24 citations · 35 across the 17 of their papers we have counts for
5 papers · 1 filter
CodeRosetta: Pushing the Boundaries of Unsupervised Code Translation for Parallel Programming
Ali TehraniJamsaz, Arijit Bhattacharjee, Le Chen +3
Recent advancements in Large Language Models (LLMs) have renewed interest in automatic programming language translation. Encoder-decoder transformer models, in particular, have sho…
OMPar: Automatic Parallelization with AI-Driven Source-to-Source Compilation
Tal Kadosh, Niranjan Hasabnis, Prema Soundararajan +5
Manual parallelization of code remains a significant challenge due to the complexities of modern software systems and the widespread adoption of multi-core architectures. This pape…
The Landscape and Challenges of HPC Research and LLMs
Le Chen, Nesreen K. Ahmed, Akash Dutta +14
Recently, language models (LMs), especially large language models (LLMs), have revolutionized the field of deep learning. Both encoder-decoder models and prompt-based techniques ha…
MPIrigen: MPI Code Generation through Domain-Specific Language Models
Nadav Schneider, Niranjan Hasabnis, Vy A. Vo +9
The imperative need to scale computation across numerous nodes highlights the significance of efficient parallel computing, particularly in the realm of Message Passing Interface (…
OMPGPT: A Generative Pre-trained Transformer Model for OpenMP
Le Chen, Arijit Bhattacharjee, Nesreen Ahmed +4
Large language models (LLMs)such as ChatGPT have significantly advanced the field of Natural Language Processing (NLP). This trend led to the development of code-based large langua…