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DTSTART:19700308T020000
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DTSTAMP:20181221T160742Z
LOCATION:C2/3/4 Ballroom
DTSTART;TZID=America/Chicago:20181113T171500
DTEND;TZID=America/Chicago:20181113T190000
UID:submissions.supercomputing.org_SC18_sess343_drs123@linklings.com
SUMMARY:Designing High-Performance, Resilient, and Heterogeneity-Aware Key
 -Value Storage for Modern HPC Clusters
DESCRIPTION:Doctoral Showcase\nWorkshop Reg Pass, Tutorial Reg Pass, Tech 
 Program Reg Pass, Exhibits Reg Pass, Exhibits - Exhibit Hall Only Reg Pass
 \n\nDesigning High-Performance, Resilient, and Heterogeneity-Aware Key-Val
 ue Storage for Modern HPC Clusters\n\nShankar, Panda, Lu\n\nDistributed ke
 y-value stores are being increasingly used to accelerate Big Data workload
 s on modern HPC clusters. The advances in HPC technologies (e.g., RDMA, SS
 Ds) has directed several efforts towards employing hybrid storage with RDM
 A, for designing high- performance key-value stores. With this as basis, i
 n my research, I take a holistic approach to designing a high-performance 
 key-value storage system for HPC clusters that can maximize end-to-end per
 formance while ensuring data resilience, that encompasses: (1) RDMA-enable
 d networking, (2) high-speed NVMs, and, (3) heterogeneous compute capabili
 ties, available on current HPC systems. Towards this, I introduce RDMA-awa
 re designs to enable: (1) non-blocking API semantics for designing high-pe
 rformance client-side read/write pipelines, (2) fast online erasure coding
  for memory-efficient resilience, and, (3) SIMD-aware server-side accelera
 tions; to enable Big Data applications to optimally leverage hybrid key-va
 lue stores in HPC environments.
URL:https://sc18.supercomputing.org/presentation/?id=drs123&sess=sess343
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