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LLM-Assisted Translation of Legacy FORTRAN Codes to C++: A Cross-Platform Study

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arxiv 2504.15424 v1 pith:L4RQZNA6 submitted 2025-04-21 cs.SE cs.AI

LLM-Assisted Translation of Legacy FORTRAN Codes to C++: A Cross-Platform Study

classification cs.SE cs.AI
keywords fortrantranslationcodecodeslegacyquantifiedtranslatedllm-based
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Large Language Models (LLMs) are increasingly being leveraged for generating and translating scientific computer codes by both domain-experts and non-domain experts. Fortran has served as one of the go to programming languages in legacy high-performance computing (HPC) for scientific discoveries. Despite growing adoption, LLM-based code translation of legacy code-bases has not been thoroughly assessed or quantified for its usability. Here, we studied the applicability of LLM-based translation of Fortran to C++ as a step towards building an agentic-workflow using open-weight LLMs on two different computational platforms. We statistically quantified the compilation accuracy of the translated C++ codes, measured the similarity of the LLM translated code to the human translated C++ code, and statistically quantified the output similarity of the Fortran to C++ translation.

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Cited by 2 Pith papers

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  2. Systematic LLM Translation of Legacy Scientific Code to Differentiable Frameworks: Application to a Land Surface Model

    cs.SE 2026-06 conditional novelty 6.0

    An LLM-based pipeline systematically converts the CLM-ml-v2 Fortran land surface model to JAX, delivering full differentiability, 8x fewer optimization steps, and 24x wall-clock speedup at N=2048 while releasing the c...