LIDC: A Location Independent Multi-Cluster Computing Framework for Data Intensive Science

Scientific communities are increasingly using geographically distributed computing platforms. The current methods of compute placement predominantly use logically centralized controllers such as Kubernetes (K8s) to match tasks to available resources. However, this centralized approach is unsuitable...

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Bibliographic Details

Published in:	SC24-W: Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis pp. 760 - 764
Main Authors:	Timilsina, Sankalpa, Shannigrahi, Susmit
Format:	Conference Proceeding
Language:	English
Published:	IEEE 17.11.2024
Subjects:	Collaboration Complexity theory Conferences data intensive science Decentralized control Distributed computing High performance computing Manuals orchestration systems Semantics
Online Access:	Get full text
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