, we have been working with compilers that automatically select an appropriate compilation sequence for each input program. These adaptive compilers discover a good compilation sequence tailored to the input program, the target machine, and a user-chosen objective function. We have shown, as have others, that program-specific sequences can produce better results than any single universal sequence [1, 7, 10, 21, 23] Our adaptive compiler looks for compilation sequences in a large and complex search space. Its typical compilation sequence includes 10 passes (with possible repeats) chosen from the 16 available—there are 1610 or [1,099,511,627,776] such sequences. To learn about the properties of such spaces, we have studied subspaces that consist of 10 passes drawn from a set of 5 (510 or 9,765,625 sequences). These 10-of-5 subspaces are small enough that we can analyze them thoroughly but large enough to reflect important properties of the full spaces.This paper reports, in detail, on our analysis of several of these subspaces and on the consequences of those observed properties for the design of search algorithms. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Supercomputing 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: 20791701 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Exploring the structure of the space of compilation sequences using randomized search algorithms. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Cooper%2C+Keith%22">Cooper, Keith</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Grosul%2C+Alexander%22">Grosul, Alexander</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Harvey%2C+Timothy%22">Harvey, Timothy</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Reeves%2C+Steve%22">Reeves, Steve</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Subramanian%2C+Devika%22">Subramanian, Devika</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Torczon%2C+Linda%22">Torczon, Linda</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Waterman%2C+Todd%22">Waterman, Todd</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Supercomputing%22">Journal of Supercomputing</searchLink>. May2006, Vol. 36 Issue 2, p135-151. 17p. 7 Charts, 6 Graphs. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Optimizing+compilers%22">Optimizing compilers</searchLink><br /><searchLink fieldCode="DE" term="%22Compilers+%28Computer+programs%29%22">Compilers (Computer programs)</searchLink><br /><searchLink fieldCode="DE" term="%22Systems+software%22">Systems software</searchLink><br /><searchLink fieldCode="DE" term="%22Supercomputers%22">Supercomputers</searchLink><br /><searchLink fieldCode="DE" term="%22Computers%22">Computers</searchLink><br /><searchLink fieldCode="DE" term="%22High+performance+computing%22">High performance computing</searchLink><br /><searchLink fieldCode="DE" term="%22Parallel+processing%22">Parallel processing</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+programming%22">Computer programming</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Modern optimizing compilers apply a fixed sequence of optimizations, which we call a compilation sequence, to each program that they compile. These compilers let the user modify their behavior in a small number of specified ways, using command-line flags (e.g.,-O1,-O2,...). For five years, we have been working with compilers that automatically select an appropriate compilation sequence for each input program. These adaptive compilers discover a good compilation sequence tailored to the input program, the target machine, and a user-chosen objective function. We have shown, as have others, that program-specific sequences can produce better results than any single universal sequence [1, 7, 10, 21, 23] Our adaptive compiler looks for compilation sequences in a large and complex search space. Its typical compilation sequence includes 10 passes (with possible repeats) chosen from the 16 available—there are 1610 or [1,099,511,627,776] such sequences. To learn about the properties of such spaces, we have studied subspaces that consist of 10 passes drawn from a set of 5 (510 or 9,765,625 sequences). These 10-of-5 subspaces are small enough that we can analyze them thoroughly but large enough to reflect important properties of the full spaces.This paper reports, in detail, on our analysis of several of these subspaces and on the consequences of those observed properties for the design of search algorithms. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Supercomputing 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/s11227-006-7954-5 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 17 StartPage: 135 Subjects: – SubjectFull: Optimizing compilers Type: general – SubjectFull: Compilers (Computer programs) Type: general – SubjectFull: Systems software Type: general – SubjectFull: Supercomputers Type: general – SubjectFull: Computers Type: general – SubjectFull: High performance computing Type: general – SubjectFull: Parallel processing Type: general – SubjectFull: Computer programming Type: general – SubjectFull: Algorithms Type: general Titles: – TitleFull: Exploring the structure of the space of compilation sequences using randomized search algorithms. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Cooper, Keith – PersonEntity: Name: NameFull: Grosul, Alexander – PersonEntity: Name: NameFull: Harvey, Timothy – PersonEntity: Name: NameFull: Reeves, Steve – PersonEntity: Name: NameFull: Subramanian, Devika – PersonEntity: Name: NameFull: Torczon, Linda – PersonEntity: Name: NameFull: Waterman, Todd IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 05 Text: May2006 Type: published Y: 2006 Identifiers: – Type: issn-print Value: 09208542 Numbering: – Type: volume Value: 36 – Type: issue Value: 2 Titles: – TitleFull: Journal of Supercomputing Type: main |
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