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LSim: Fine-Grained Simulation Framework for Large-Scale Performance Evaluation
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Jang, Hamin | - |
dc.contributor.author | Kang, Taehun | - |
dc.contributor.author | Kim, Joonsung | - |
dc.contributor.author | Cho, Jaeyong | - |
dc.contributor.author | Jo, Jae-Eon | - |
dc.contributor.author | Lee, Seungwook | - |
dc.contributor.author | Chang, Wooseok | - |
dc.contributor.author | Kim, Jangwoo | - |
dc.contributor.author | Jang, Hanhwi | - |
dc.date.accessioned | 2022-06-24T08:27:26Z | - |
dc.date.available | 2022-06-24T08:27:26Z | - |
dc.date.created | 2022-05-25 | - |
dc.date.created | 2022-05-25 | - |
dc.date.issued | 2022-01 | - |
dc.identifier.citation | IEEE Computer Architecture Letters, Vol.21 No.1, pp.25-28 | - |
dc.identifier.issn | 1556-6056 | - |
dc.identifier.uri | https://hdl.handle.net/10371/184085 | - |
dc.description.abstract | As large-scale workloads with massive parallelism emerge, the demand for large-scale systems such as datacenters and supercomputers is rising sharply. To accurately design a large-scale system, architects heavily rely on performance modeling at design phases. However, modeling a large-scale workload without a large-scale system is a challenging problem. This paper presents LSim, a framework for large-scale performance evaluation. Based on the captured behavior within small-scale workload traces, LSim extrapolates the behavior of the workload on a large-scale system. To do so, we propose two techniques: (1) representative trace model and (2) function latency model to synthesize a trace and to predict the latency of functions in the synthesized trace, respectively. | - |
dc.language | 영어 | - |
dc.publisher | Institute of Electrical and Electronics Engineers | - |
dc.title | LSim: Fine-Grained Simulation Framework for Large-Scale Performance Evaluation | - |
dc.type | Article | - |
dc.identifier.doi | 10.1109/LCA.2022.3168831 | - |
dc.citation.journaltitle | IEEE Computer Architecture Letters | - |
dc.identifier.wosid | 000790807700002 | - |
dc.identifier.scopusid | 2-s2.0-85128694585 | - |
dc.citation.endpage | 28 | - |
dc.citation.number | 1 | - |
dc.citation.startpage | 25 | - |
dc.citation.volume | 21 | - |
dc.description.isOpenAccess | N | - |
dc.contributor.affiliatedAuthor | Kim, Jangwoo | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.subject.keywordAuthor | Computational modeling | - |
dc.subject.keywordAuthor | Predictive models | - |
dc.subject.keywordAuthor | Large-scale systems | - |
dc.subject.keywordAuthor | Graphics processing units | - |
dc.subject.keywordAuthor | Performance evaluation | - |
dc.subject.keywordAuthor | Indexes | - |
dc.subject.keywordAuthor | Data models | - |
dc.subject.keywordAuthor | Simulation | - |
dc.subject.keywordAuthor | performance evaluation | - |
dc.subject.keywordAuthor | trace synthesis | - |
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