no code implementations • 29 Jun 2023 • Daniel Nichols, Aniruddha Marathe, Harshitha Menon, Todd Gamblin, Abhinav Bhatele
In this paper, we show how large language models (LLMs) can be applied to tasks specific to high performance and scientific codes.
no code implementations • 15 Mar 2023 • Giorgis Georgakoudis, Konstantinos Parasyris, Chunhua Liao, David Beckingsale, Todd Gamblin, Bronis de Supinski
To address those challenges, this paper proposes new extensions to OpenMP for autonomous, machine learning-driven adaptation.
1 code implementation • 1 Jul 2020 • Suraj P. Kesavan, Harsh Bhatia, Abhinav Bhatele, Todd Gamblin, Peer-Timo Bremer, Kwan-Liu Ma
Optimizing the performance of large-scale parallel codes is critical for efficient utilization of computing resources.
Distributed, Parallel, and Cluster Computing Performance