Resource-Aware Device Allocation of Data-Parallel Applications on Heterogeneous Systems
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Donghyeon | - |
dc.contributor.author | Kang, Seokwon | - |
dc.contributor.author | Lim, Junsu | - |
dc.contributor.author | Jung, Sunwook | - |
dc.contributor.author | Kim, Woosung | - |
dc.contributor.author | Park, Yongjun | - |
dc.date.accessioned | 2022-07-07T11:14:49Z | - |
dc.date.available | 2022-07-07T11:14:49Z | - |
dc.date.created | 2021-05-12 | - |
dc.date.issued | 2020-11 | - |
dc.identifier.issn | 2079-9292 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/144414 | - |
dc.description.abstract | As recent heterogeneous systems comprise multi-core CPUs and multiple GPUs, efficient allocation of multiple data-parallel applications has become a primary goal to achieve both maximum total performance and efficiency. However, the efficient orchestration of multiple applications is highly challenging because a detailed runtime status such as expected remaining time and available memory size of each computing device is hidden. To solve these problems, we propose a dynamic data-parallel application allocation framework called ADAMS. Evaluations show that our framework improves the average total execution device time by 1.85x over the round-robin policy in the non-shared-memory system with small data set. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | MDPI | - |
dc.title | Resource-Aware Device Allocation of Data-Parallel Applications on Heterogeneous Systems | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Park, Yongjun | - |
dc.identifier.doi | 10.3390/electronics9111825 | - |
dc.identifier.scopusid | 2-s2.0-85094895522 | - |
dc.identifier.wosid | 000593613800001 | - |
dc.identifier.bibliographicCitation | ELECTRONICS, v.9, no.11, pp.1 - 18 | - |
dc.relation.isPartOf | ELECTRONICS | - |
dc.citation.title | ELECTRONICS | - |
dc.citation.volume | 9 | - |
dc.citation.number | 11 | - |
dc.citation.startPage | 1 | - |
dc.citation.endPage | 18 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | Y | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Physics | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.relation.journalWebOfScienceCategory | Physics, Applied | - |
dc.subject.keywordPlus | OPENCL | - |
dc.subject.keywordAuthor | device abstraction | - |
dc.subject.keywordAuthor | dynamic resource management | - |
dc.subject.keywordAuthor | GPGPUs | - |
dc.subject.keywordAuthor | heterogeneous system architecture | - |
dc.subject.keywordAuthor | multitasking | - |
dc.subject.keywordAuthor | OpenCL | - |
dc.identifier.url | https://www.mdpi.com/2079-9292/9/11/1825 | - |
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