Congratulations Bin Lei, Caiwen Ding, Le Chen, Pei-Hung Lin, and Chunhua Liao on having your paper accepted by the HPEC 2023 conference and receiving the Outstanding Student Paper Award.

Creating a Dataset for High-Performance Computing Code Translation using LLMs: A Bridge Between OpenMP Fortran and C++

In this study, we present a novel dataset for training machine learning models translating between OpenMP Fortran and C++ code. To ensure reliability and applicability, the dataset is created from a range of representative open-source OpenMP benchmarks. It is also refined using a meticulous code similarity test. The effectiveness of our dataset is assessed using both quantitative (CodeBLEU) and qualitative (human evaluation) methods. We showcase how this dataset significantly elevates the translation competencies of large language models (LLMs). Specifically, models without prior coding knowledge experienced a boost of × 5.1 in their CodeBLEU scores, while models with some coding familiarity saw an impressive × 9.9-fold increase.

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