Empirical study of agentic LLM generation of parallel Julia code finds reliable execution only at small scales with recurring failures in task dependencies and scheduling at larger scales.
and Iserte, S.: Exploring the Role of Large Language Models in High-Performance Computing Programming: A Survey
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Generated, Parallel, Scalable? A Study of Agentic AI-Generated Julia Code on Supercomputers
Empirical study of agentic LLM generation of parallel Julia code finds reliable execution only at small scales with recurring failures in task dependencies and scheduling at larger scales.