mlsanityData to 14 Oct 2026

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

arXiv 2504.15424 ↗First posted 21 Apr 2025cs.SE cs.AIcited by 7

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Abstract (arXiv)

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.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 10 of its 44 references that are in the map. First posted on arXiv 21 Apr 2025.

Builds on

10 of 44 references.

References · 10

  1. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 14,132
  2. 2023Efficient Memory Management for Large Language Model Serving with PagedAttentioncited by 5,944
  3. 2020CodeBLEU: a Method for Automatic Evaluation of Code Synthesiscited by 479
  4. 2024OpenCodeInterpreter: Integrating Code Generation with Execution and Refinementcited by 247
  5. 2023Is ChatGPT A Good Translator? Yes With GPT-4 As The Enginecited by 176
  6. 2017A Tutorial on Kernel Density Estimation and Recent Advancescited by 101
  7. 2023CodeTransOcean: A Comprehensive Multilingual Benchmark for Code Translationcited by 57
  8. 2024SambaNova SN40L: Scaling the AI Memory Wall with Dataflow and Composition of Expertscited by 18
  9. 2024Enhancing Code Translation in Language Models with Few-Shot Learning via Retrieval-Augmented Generationcited by 16
  10. 2023Creating a Dataset for High-Performance Computing Code Translation using LLMs: A Bridge Between OpenMP Fortran and C++cited by 11

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 3; 2026: 4.

7 papers.

  1. 2026Autonomous Research Agents: A Survey of AI Scientists and the Verification Gapcited by 9
  2. 2025From Legacy Fortran to Portable Kokkos: An Autonomous Agentic AI Workflowcited by 5
  3. 2025Leveraging LLMs to Automate Energy-Aware Refactoring of Parallel Scientific Codescited by 3
  4. 2026Systematic LLM Translation of Legacy Scientific Code to Differentiable Frameworks: Application to a Land Surface Modelcited by 2
  5. 2025Performance Evaluation of General Purpose Large Language Models for Basic Linear Algebra Subprograms Code Generationcited by 1
  6. 2026LLM Translation of Compiler Intermediate Representationcited by 0
  7. 2026An Agentic Workflow for Legacy HPC Modernization: Converting the Two-Electron-Integral Core of GAMESScited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024Fortran2CPP: Automating Fortran-to-C++ Translation using LLMs via Multi-Turn Dialogue and Dual-Agent Integration
  2. 2025Beyond Code Pairs: Dialogue-Based Data Generation for LLM Code Translation
  3. 2024TransAgent: Enhancing LLM-Based Code Translation via Fine-Grained Execution Alignment
  4. 2025TransLibEval: Demystify Large Language Models' Capability in Third-party Library-targeted Code Translation
  5. 2025Exploring Code Language Models for Automated HLS-based Hardware Generation: Benchmark, Infrastructure and Analysis
  6. 2026Exploring the Role of LLMs in HPC Programming: A Survey
  7. 2024Automated C/C++ Program Repair for High-Level Synthesis via Large Language Models
  8. 2025When Code Crosses Borders: A Security-Centric Study of LLM-based Code Translation ↗