Researchers Successfully Modernize Legacy Physics Code Using Structured AI Assistance
Researchers have developed a five-phase agentic pipeline that uses large language models to automatically translate legacy Fortran scientific code into JAX, a differentiable programming framework. The system was tested on CLM-ml-v2, a 19,000-line Fortran land surface model used in Earth system science. The approach could significantly accelerate the modernization of scientific codebases, enabling faster parameter estimation and data assimilation in climate and environmental models.
A team of researchers has built and evaluated a five-phase LLM-based agentic pipeline designed to translate legacy Fortran code into JAX, Google's differentiable programming framework. The pipeline performs static dependency analysis to determine translation order, uses iterative compile-repair loops to autonomously fix errors, and enforces numerical accuracy through a Fortran reference oracle before integrating and verifying gradients. The system was applied to CLM-ml-v2, a 19,000-line Fortran land surface model, across 73 module translation tasks. The resulting differentiable model computes a complete Jacobian in a single backward pass, recovers physical parameters in eight times fewer optimization steps than gradient-free methods, and runs 24 times faster than sequential Fortran at an ensemble size of 2,048. Both the translated model and the pipeline infrastructure have been released publicly as a reusable framework for differentiating other Earth system model components.
What's missing
The paper does not report the overall translation success rate across all 73 modules or detail how many required significant manual intervention beyond the autonomous repair loops. It is also unclear how the pipeline performs on Fortran codebases with different structural characteristics than CLM-ml-v2, limiting generalizability claims.
What different sources said
- arXiv cs.AICenter
Systematic LLM Translation of Legacy Scientific Code to Differentiable Frameworks: Application to a Land Surface Model
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