יום שלישי, 15 בספטמבר 2026 LIVE
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כתבה arXiv cs.AI ·

Hierarchical Server Architecture for Agentic Science

תקציר מקורי באנגליתarXiv:2608.05332v2 Announce Type: replace-cross Abstract: Agentic science is transforming the landscape of computational work, and is applied to scientific pipelines and workload managers. Scientific workloads require specialized hardware within and between institutions. Automated resource discovery is an essential step for scheduling workloads with specific hardware and environmental requirements. In this paper, we present a hierarchical, dynamic architecture and accompanying software to discover resources across diverse cloud, edge, and HPC systems. The design enables concurrent, asynchronous negotiation, selection, and dispatch of requests for work using secretary agents. The agents probe and discover 51 real and simulated providers across 7 categories. We perform 19,973 negotiation and
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