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DTSTAMP:20260624T171344Z
LOCATION:Bldg. 8 - B 102
DTSTART;TZID=Europe/Stockholm:20260701T140000
DTEND;TZID=Europe/Stockholm:20260701T143000
UID:submissions.pasc-conference.org_PASC26_sess165_msa235@linklings.com
SUMMARY:Lessons in Scale: Exploring the Potential of AI Agents for Global 
 Compute Orchestration
DESCRIPTION:Kaushik De (University of Texas at Arlington)\n\nLarge-scale H
 igh Energy Physics (HEP) experiments, such as ATLAS at the LHC, have spent
  decades mastering the art of the "heterogeneous ensemble"—knitting togeth
 er geographically distributed grid sites, Kubernetes clusters, HPC centers
 , and commercial clouds. While these systems have successfully accelerated
  global scientific goals, they have also exposed the inherent limits of ma
 nual and rule-based orchestration at extreme scales.\nIn this talk, we loo
 k beyond traditional management techniques to explore the emerging frontie
 r of AI-driven orchestration. Rather than proposing a static framework, we
  investigate how the hard-won lessons of HEP infrastructure can inform the
  deployment of autonomous AI agents. By leveraging the reasoning capabilit
 ies of Large Language Models (LLMs), can we move toward a system that not 
 only automates routine tasks but also adapts to the volatile complexities 
 of global resource management? We will discuss the opportunities, risks, a
 nd conceptual shifts required to transition from human-defined workflows t
 o an era of intelligent, agentic orchestration.\n\nDomain: Engineering, Ph
 ysics, Computational Methods and Applied Mathematics\n\nSession Chair: Ozg
 ur Ozan Kilic (Brookhaven National Laboratory)\n\n
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