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UID:submissions.supercomputing.org_SC24_sess487_post169@linklings.com
SUMMARY:SWARM: Scientific Workflow Applications on Resilient Metasystem
DESCRIPTION:Pawel Zuk (University of Southern California, Information Scie
 nces Institute); Hongwei Jin (Argonne National Laboratory (ANL)); Imtiaz M
 ahmud (Lawrence Berkeley National Laboratory (LBNL)); Krishnan Raghavan (A
 rgonne National Laboratory (ANL)); Komal Thareja (Renaissance Computing In
 stitute (RENCI)); Shixun Wu (University of California, Riverside); Prasann
 a Balaprakash (Oak Ridge National Laboratory (ORNL)); Franck Cappello (Arg
 onne National Laboratory (ANL)); Zizhong Chen (University of California, R
 iverside); Ewa Deelman (University of Southern California, Information Sci
 ences Institute); Sheng Di (Argonne National Laboratory (ANL)); Aiden Hama
 de and Mariam Kiran (Oak Ridge National Laboratory (ORNL)); Anirban Mandal
 , Erik Scott, and Cong Wang (Renaissance Computing Institute (RENCI)); and
  John Wu (Lawrence Berkeley National Laboratory (LBNL))\n\nCurrent (centra
 lized) resource management strategies typically require a global view of d
 istributed HPC systems, relying on a cluster-wide resource manager for sch
 eduling, with static, expert-tuned rules. This centralized decision-making
  approach suffers from resilience, efficiency and scalability issues. In t
 his work, we describe our initial progress in the SWARM project that takes
  a novel decentralized multi-agent approach leveraging Swarm Intelligence 
 (SI) and consensus strategies for enhanced robustness, resilience, and fau
 lt tolerance. We present our foundational SWARM system model to improve ne
 twork overlays, enhance job selection using multi-agent consensus algorith
 ms, and design SI-inspired scheduling approaches.\n\nRegistration Category
 : Tech Program Reg Pass, Exhibits Reg Pass\n\nSession Chairs: Ayesha Afzal
  (Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen National Hig
 h Performance Computing Center); Sally Ellingson (University of Kentucky);
  and Alan Sussman (University of Maryland)\n\n
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