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DTSTART;TZID=America/Denver:20231116T140000
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UID:submissions.supercomputing.org_SC23_sess182_pap274@linklings.com
SUMMARY:Optimizing Reconfigurable Optical Datacenters: The Power of Random
 ization
DESCRIPTION:Marcin Bienkowski (University of Wroclaw), David Fuchssteiner 
 (University of Vienna), and Stefan Schmid (Technical University of Berlin)
 \n\nReconfigurable optical topologies are a promising new technology to im
 prove datacenter network performance and cope with the explosive growth of
  traffic. In particular, these networks allow to adaptively connect racks 
 between which there is currently much traffic, hence making an optimal use
  of the bandwidth by avoiding multi-hop forwarding.\n\nThis paper studies 
 the dynamic optimization of such reconfigurable topologies, adapting to th
 e traffic in an online manner. The underlying algorithmic problem can be d
 escribed as an online maximum weight b-matching problem, a generalization 
 of maximum weight matching where each node has at most  b>=1 incident matc
 hing edges. \n\nWe make the case for a randomized approach for matching op
 timization.  Our main contribution is a O(log b)-competitive algorithm and
  we show that it is asymptotically optimal. This algorithm is exponentiall
 y better than the best possible deterministic online algorithm. \n\nWe com
 plement our theoretical results with trace-driven simulations, based on re
 al-world datacenter workloads.\n\nTag: Algorithms, Cloud Computing, Distri
 buted Computing, Heterogeneous Computing, Large Scale Systems, State of th
 e Practice\n\nRegistration Category: Tech Program Reg Pass\n\nReproducibil
 ity Badges: Artifact Available, Artifact Functional\n\nSession Chair: Mahd
 ieh Ghazimirsaeed (Advanced Micro Devices (AMD) Inc)\n\n
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