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DTSTART:19700308T020000
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DTSTAMP:20181221T160902Z
LOCATION:C146
DTSTART;TZID=America/Chicago:20181113T103000
DTEND;TZID=America/Chicago:20181113T120000
UID:submissions.supercomputing.org_SC18_sess179@linklings.com
SUMMARY:Data and Storage
DESCRIPTION:Paper\nClouds and Distributed Computing, File Systems, I/O, St
 orage, Tech Program Reg Pass\n\nScaling Embedded In Situ Indexing with Del
 taFS\n\nZheng, Cranor, Guo, Ganger, Amvrosiadis...\n\nAnalysis of large-sc
 ale simulation output is a core element of scientific inquiry, but analysi
 s queries may experience significant I/O overhead when the data is not str
 uctured for efficient retrieval. While in-situ processing allows for impro
 ved time-to-insight for many applications, scaling in-situ...\n\n---------
 ------------\nSP-Cache: Load-Balanced, Redundancy-Free Cluster Caching wit
 h Selective Partition\n\nYu, Huang, Wang, Zhang, Letaief\n\nData-intensive
  clusters increasingly employ in-memory solutions to improve I/O performan
 ce. However, the routinely observed file popularity skew and load imbalanc
 e create hotspots, which significantly degrades the benefits of in-memory 
 solutions. Common approaches to tame load imbalance include copy...\n\n---
 ------------------\nBESPOKV: Application Tailored Scale-Out Key-Value Stor
 es\n\nAnwar, Cheng, Huang, Han, Sim...\n\nEnterprise KV stores are not wel
 l suited for HPC applications, and entail customization and cumbersome end
 -to-end KV design to extract the HPC application needs. In this paper we p
 resent BESPOKV, an adaptive, extensible, and scale-out KV store framework.
  BESPOKV decouples the KV store design into th...\n
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