Accelerating LINPACK with MPI-OpenCL on Clusters of Multi-GPU Nodes.
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| Title: | Accelerating LINPACK with MPI-OpenCL on Clusters of Multi-GPU Nodes. |
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| Authors: | Jo, Gangwon1, Nah, Jeongho1, Lee, Jun1, Kim, Jungwon2, Lee, Jaejin1 |
| Source: | IEEE Transactions on Parallel & Distributed Systems. Jul2015, Vol. 26 Issue 7, p1814-1825. 12p. |
| Subjects: | LINPACK (Computer system), Graphics processing units, Heterogeneous computing, Communication models, Benchmark testing (Engineering) |
| Abstract: | OpenCL is an open standard to write parallel applications for heterogeneous computing systems. Since its usage is restricted to a single operating system instance, programmers need to use a mix of OpenCL and MPI to program a heterogeneous cluster. In this paper, we introduce an MPI-OpenCL implementation of the LINPACK benchmark for a cluster with multi-GPU nodes. The LINPACK benchmark is one of the most widely used benchmark applications for evaluating high performance computing systems. Our implementation is based on High Performance LINPACK (HPL) and uses the blocked LU decomposition algorithm. We address that optimizations aimed at reducing the overhead of CPUs are necessary to overcome the performance gap between the CPUs and the multiple GPUs. Our LINPACK implementation achieves 93.69 Tflops (46 percent of the theoretical peak) on the target cluster with 49 nodes, each node containing two eight-core CPUs and four GPUs. [ABSTRACT FROM AUTHOR] |
| Copyright of IEEE Transactions on Parallel & Distributed Systems is the property of IEEE 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 | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 103222732 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Accelerating LINPACK with MPI-OpenCL on Clusters of Multi-GPU Nodes. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Jo%2C+Gangwon%22">Jo, Gangwon</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Nah%2C+Jeongho%22">Nah, Jeongho</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Lee%2C+Jun%22">Lee, Jun</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Kim%2C+Jungwon%22">Kim, Jungwon</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Lee%2C+Jaejin%22">Lee, Jaejin</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22IEEE+Transactions+on+Parallel+%26+Distributed+Systems%22">IEEE Transactions on Parallel & Distributed Systems</searchLink>. Jul2015, Vol. 26 Issue 7, p1814-1825. 12p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22LINPACK+%28Computer+system%29%22">LINPACK (Computer system)</searchLink><br /><searchLink fieldCode="DE" term="%22Graphics+processing+units%22">Graphics processing units</searchLink><br /><searchLink fieldCode="DE" term="%22Heterogeneous+computing%22">Heterogeneous computing</searchLink><br /><searchLink fieldCode="DE" term="%22Communication+models%22">Communication models</searchLink><br /><searchLink fieldCode="DE" term="%22Benchmark+testing+%28Engineering%29%22">Benchmark testing (Engineering)</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: OpenCL is an open standard to write parallel applications for heterogeneous computing systems. Since its usage is restricted to a single operating system instance, programmers need to use a mix of OpenCL and MPI to program a heterogeneous cluster. In this paper, we introduce an MPI-OpenCL implementation of the LINPACK benchmark for a cluster with multi-GPU nodes. The LINPACK benchmark is one of the most widely used benchmark applications for evaluating high performance computing systems. Our implementation is based on High Performance LINPACK (HPL) and uses the blocked LU decomposition algorithm. We address that optimizations aimed at reducing the overhead of CPUs are necessary to overcome the performance gap between the CPUs and the multiple GPUs. Our LINPACK implementation achieves 93.69 Tflops (46 percent of the theoretical peak) on the target cluster with 49 nodes, each node containing two eight-core CPUs and four GPUs. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of IEEE Transactions on Parallel & Distributed Systems is the property of IEEE 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: 10.1109/TPDS.2014.2321742 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 12 StartPage: 1814 Subjects: – SubjectFull: LINPACK (Computer system) Type: general – SubjectFull: Graphics processing units Type: general – SubjectFull: Heterogeneous computing Type: general – SubjectFull: Communication models Type: general – SubjectFull: Benchmark testing (Engineering) Type: general Titles: – TitleFull: Accelerating LINPACK with MPI-OpenCL on Clusters of Multi-GPU Nodes. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Jo, Gangwon – PersonEntity: Name: NameFull: Nah, Jeongho – PersonEntity: Name: NameFull: Lee, Jun – PersonEntity: Name: NameFull: Kim, Jungwon – PersonEntity: Name: NameFull: Lee, Jaejin IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 07 Text: Jul2015 Type: published Y: 2015 Identifiers: – Type: issn-print Value: 10459219 Numbering: – Type: volume Value: 26 – Type: issue Value: 7 Titles: – TitleFull: IEEE Transactions on Parallel & Distributed Systems Type: main |
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