3 papers
cs.PF2026
KEET: Explaining Performance of GPU Kernels Using LLM Agents
Joshua H. Davis, Klaudiusz Rydzy, Srinivasan Ramesh +5
Performance profiles of GPU kernels generated by tools such as Nsight Compute are rich in detail but are often challenging to interpret. To achieve the best performance possible on…
cs.DC2025
ParEval-Repo: A Benchmark Suite for Evaluating LLMs with Repository-level HPC Translation Tasks
Joshua H. Davis, Daniel Nichols, Ishan Khillan +1
GPGPU architectures have become significantly more diverse in recent years, which has led to an emergence of a variety of specialized programming models and software stacks to supp…
cs.DC2024
Can Large Language Models Write Parallel Code?
Daniel Nichols, Joshua H. Davis, Zhaojun Xie +2
Large language models are increasingly becoming a popular tool for software development. Their ability to model and generate source code has been demonstrated in a variety of conte…