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DTSTART;TZID=America/New_York:20241118T121200
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UID:submissions.supercomputing.org_SC24_sess750_ws_indis105@linklings.com
SUMMARY:LIDC: A Location Independent Multi-Cluster Computing Framework for
  Data Intensive Science
DESCRIPTION:Susmit Shannigrahi and Sankalpa Timilsina (Tennessee Technolog
 ical University)\n\nScientific communities are increasingly using geograph
 ically distributed computing platforms. The current methods of compute pla
 cement predominantly use logically centralized controllers such as Kuberne
 tes (K8s) to match tasks to available resources. However, this centralized
  approach is unsuitable in multi-organizational collaborations. Furthermor
 e, workflows often need to use manual configurations tailored for a single
  platform and cannot adapt to dynamic changes across infrastructure.\n\nOu
 r work introduces a decentralized control plane for placing computations o
 n geographically dispersed compute clusters using semantic names. We assig
 n semantic names to computations to match requests with named Kubernetes (
 K8s) service endpoints. We show that this approach provides multiple benef
 its. First, it allows placement of  computational jobs to be independent o
 f location, enabling any cluster with sufficient resources to execute the 
 computation. Second, it facilitates dynamic compute placement without requ
 iring prior knowledge of cluster locations or predefined configurations.\n
 \nTag: Architecture, Data-Intensive, Network, Performance Optimization, Qu
 antum Computing, Security, System Administration\n\nRegistration Category:
  Workshop Reg Pass\n\nSession Chairs: Akbar Kara (Ciena Corporation, SCine
 t); Anees Al-Najjar (Oak Ridge National Laboratory (ORNL), SCinet); and Ni
 k Sultana (Illinois Institute of Technology, SCinet)\n\n
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