Multi-dimensional Homomorphisms and Their Implementation in OpenCL.
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| Title: | Multi-dimensional Homomorphisms and Their Implementation in OpenCL. |
|---|---|
| Authors: | Rasch, Ari1 a.rasch@uni-muenster.de, Gorlatch, Sergei1 gorlatch@uni-muenster.de |
| Source: | International Journal of Parallel Programming. Feb2018, Vol. 46 Issue 1, p101-119. 19p. |
| Subjects: | OpenCL (Computer program language), Homomorphisms, Graphics processing units, Central processing units, Parallel programming |
| Abstract: | Homomorphisms (traditionally defined on lists) are functions that can be parallelized by the divide-and-conquer paradigm. In this paper, we introduce an extension of the traditional homomorphism concept- multi-dimensional homomorphisms (MDHs)-which capture parallelism on multi-dimensional arrays. We propose md_hom-a new parallel pattern (a.k.a. algorithmic skeleton), based on the MDH concept, to simplify parallel programming for a broad class of applications. The md_hom pattern is general enough to subsume common parallel patterns such as map and reduce, and also more complex functions built by composing and nesting several patterns. We present a generic implementation schema for md_hom in form of an efficient, correct-by-construction OpenCL pseudocode that targets various parallel architectures such as multi-core CPU and graphics processing unit (GPU). We develop our pseudocode schema as parametrized in tuning parameters: these allow to optimize the code for different devices and input sizes by performing an automated search on the parameter space. We evaluate the schematically generated, executable OpenCL code using the example of general matrix-vector multiplication (GEMV)-an important linear algebra routine which has gained more attention recently due to its use in the application area of deep learning-on two parallel architectures-Intel CPU and NVIDIA GPU. Our performance results are competitive and in some cases even better than the hand-tuned GEMV implementations provided by the state-of-the-art libraries Intel MKL and NVIDIA cuBLAS, as well as the auto-tunable OpenCL BLAS library CLBlast. [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 |
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| Header | DbId: egs DbLabel: Engineering Source An: 127064438 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Multi-dimensional Homomorphisms and Their Implementation in OpenCL. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Rasch%2C+Ari%22">Rasch, Ari</searchLink><relatesTo>1</relatesTo><i> a.rasch@uni-muenster.de</i><br /><searchLink fieldCode="AR" term="%22Gorlatch%2C+Sergei%22">Gorlatch, Sergei</searchLink><relatesTo>1</relatesTo><i> gorlatch@uni-muenster.de</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Parallel+Programming%22">International Journal of Parallel Programming</searchLink>. Feb2018, Vol. 46 Issue 1, p101-119. 19p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22OpenCL+%28Computer+program+language%29%22">OpenCL (Computer program language)</searchLink><br /><searchLink fieldCode="DE" term="%22Homomorphisms%22">Homomorphisms</searchLink><br /><searchLink fieldCode="DE" term="%22Graphics+processing+units%22">Graphics processing units</searchLink><br /><searchLink fieldCode="DE" term="%22Central+processing+units%22">Central processing units</searchLink><br /><searchLink fieldCode="DE" term="%22Parallel+programming%22">Parallel programming</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Homomorphisms (traditionally defined on lists) are functions that can be parallelized by the divide-and-conquer paradigm. In this paper, we introduce an extension of the traditional homomorphism concept- multi-dimensional homomorphisms (MDHs)-which capture parallelism on multi-dimensional arrays. We propose md_hom-a new parallel pattern (a.k.a. algorithmic skeleton), based on the MDH concept, to simplify parallel programming for a broad class of applications. The md_hom pattern is general enough to subsume common parallel patterns such as map and reduce, and also more complex functions built by composing and nesting several patterns. We present a generic implementation schema for md_hom in form of an efficient, correct-by-construction OpenCL pseudocode that targets various parallel architectures such as multi-core CPU and graphics processing unit (GPU). We develop our pseudocode schema as parametrized in tuning parameters: these allow to optimize the code for different devices and input sizes by performing an automated search on the parameter space. We evaluate the schematically generated, executable OpenCL code using the example of general matrix-vector multiplication (GEMV)-an important linear algebra routine which has gained more attention recently due to its use in the application area of deep learning-on two parallel architectures-Intel CPU and NVIDIA GPU. Our performance results are competitive and in some cases even better than the hand-tuned GEMV implementations provided by the state-of-the-art libraries Intel MKL and NVIDIA cuBLAS, as well as the auto-tunable OpenCL BLAS library CLBlast. [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/s10766-017-0508-z Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 19 StartPage: 101 Subjects: – SubjectFull: OpenCL (Computer program language) Type: general – SubjectFull: Homomorphisms Type: general – SubjectFull: Graphics processing units Type: general – SubjectFull: Central processing units Type: general – SubjectFull: Parallel programming Type: general Titles: – TitleFull: Multi-dimensional Homomorphisms and Their Implementation in OpenCL. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Rasch, Ari – PersonEntity: Name: NameFull: Gorlatch, Sergei IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 02 Text: Feb2018 Type: published Y: 2018 Identifiers: – Type: issn-print Value: 08857458 Numbering: – Type: volume Value: 46 – Type: issue Value: 1 Titles: – TitleFull: International Journal of Parallel Programming Type: main |
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