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DTSTART;TZID=America/Chicago:20181113T160000
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UID:submissions.supercomputing.org_SC18_sess279_drs123@linklings.com
SUMMARY:Designing High-Performance, Resilient, and Heterogeneity-Aware Key
 -Value Storage for Modern HPC Clusters
DESCRIPTION:Doctoral Showcase\nArchitectures, Memory, Runtime Systems, Sto
 rage, Workshop Reg Pass, Tutorial Reg Pass, Tech Program Reg Pass, Exhibit
 s Reg Pass, Exhibits - Exhibit Hall Only Reg Pass, Doctoral Showcase\n\nDe
 signing High-Performance, Resilient, and Heterogeneity-Aware Key-Value Sto
 rage for Modern HPC Clusters\n\nShankar, Panda, Lu\n\nDistributed key-valu
 e stores are being increasingly used to accelerate Big Data workloads on m
 odern HPC clusters. The advances in HPC technologies (e.g., RDMA, SSDs) ha
 s directed several efforts towards employing hybrid storage with RDMA, for
  designing high- performance key-value stores. With this as basis, in my r
 esearch, I take a holistic approach to designing a high-performance key-va
 lue storage system for HPC clusters that can maximize end-to-end performan
 ce while ensuring data resilience, that encompasses: (1) RDMA-enabled netw
 orking, (2) high-speed NVMs, and, (3) heterogeneous compute capabilities, 
 available on current HPC systems. Towards this, I introduce RDMA-aware des
 igns to enable: (1) non-blocking API semantics for designing high-performa
 nce client-side read/write pipelines, (2) fast online erasure coding for m
 emory-efficient resilience, and, (3) SIMD-aware server-side accelerations;
  to enable Big Data applications to optimally leverage hybrid key-value st
 ores in HPC environments.
URL:https://sc18.supercomputing.org/presentation/?id=drs123&sess=sess279
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