A parallel fast neighbor searching algorithm for particle-based methods on CPU and GPU architectures in multi-scale simulation.
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| Title: | A parallel fast neighbor searching algorithm for particle-based methods on CPU and GPU architectures in multi-scale simulation. |
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| Authors: | DAI Chang-wei1, KONG Rui-lin1, JI Zhe1,2,3 jizhe@nwpu.edu.cn |
| Source: | Computer Engineering & Science / Jisuanji Gongcheng yu Kexue. Aug2024, Vol. 46 Issue 8, p1349-1360. 12p. |
| Abstract: | Particle-based methods are widely applied in the resolving of complex multi-scale physical phenomena in various science and engineering areas. In order to handle the challenge of increasing computational complexity and declining concurrency for the pair-wised particle searching procedure in massive multi-scale particle-based simulations, a new parallel fast neighbor searching algorithm, which features high-concurrency and low memory footprint, is developed and demonstrated on both many-core CPU and GPU architectures. An inter-level interaction strategy based on the concept of hierarchical nested data structure is proposed to resolve the issue of racing condition in cross-level particle search. An asymmetric mapping method is developed to eliminate the full mapping of particles on each level, which reduces the memory consumption. A set of numerical experiments show that, the proposed algorithm can handle multi-scale problems with particle volume ratio up to 108. Compared with traditional algorithm, the proposed algorithm can achieve 2x-8x speedups and lower memory consumption. The GPUbased implementation of the algorithm achieves state-of-the-art computational efficiency. [ABSTRACT FROM AUTHOR] |
| Copyright of Computer Engineering & Science / Jisuanji Gongcheng yu Kexue is the property of Computer Engineering & Science 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: 179575148 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: A parallel fast neighbor searching algorithm for particle-based methods on CPU and GPU architectures in multi-scale simulation. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22DAI+Chang-wei%22">DAI Chang-wei</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22KONG+Rui-lin%22">KONG Rui-lin</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22JI+Zhe%22">JI Zhe</searchLink><relatesTo>1,2,3</relatesTo><i> jizhe@nwpu.edu.cn</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Computer+Engineering+%26+Science+%2F+Jisuanji+Gongcheng+yu+Kexue%22">Computer Engineering & Science / Jisuanji Gongcheng yu Kexue</searchLink>. Aug2024, Vol. 46 Issue 8, p1349-1360. 12p. – Name: Abstract Label: Abstract Group: Ab Data: Particle-based methods are widely applied in the resolving of complex multi-scale physical phenomena in various science and engineering areas. In order to handle the challenge of increasing computational complexity and declining concurrency for the pair-wised particle searching procedure in massive multi-scale particle-based simulations, a new parallel fast neighbor searching algorithm, which features high-concurrency and low memory footprint, is developed and demonstrated on both many-core CPU and GPU architectures. An inter-level interaction strategy based on the concept of hierarchical nested data structure is proposed to resolve the issue of racing condition in cross-level particle search. An asymmetric mapping method is developed to eliminate the full mapping of particles on each level, which reduces the memory consumption. A set of numerical experiments show that, the proposed algorithm can handle multi-scale problems with particle volume ratio up to 108. Compared with traditional algorithm, the proposed algorithm can achieve 2x-8x speedups and lower memory consumption. The GPUbased implementation of the algorithm achieves state-of-the-art computational efficiency. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Computer Engineering & Science / Jisuanji Gongcheng yu Kexue is the property of Computer Engineering & Science 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.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=179575148 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3969/j.issn.1007-130X.2024.08.003 Languages: – Code: chi Text: Chinese PhysicalDescription: Pagination: PageCount: 12 StartPage: 1349 Titles: – TitleFull: A parallel fast neighbor searching algorithm for particle-based methods on CPU and GPU architectures in multi-scale simulation. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: DAI Chang-wei – PersonEntity: Name: NameFull: KONG Rui-lin – PersonEntity: Name: NameFull: JI Zhe IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 08 Text: Aug2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 1007130X Numbering: – Type: volume Value: 46 – Type: issue Value: 8 Titles: – TitleFull: Computer Engineering & Science / Jisuanji Gongcheng yu Kexue Type: main |
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