60 citations · 129 across the 11 of their papers we have counts for
11 papers
Sustainable Supercomputing for AI: GPU Power Capping at HPC Scale
Dan Zhao, Siddharth Samsi, Joseph McDonald +5
As research and deployment of AI grows, the computational burden to support and sustain its progress inevitably does too. To train or fine-tune state-of-the-art models in NLP, comp…
A Benchmark Dataset for Tornado Detection and Prediction using Full-Resolution Polarimetric Weather Radar Data
Mark S. Veillette, James M. Kurdzo, Phillip M. Stepanian +3
Weather radar is the primary tool used by forecasters to detect and warn for tornadoes in near-real time. In order to assist forecasters in warning the public, several algorithms h…
From Words to Watts: Benchmarking the Energy Costs of Large Language Model Inference
Siddharth Samsi, Dan Zhao, Joseph McDonald +7
Large language models (LLMs) have exploded in popularity due to their new generative capabilities that go far beyond prior state-of-the-art. These technologies are increasingly bei…
A Green(er) World for A.I
Dan Zhao, Nathan C. Frey, Joseph McDonald +6
As research and practice in artificial intelligence (A.I.) grow in leaps and bounds, the resources necessary to sustain and support their operations also grow at an increasing pace…
A Deep Learning-based Velocity Dealiasing Algorithm Derived from the WSR-88D Open Radar Product Generator
Mark S. Veillette, James M. Kurdzo, Phillip M. Stepanian +3
Radial velocity estimates provided by Doppler weather radar are critical measurements used by operational forecasters for the detection and monitoring of life-impacting storms. The…
An Evaluation of Low Overhead Time Series Preprocessing Techniques for Downstream Machine Learning
Matthew L. Weiss, Joseph McDonald, David Bestor +8
In this paper we address the application of pre-processing techniques to multi-channel time series data with varying lengths, which we refer to as the alignment problem, for downst…
Great Power, Great Responsibility: Recommendations for Reducing Energy for Training Language Models
Joseph McDonald, Baolin Li, Nathan Frey +3
The energy requirements of current natural language processing models continue to grow at a rapid, unsustainable pace. Recent works highlighting this problem conclude there is an u…
The MIT Supercloud Workload Classification Challenge
Benny J. Tang, Qiqi Chen, Matthew L. Weiss +24
High-Performance Computing (HPC) centers and cloud providers support an increasingly diverse set of applications on heterogenous hardware. As Artificial Intelligence (AI) and Machi…
Benchmarking Resource Usage for Efficient Distributed Deep Learning
Nathan C. Frey, Baolin Li, Joseph McDonald +6
Deep learning (DL) workflows demand an ever-increasing budget of compute and energy in order to achieve outsized gains. Neural architecture searches, hyperparameter sweeps, and rap…
Scalable Geometric Deep Learning on Molecular Graphs
Nathan C. Frey, Siddharth Samsi, Joseph McDonald +3
Deep learning in molecular and materials sciences is limited by the lack of integration between applied science, artificial intelligence, and high-performance computing. Bottleneck…
The MIT Supercloud Dataset
Siddharth Samsi, Matthew L Weiss, David Bestor +24
Artificial intelligence (AI) and Machine learning (ML) workloads are an increasingly larger share of the compute workloads in traditional High-Performance Computing (HPC) centers a…