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LLM pipeline translates legacy Fortran code to JAX for scientific modeling

By PulseAugur Editorial · [2 sources] ·

Researchers have developed a novel five-phase pipeline utilizing LLM-based agents to translate legacy Fortran code into the JAX framework. This system automates the process of code migration, including dependency analysis, autonomous error correction, and numerical parity enforcement. The pipeline was successfully applied to CLM-ml-v2, a 19,000-line land surface model, resulting in a differentiable version that significantly speeds up computation and parameter recovery. AI

IMPACT Enables rapid differentiation of complex scientific models, accelerating research and parameter estimation.

RANK_REASON The cluster contains an academic paper detailing a new methodology and its application.

Read on arXiv cs.MA (Multiagent) →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

LLM pipeline translates legacy Fortran code to JAX for scientific modeling

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COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Aya Lahlou, Linnia Hawkins, Pierre Gentine ·

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

    arXiv:2606.07681v1 Announce Type: cross Abstract: Differentiable programming offers transformative capabilities for scientific modeling, enabling gradient-based parameter estimation, sensitivity analysis, and data assimilation. Yet, migrating legacy codebases into differentiable …

  2. arXiv cs.MA (Multiagent) TIER_1 English(EN) · Pierre Gentine ·

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

    Differentiable programming offers transformative capabilities for scientific modeling, enabling gradient-based parameter estimation, sensitivity analysis, and data assimilation. Yet, migrating legacy codebases into differentiable frameworks remains a challenge. We present a five-…

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