From Legacy Fortran to Portable Kokkos: An Autonomous Agentic AI Workflow

The paper introduces an autonomous AI workflow that uses specialized large language model agents to translate legacy Fortran code into performance‑portable Kokkos C++ programs. The pipeline handles translation, validation, compilation, execution, testing, debugging, and optimization, and has been shown to modernize benchmark kernels across heterogeneous GPU‑accelerated hardware. Experiments demonstrate that paid OpenAI models can produce optimized Kokkos code for only a few dollars, outperforming Fortran baselines, while open‑source models often fail to generate functional code.

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• llms
• agents
• benchmarks