ECAS: An Edge-Controlled Agentic System for Validation-Gated Scientific Application Execution
Scientific applications increasingly rely on high-performance computing (HPC), yet translating a scientist's high-level goal into a correct target-scale execution remains brittle and labor-intensive. Large language model (LLM) agents promise to automate this, but two obstacles remain: granting a cloud-hosted model direct HPC access exposes credentials and execution authority, while withholding it demands continuous human supervision; and one-shot generation cannot adapt when generated artifacts fail in a site-specific HPC environment. We present \textsc{ECAS}, an \textbf{E}dge-\textbf{C}ontrolled \textbf{A}gentic \textbf{S}ystem for closed-loop execution of scientific computing campaigns ...
| Authors | Baixi Sun, Mingze Xia, Huihuo Zheng |
|---|---|
| Primary category | cs.DC |
| Published | 13 September 2026 |
| Last updated at source | 13 September 2026 |
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