272 citations · 1.8k across the 82 of their papers we have counts for
82 papers
Advancing AI Challenges for the United States Department of the Air Force
Christian Prothmann, Vijay Gadepally, Jeremy Kepner +35
The DAF-MIT AI Accelerator is a collaboration between the United States Department of the Air Force (DAF) and the Massachusetts Institute of Technology (MIT). This program pioneers…
Combining Performance and Productivity: Accelerating the Network Sensing Graph Challenge with GPUs and Commodity Data Science Software
Siddharth Samsi, Dan Campbell, Emanuel Scoullos +1
The HPEC Graph Challenge is a collection of benchmarks representing complex workloads that test the hardware and software components of HPC systems, which traditional benchmarks, s…
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…
Lincoln AI Computing Survey (LAICS) Update
Albert Reuther, Peter Michaleas, Michael Jones +3
This paper is an update of the survey of AI accelerators and processors from past four years, which is now called the Lincoln AI Computing Survey - LAICS (pronounced "lace"). As in…
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…
Mapping of Internet "Coastlines" via Large Scale Anonymized Network Source Correlations
Hayden Jananthan, Jeremy Kepner, Michael Jones +25
Expanding the scientific tools available to protect computer networks can be aided by a deeper understanding of the underlying statistical distributions of network traffic and thei…
pPython Performance Study
Chansup Byun, William Arcand, David Bestor +17
pPython seeks to provide a parallel capability that provides good speed-up without sacrificing the ease of programming in Python by implementing partitioned global array semantics…
Focusing and Calibration of Large Scale Network Sensors using GraphBLAS Anonymized Hypersparse Matrices
Jeremy Kepner, Michael Jones, Phil Dykstra +23
Defending community-owned cyber space requires community-based efforts. Large-scale network observations that uphold the highest regard for privacy are key to protecting our shared…
Deployment of Real-Time Network Traffic Analysis using GraphBLAS Hypersparse Matrices and D4M Associative Arrays
Michael Jones, Jeremy Kepner, Andrew Prout +20
Matrix/array analysis of networks can provide significant insight into their behavior and aid in their operation and protection. Prior work has demonstrated the analytic, performan…
Toward Sustainable HPC: Carbon Footprint Estimation and Environmental Implications of HPC Systems
Baolin Li, Rohan Basu Roy, Daniel Wang +3
The rapid growth in demand for HPC systems has led to a rise in carbon footprint, which requires urgent intervention. In this work, we present a comprehensive analysis of the carbo…
Clover: Toward Sustainable AI with Carbon-Aware Machine Learning Inference Service
Baolin Li, Siddharth Samsi, Vijay Gadepally +1
This paper presents a solution to the challenge of mitigating carbon emissions from hosting large-scale machine learning (ML) inference services. ML inference is critical to modern…
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…
AI and ML Accelerator Survey and Trends
Albert Reuther, Peter Michaleas, Michael Jones +3
This paper updates the survey of AI accelerators and processors from past three years. This paper collects and summarizes the current commercial accelerators that have been publicl…
KAIROS: Building Cost-Efficient Machine Learning Inference Systems with Heterogeneous Cloud Resources
Baolin Li, Siddharth Samsi, Vijay Gadepally +1
Online inference is becoming a key service product for many businesses, deployed in cloud platforms to meet customer demands. Despite their revenue-generation capability, these ser…
Hypersparse Network Flow Analysis of Packets with GraphBLAS
Tyler Trigg, Chad Meiners, Sandeep Pisharody +23
Internet analysis is a major challenge due to the volume and rate of network traffic. In lieu of analyzing traffic as raw packets, network analysts often rely on compressed network…
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…
Python Implementation of the Dynamic Distributed Dimensional Data Model
Hayden Jananthan, Lauren Milechin, Michael Jones +17
Python has become a standard scientific computing language with fast-growing support of machine learning and data analysis modules, as well as an increasing usage of big data. The…
pPython for Parallel Python Programming
Chansup Byun, William Arcand, David Bestor +18
pPython seeks to provide a parallel capability that provides good speed-up without sacrificing the ease of programming in Python by implementing partitioned global array semantics…
Developing a Series of AI Challenges for the United States Department of the Air Force
Vijay Gadepally, Gregory Angelides, Andrei Barbu +39
Through a series of federal initiatives and orders, the U.S. Government has been making a concerted effort to ensure American leadership in AI. These broad strategy documents have…
MISO: Exploiting Multi-Instance GPU Capability on Multi-Tenant Systems for Machine Learning
Baolin Li, Tirthak Patel, Siddarth Samsi +2
GPU technology has been improving at an expedited pace in terms of size and performance, empowering HPC and AI/ML researchers to advance the scientific discovery process. However,…
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…