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DTSTART;TZID=America/Chicago:20181114T133000
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UID:submissions.supercomputing.org_SC18_sess177@linklings.com
SUMMARY:Clouds and Distributed Computing
DESCRIPTION:Paper\nClouds and Distributed Computing, Resource Management, 
 Scheduling, Tech Program Reg Pass\n\nDynamically Negotiating Capacity Betw
 een On-Demand and Batch Clusters\n\nLiu, Keahey, Riteau, Weissman\n\nIn th
 e era of rapid experimental expansion data analysis needs are rapidly outp
 acing the capabilities of small institutional clusters and looking to inte
 grate HPC resources into their workflow. We propose one way of reconciling
  on-demand needs of experimental analytics with the batch managed HPC res.
 ..\n\n---------------------\nA Lightweight Model for Right-Sizing Master-W
 orker Applications\n\nKremer-Herman, Tovar, Thain\n\nWhen running a parall
 el application at scale, a resource provisioning policy should minimize ov
 er-commitment (idle resources) and under-commitment (resource contention).
  However, users seldom know the quantity of resources to appropriately exe
 cute their application. Even with such knowledge, over- a...\n\n----------
 -----------\nA Reference Architecture for Datacenter Scheduling: Design, V
 alidation, and Experiments\n\nAndreadis, Versluis, Mastenbroek, Iosup\n\nD
 atacenters act as cloud-infrastructure to stakeholders across industry, go
 vernment, and academia. To meet growing demand yet operate efficiently, da
 tacenter operators employ increasingly more sophisticated scheduling syste
 ms, mechanisms, and policies. Although many scheduling techniques already 
 exi...\n
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