DC Field | Value | Language |
---|---|---|
dc.contributor.author | Yoon, Wonsup | ko |
dc.contributor.author | Ok, Jisu | ko |
dc.contributor.author | Moon, Sue | ko |
dc.contributor.author | Kwon, Youngjin | ko |
dc.date.accessioned | 2023-11-20T08:01:32Z | - |
dc.date.available | 2023-11-20T08:01:32Z | - |
dc.date.created | 2023-11-20 | - |
dc.date.created | 2023-11-20 | - |
dc.date.issued | 2023-09-12 | - |
dc.identifier.citation | ACM SIGCOMM 2023 Conference | - |
dc.identifier.uri | http://hdl.handle.net/10203/314872 | - |
dc.description.abstract | Memory disaggregation is a new datacenter paradigm separating compute and memory nodes. While memory disaggregation improves memory utilization and scalability, it poses challenges for cloud applications, particularly in terms of high tail latency. Existing memory disaggregation systems focus on optimizing the disaggregation stack, but it does not always guarantee excellent application performance. We review existing memory disaggregation and tail-optimized systems and explain their limitations in this context. We also propose two preliminary solutions: asynchronous page fault handling and a faulty request classifier. The emulation result shows that asynchronous page fault handling reduces tail latencies by 50% compared to synchronous handling. | - |
dc.language | English | - |
dc.publisher | Association for Computing Machinery, Inc | - |
dc.title | Designing a Memory Disaggregation System for Cloud | - |
dc.type | Conference | - |
dc.identifier.scopusid | 2-s2.0-85174016240 | - |
dc.type.rims | CONF | - |
dc.citation.publicationname | ACM SIGCOMM 2023 Conference | - |
dc.identifier.conferencecountry | US | - |
dc.identifier.conferencelocation | New York | - |
dc.identifier.doi | 10.1145/3603269.3610854 | - |
dc.contributor.localauthor | Moon, Sue | - |
dc.contributor.localauthor | Kwon, Youngjin | - |
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