Exploiting Vector Instructions with Generalized Stream Fusion.
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| Title: | Exploiting Vector Instructions with Generalized Stream Fusion. |
|---|---|
| Authors: | Mainland, Geoffrey1 mainland@drexel.edu, Leshchinskiy, Roman rleshchinskiy@gmail.com, Peyton Jones, Simon2 simonpj@microsoft.com |
| Source: | Communications of the ACM. May2017, Vol. 60 Issue 5, p83-91. 9p. 2 Charts, 2 Graphs. |
| Subjects: | Haskell (Computer program language), Computer programming, Array processing, Unicode (Computer character set), Vector processing (Computer science), SIMD (Computer architecture) |
| Abstract: | Ideally, a program written as a composition of concise, self-contained components should perform as well as the equivalent hand-written version where the functionality of what was many components has been manually combined into a monolithic implementation. That is, programmers should not have to sacrifice code clarity or good software engineering practices to obtain performance--we want compositionality without a performance penalty. This work shows how to attain this goal for high-level Haskell in the domain of sequence-processing functions, which includes applications such as array processing. Prior work on stream fusion3 shows how to automatically transform some high-level sequence-processing functions into efficient implementations. It has been used to great effect in Haskell libraries for manipulating byte arrays, Unicode text, and unboxed vectors. However some operations, like vector append, do not perform well within the stream fusion framework. Others, like SIMD computation using the SSE and AVX instructions available on modern x86 chips, do not seem to fit in the stream fusion framework at all. We describe generalized stream fusion, which solves these issues through a careful choice of stream representation. Benchmarks show that high-level Haskell code written using our compiler and libraries can produce code that is faster than both compiler- and hand-vectorized C. [ABSTRACT FROM AUTHOR] |
| Copyright of Communications of the ACM is the property of Association for Computing Machinery 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 |
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| Header | DbId: egs DbLabel: Engineering Source An: 122701128 AccessLevel: 6 PubType: Periodical PubTypeId: serialPeriodical PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Exploiting Vector Instructions with Generalized Stream Fusion. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Mainland%2C+Geoffrey%22">Mainland, Geoffrey</searchLink><relatesTo>1</relatesTo><i> mainland@drexel.edu</i><br /><searchLink fieldCode="AR" term="%22Leshchinskiy%2C+Roman%22">Leshchinskiy, Roman</searchLink><i> rleshchinskiy@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Peyton+Jones%2C+Simon%22">Peyton Jones, Simon</searchLink><relatesTo>2</relatesTo><i> simonpj@microsoft.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Communications+of+the+ACM%22">Communications of the ACM</searchLink>. May2017, Vol. 60 Issue 5, p83-91. 9p. 2 Charts, 2 Graphs. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Haskell+%28Computer+program+language%29%22">Haskell (Computer program language)</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+programming%22">Computer programming</searchLink><br /><searchLink fieldCode="DE" term="%22Array+processing%22">Array processing</searchLink><br /><searchLink fieldCode="DE" term="%22Unicode+%28Computer+character+set%29%22">Unicode (Computer character set)</searchLink><br /><searchLink fieldCode="DE" term="%22Vector+processing+%28Computer+science%29%22">Vector processing (Computer science)</searchLink><br /><searchLink fieldCode="DE" term="%22SIMD+%28Computer+architecture%29%22">SIMD (Computer architecture)</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Ideally, a program written as a composition of concise, self-contained components should perform as well as the equivalent hand-written version where the functionality of what was many components has been manually combined into a monolithic implementation. That is, programmers should not have to sacrifice code clarity or good software engineering practices to obtain performance--we want compositionality without a performance penalty. This work shows how to attain this goal for high-level Haskell in the domain of sequence-processing functions, which includes applications such as array processing. Prior work on stream fusion3 shows how to automatically transform some high-level sequence-processing functions into efficient implementations. It has been used to great effect in Haskell libraries for manipulating byte arrays, Unicode text, and unboxed vectors. However some operations, like vector append, do not perform well within the stream fusion framework. Others, like SIMD computation using the SSE and AVX instructions available on modern x86 chips, do not seem to fit in the stream fusion framework at all. We describe generalized stream fusion, which solves these issues through a careful choice of stream representation. Benchmarks show that high-level Haskell code written using our compiler and libraries can produce code that is faster than both compiler- and hand-vectorized C. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Communications of the ACM is the property of Association for Computing Machinery 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: 10.1145/3060597 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 9 StartPage: 83 Subjects: – SubjectFull: Haskell (Computer program language) Type: general – SubjectFull: Computer programming Type: general – SubjectFull: Array processing Type: general – SubjectFull: Unicode (Computer character set) Type: general – SubjectFull: Vector processing (Computer science) Type: general – SubjectFull: SIMD (Computer architecture) Type: general Titles: – TitleFull: Exploiting Vector Instructions with Generalized Stream Fusion. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Mainland, Geoffrey – PersonEntity: Name: NameFull: Leshchinskiy, Roman – PersonEntity: Name: NameFull: Peyton Jones, Simon IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 05 Text: May2017 Type: published Y: 2017 Identifiers: – Type: issn-print Value: 00010782 Numbering: – Type: volume Value: 60 – Type: issue Value: 5 Titles: – TitleFull: Communications of the ACM Type: main |
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