ASCEND: Personal AI Agents for Autonomous Scientific Computing Across HPC Clusters and GPU Workstations

תקציר מקורי באנגליתarXiv:2609.32868v3 Announce Type: replace-cross Abstract: Traditional scientific computing requires researchers to translate intent into environment configuration, resource requests, and executable jobs, then diagnose failures from scheduler state and logs. We present ASCEND (Autonomous Scientific Computing Engine and Novel Discovery), an AI-powered agent interface that supports several placements of the agent and, in the arrangement used for every case here, runs it on the researcher's own laptop, reaching Slurm-managed clusters and a GPU workstation over a multiplexed authenticated connection, with site policies checked by locally executed tools. The language model agent (Claude Code or Codex, selected at each launch) is hosted remotely and proposes actions but holds no credentials. No f