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UID:submissions.supercomputing.org_SC23_sess463_ws_resdis102@linklings.com
SUMMARY:RISA:  Round-Robin Intra-Rack Friendly Scheduling Algorithm for Di
 saggregated Datacenters
DESCRIPTION:Rashadul Kabir (Colorado State University), Ryan G. Kim (Intel
  Corporation), and Mahdi Nikdast (Colorado State University)\n\nRecent tre
 nds see a move away from a fixed-resource server-centric datacenter model 
 to a more adaptable “disaggregated” datacenter model. These disaggregated 
 datacenters can then dynamically group resources to the specific requireme
 nts of an incoming workload, thereby improving efficiency. To properly uti
 lize these disaggregated datacenters, workload allocation techniques must 
 examine the current state of the datacenter and choose resources that not 
 only optimize the current workload request, but future ones. Since disaggr
 egated datacenters are severely bottlenecked by the available network reso
 urces, our work proposes a heuristic-based approach called RISA, which sig
 nificantly reduces the network usage of workload allocations in disaggrega
 ted datacenters. Compared to the state-of-the-art, RISA reduces the power 
 consumption for optical components by 33% and reduces the average CPU-RAM 
 round-trip latency by 50%. Additionally, RISA significantly outperforms th
 e state-of-the-art in terms of execution time.\n\nTag: Architecture and Ne
 tworks, Data Movement and Memory, Resource Management\n\nRegistration Cate
 gory: Workshop Reg Pass\n\nSession Chairs: Balazs Gerofi (Intel Corporatio
 n, RIKEN Center for Computational Science (R-CCS)); Christian Pinto (IBM);
  and John Shalf (Lawrence Berkeley National Laboratory (LBNL))\n\n
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