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DTSTAMP:20211207T054812Z
LOCATION:230-231-232
DTSTART;TZID=America/Chicago:20211118T140000
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UID:submissions.supercomputing.org_SC21_sess169_pap146@linklings.com
SUMMARY:LogECMem: Coupling Erasure-Coded In-Memory Key-Value Stores with P
 arity Logging
DESCRIPTION:Paper\n\nLogECMem: Coupling Erasure-Coded In-Memory Key-Value 
 Stores with Parity Logging\n\nCheng, Hu, Ke, Xu, Yao...\n\nIn-memory key-v
 alue stores are often used to speed up Big Data workloads on modern HPC cl
 usters. To maintain their high availability, erasure coding has been recen
 tly adopted as a low-cost redundancy scheme instead of replication. Existi
 ng erasure-coded update schemes, however, have either low performance or h
 igh memory overhead. In this paper, we propose a novel parity logging-base
 d architecture, HybridPL, which creates a hybrid of in-place update (for d
 ata and XOR parity chunks) and log-based update (for the remaining parity 
 chunks), so as to balance the update performance and memory cost, while ma
 intaining efficient single-failure repairs. We realize HybridPL as an in-m
 emory key-value store called LogECMem, and further design efficient repair
  schemes for multiple failures. We prototype LogECMem and conduct experime
 nts on different workloads. We show that LogECMem achieves better update p
 erformance over existing erasure-coded update schemes with low memory over
 head, while maintaining high basic I/O and repair performance.\n\nTag: Rep
 roducibility Badge, Big Data, Data Analytics, Data Management, File System
 s and I/O, Memory Systems, Storage\n\nRegistration Category: Tech Program 
 Reg Pass\n\nReproducibility Badges: Artifact Available
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