Invasive Compute Balancing for Applications with Shared and Hybrid Parallelization.
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| Title: | Invasive Compute Balancing for Applications with Shared and Hybrid Parallelization. |
|---|---|
| Authors: | Schreiber, Martin1 martin.schreiber@in.tum.de, Riesinger, Christoph1 riesinge@in.tum.de, Neckel, Tobias1 neckel@in.tum.de, Bungartz, Hans-Joachim1 bungartz@in.tum.de, Breuer, Alexander1 breuera@in.tum.de |
| Source: | International Journal of Parallel Programming. Dec2015, Vol. 43 Issue 6, p1004-1027. 24p. |
| Subjects: | High performance computing research, Computer systems, Mesh networks, Parallel programming, Computer programming |
| Abstract: | Achieving high scalability with dynamically adaptive algorithms in high-performance computing (HPC) is a non-trivial task. The invasive paradigm using compute migration represents an efficient alternative to classical data migration approaches for such algorithms in HPC. We present a core-distribution scheduler which realizes the migration of computational power by distributing the cores depending on the requirements specified by one or more parallel program instances. We validate our approach with different benchmark suites for simulations with artificial workload as well as applications based on dynamically adaptive shallow water simulations, and investigate concurrently executed adaptivity parameter studies on realistic Tsunami simulations. The invasive approach results in significantly faster overall execution times and higher hardware utilization than alternative approaches. A dynamic resource management is therefore mandatory for a more efficient execution of scenarios similar to our simulations, e.g. several Tsunami simulations in urgent computing, to overcome strong scalability challenges in the area of HPC. The optimizations obtained by invasive migration of cores can be generalized to similar classes of algorithms with dynamic resource requirements. [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: 109967657 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Invasive Compute Balancing for Applications with Shared and Hybrid Parallelization. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Schreiber%2C+Martin%22">Schreiber, Martin</searchLink><relatesTo>1</relatesTo><i> martin.schreiber@in.tum.de</i><br /><searchLink fieldCode="AR" term="%22Riesinger%2C+Christoph%22">Riesinger, Christoph</searchLink><relatesTo>1</relatesTo><i> riesinge@in.tum.de</i><br /><searchLink fieldCode="AR" term="%22Neckel%2C+Tobias%22">Neckel, Tobias</searchLink><relatesTo>1</relatesTo><i> neckel@in.tum.de</i><br /><searchLink fieldCode="AR" term="%22Bungartz%2C+Hans-Joachim%22">Bungartz, Hans-Joachim</searchLink><relatesTo>1</relatesTo><i> bungartz@in.tum.de</i><br /><searchLink fieldCode="AR" term="%22Breuer%2C+Alexander%22">Breuer, Alexander</searchLink><relatesTo>1</relatesTo><i> breuera@in.tum.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>. Dec2015, Vol. 43 Issue 6, p1004-1027. 24p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22High+performance+computing+research%22">High performance computing research</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+systems%22">Computer systems</searchLink><br /><searchLink fieldCode="DE" term="%22Mesh+networks%22">Mesh networks</searchLink><br /><searchLink fieldCode="DE" term="%22Parallel+programming%22">Parallel programming</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+programming%22">Computer programming</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Achieving high scalability with dynamically adaptive algorithms in high-performance computing (HPC) is a non-trivial task. The invasive paradigm using compute migration represents an efficient alternative to classical data migration approaches for such algorithms in HPC. We present a core-distribution scheduler which realizes the migration of computational power by distributing the cores depending on the requirements specified by one or more parallel program instances. We validate our approach with different benchmark suites for simulations with artificial workload as well as applications based on dynamically adaptive shallow water simulations, and investigate concurrently executed adaptivity parameter studies on realistic Tsunami simulations. The invasive approach results in significantly faster overall execution times and higher hardware utilization than alternative approaches. A dynamic resource management is therefore mandatory for a more efficient execution of scenarios similar to our simulations, e.g. several Tsunami simulations in urgent computing, to overcome strong scalability challenges in the area of HPC. The optimizations obtained by invasive migration of cores can be generalized to similar classes of algorithms with dynamic resource requirements. [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/s10766-014-0336-3 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 24 StartPage: 1004 Subjects: – SubjectFull: High performance computing research Type: general – SubjectFull: Computer systems Type: general – SubjectFull: Mesh networks Type: general – SubjectFull: Parallel programming Type: general – SubjectFull: Computer programming Type: general Titles: – TitleFull: Invasive Compute Balancing for Applications with Shared and Hybrid Parallelization. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Schreiber, Martin – PersonEntity: Name: NameFull: Riesinger, Christoph – PersonEntity: Name: NameFull: Neckel, Tobias – PersonEntity: Name: NameFull: Bungartz, Hans-Joachim – PersonEntity: Name: NameFull: Breuer, Alexander IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 12 Text: Dec2015 Type: published Y: 2015 Identifiers: – Type: issn-print Value: 08857458 Numbering: – Type: volume Value: 43 – Type: issue Value: 6 Titles: – TitleFull: International Journal of Parallel Programming Type: main |
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