RESOURCE DISCOVERY IN DISTRIBUTED EXASCALE SYSTEMS USING A MULTI-AGENT MODEL: CATEGORIZATION OF AGENTS BASED ON THEIR CHARACTERISTICS
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Volume 6 (1), June 2023, Pages 113-120
Fakhraddin Abdullayev
Azerbaijan State Oil and Industry University, Baku, Azerbaijan, This email address is being protected from spambots. You need JavaScript enabled to view it.
Abstract
Resource discovery is a crucial component in high-performance computing (HPC) systems. This paper presents a multi-agent model for resource discovery in distributed exascale systems. Agents are categorized based on resource types and behavior-specific characteristics. The model enables efficient identification and acquisition of memory, process, file, and IO resources. Through a comprehensive exploration, we highlight the potential of our approach in addressing resource discovery challenges in exascale computing systems, paving the way for optimized resource utilization and enhanced system performance.
Keywords:
HPC, Resource Discovery, Agents, Dynamic and Interactive Event, Exascale Systems.
DOI: https://doi.org/10.32010/26166127.2023.6.1.113.120
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