no code implementations • 25 Feb 2024 • Dan Zhao, Siddharth Samsi, Joseph McDonald, Baolin Li, David Bestor, Michael Jones, Devesh Tiwari, Vijay Gadepally
In this paper, we study the aggregate effect of power-capping GPUs on GPU temperature and power draw at a research supercomputing center.
no code implementations • 26 Jan 2024 • Mark S. Veillette, James M. Kurdzo, Phillip M. Stepanian, John Y. N. Cho, Siddharth Samsi, Joseph McDonald
A number of ML baselines for tornado detection are developed and compared, including a novel deep learning (DL) architecture capable of processing raw radar imagery without the need for manual feature extraction required for existing ML algorithms.
no code implementations • 4 Oct 2023 • Siddharth Samsi, Dan Zhao, Joseph McDonald, Baolin Li, Adam Michaleas, Michael Jones, William Bergeron, Jeremy Kepner, Devesh Tiwari, Vijay Gadepally
Large language models (LLMs) have exploded in popularity due to their new generative capabilities that go far beyond prior state-of-the-art.
no code implementations • 27 Jan 2023 • Dan Zhao, Nathan C. Frey, Joseph McDonald, Matthew Hubbell, David Bestor, Michael Jones, Andrew Prout, Vijay Gadepally, Siddharth Samsi
applications, we are sure to face an ever-mounting energy footprint to sustain these computational budgets, data storage needs, and more.
no code implementations • 12 Sep 2022 • Matthew L. Weiss, Joseph McDonald, David Bestor, Charles Yee, Daniel Edelman, Michael Jones, Andrew Prout, Andrew Bowne, Lindsey McEvoy, Vijay Gadepally, Siddharth Samsi
Our best performing models achieve a classification accuracy greater than 95%, outperforming previous approaches to multi-channel time series classification with the MIT SuperCloud Dataset by 5%.
no code implementations • Findings (NAACL) 2022 • Joseph McDonald, Baolin Li, Nathan Frey, Devesh Tiwari, Vijay Gadepally, Siddharth Samsi
In particular, we focus on techniques to measure energy usage and different hardware and datacenter-oriented settings that can be tuned to reduce energy consumption for training and inference for language models.
no code implementations • 12 Apr 2022 • Benny J. Tang, Qiqi Chen, Matthew L. Weiss, Nathan Frey, Joseph McDonald, David Bestor, Charles Yee, William Arcand, Chansup Byun, Daniel Edelman, Matthew Hubbell, Michael Jones, Jeremy Kepner, Anna Klein, Adam Michaleas, Peter Michaleas, Lauren Milechin, Julia Mullen, Andrew Prout, Albert Reuther, Antonio Rosa, Andrew Bowne, Lindsey McEvoy, Baolin Li, Devesh Tiwari, Vijay Gadepally, Siddharth Samsi
We introduce a labelled dataset that can be used to develop new approaches to workload classification and present initial results based on existing approaches.
no code implementations • 28 Jan 2022 • Nathan C. Frey, Baolin Li, Joseph McDonald, Dan Zhao, Michael Jones, David Bestor, Devesh Tiwari, Vijay Gadepally, Siddharth Samsi
Deep learning (DL) workflows demand an ever-increasing budget of compute and energy in order to achieve outsized gains.
1 code implementation • NeurIPS Workshop AI4Scien 2021 • Nathan C. Frey, Siddharth Samsi, Joseph McDonald, Lin Li, Connor W. Coley, Vijay Gadepally
Deep learning in molecular and materials sciences is limited by the lack of integration between applied science, artificial intelligence, and high-performance computing.
no code implementations • 4 Aug 2021 • Siddharth Samsi, Matthew L Weiss, David Bestor, Baolin Li, Michael Jones, Albert Reuther, Daniel Edelman, William Arcand, Chansup Byun, John Holodnack, Matthew Hubbell, Jeremy Kepner, Anna Klein, Joseph McDonald, Adam Michaleas, Peter Michaleas, Lauren Milechin, Julia Mullen, Charles Yee, Benjamin Price, Andrew Prout, Antonio Rosa, Allan Vanterpool, Lindsey McEvoy, Anson Cheng, Devesh Tiwari, Vijay Gadepally
In this paper we introduce the MIT Supercloud Dataset which aims to foster innovative AI/ML approaches to the analysis of large scale HPC and datacenter/cloud operations.