2 citations · 4 across the 4 of their papers we have counts for
4 papers
CompCodeVet: A Compiler-guided Validation and Enhancement Approach for Code Dataset
Le Chen, Arijit Bhattacharjee, Nesreen K. Ahmed +4
Large language models (LLMs) have become increasingly prominent in academia and industry due to their remarkable performance in diverse applications. As these models evolve with in…
Scope is all you need: Transforming LLMs for HPC Code
Tal Kadosh, Niranjan Hasabnis, Vy A. Vo +9
With easier access to powerful compute resources, there is a growing trend in the field of AI for software development to develop larger and larger language models (LLMs) to addres…
Quantifying OpenMP: Statistical Insights into Usage and Adoption
Tal Kadosh, Niranjan Hasabnis, Timothy Mattson +2
In high-performance computing (HPC), the demand for efficient parallel programming models has grown dramatically since the end of Dennard Scaling and the subsequent move to multi-c…
Advising OpenMP Parallelization via a Graph-Based Approach with Transformers
Tal Kadosh, Nadav Schneider, Niranjan Hasabnis +3
There is an ever-present need for shared memory parallelization schemes to exploit the full potential of multi-core architectures. The most common parallelization API addressing th…