Publications | Research

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Artificial Intelligence and Machine Learning
High Performance Computing

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2025

Augmenting Simulated Noisy Quantum Data Collection by Orders of Magnitude Using Pre-Trajectory Sampling with Batched Execution

Taylor Patti, Thien Nguyen, Justin Lietz, Alex McCaskey, Brucek Khailany

Huge ensembles–Part 1: Design of ensemble weather forecasts using spherical Fourier neural operators

Ankur Mahesh, William D. Collins, Boris Bonev, Noah Brenowitz, Yair Cohen, Joshua Elms, Peter Harrington, Karthik Kashinath, Thorsten Kurth, Joshua North, Travis O'Brian, Mike Pritchard, David Pruitt, Mark Risser, Shashank Subramanian, Jared Willard

Huge ensembles – Part 2: Properties of a huge ensemble of hindcasts generated with spherical Fourier neural operators

Ankur Mahesh, William D. Collins, Boris Bonev, Noah Brenowitz, Yair Cohen, Peter Harrington, Karthik Kashinath, Thorsten Kurth, Joshua North, Travis O'Brian, Mike Pritchard, David Pruitt, Mark Risser, Shashank Subramanian, Jared Willard

FourCastNet 3: A geometric approach to probabilistic machine-learning weather forecasting at scale

Boris Bonev, Thorsten Kurth, Ankur Mahesh, Mauro Bisson, Jean Kossaifi, Karthik Kashinath, Anima Anandkumar, William D. Collins, Mike Pritchard, Alex Keller

Beyond the Buzz: A Pragmatic Take on Inference Disaggregation

Tiyasa Mitra, Ritika Borkar, Nidhi Bhatia, Ramon Matas, Shivam Raj, Dheevatsa Mudigere, Ritchie Zhao, Maximilian Golub, Arpan Dutta, Sailaja Madduri, Dharmesh Jani, Brian Pharris, Bita Darvish Rouhani

SLIM: One-shot Quantization and Sparsity with Low-rank Approximation for LLM Weight Compression

Mohammad Mozaffari , Amir Yazdanbakhsh, Maryam Mehri Dehnavi

ICML

2024

Differentiable GPU-Parallelized Task and Motion Planning

William Shen, Caelan Garrett, Nishanth Kumar, Ankit Goyal, Tucker Hermans, Leslie Pack Kaelbling, Tomás Lozano-Pérez, Fabio Ramos

CORL

2023

Neuralangelo: High-Fidelity Neural Surface Reconstruction

Max Zhaoshuo Li, Thomas Müller, Alex Evans, Russell H. Taylor, Mathias Unberath, Ming-Yu Liu, Chen-Hsuan Lin

CVPR

The Best Inventions of 2023, TIME Magazine

2022

Instant Neural Graphics Primitives with a Multiresolution Hash Encoding

Thomas Müller, Alex Evans, Christoph Schied, Alex Keller

SIGGRAPH

Best Technical Paper, SIGGRAPH 2022
THE BEST INVENTIONS OF 2022, TIME

2021

Learning Sparse Matrix Row Permutations for Efficient SpMM on GPU Architectures

Atefeh Mehrabi, Donghyuk Lee, Niladrish Chatterjee, Danial J. Sorin, Benjamin C. Lee, Mike O'Connor

2020

Accelerating Reinforcement Learning through GPU Atari Emulation

Iuri Frosio, Steven Dalton

Buddy Compression: Enabling Larger Memory for Deep Learning and HPC Workloads on GPUs

Esha Chouske, Michael B. Sullivan, Mike O'Connor, Mattan Erez, Jeff Pool, David Nellans, Steve Keckler

An In-Network Architecture for Accelerating Shared-Memory Multiprocessor Collectives

Benjamin Klenk, Ted Jiang, Greg Thorson, Larry Dennison

2019

Highly-scalable, Physics-informed GANs for Learning Solutions of Stochastic PDEs

Liu Yang, Sean Treichler, Thorsten Kurth, Keno Fischer, David Barajas-Solano, Josh Romero, Valentin Churavy, Alexandre Tartakovsky, Michael Houston, Prabhat, George Karniadakis

GPU-Accelerated Atari Emulation for Reinforcement Learning

Steven Dalton, Iuri Frosio, Michael Garland

Buddy Compression: Enabling Larger Memory for Deep Learning and HPC Workloads on GPUs

Esha Choukse, Michael B. Sullivan, Mike O'Connor, Mattan Erez, Jeff Pool, David Nellans, Stephen W. Keckler

Metaoptimization on a Distributed System for Deep Reinforcement Learning

Greg Heinrich, Iuri Frosio

2018

Exascale Deep Learning for Climate Analytics

Thorsten Kurth, Sean Treichler, Joshua Romero, Mayur Mudigonda, Nathan Luehr, Everett Phillips, Ankur Mahesh, Michael Matheson, Jack Deslippe, Massimiliano Fatica, Prabhat, Michael Houston

Structurally Sparsified Backward Propagation for Faster Long Short-Term Memory Training

Maohua Zhu, Jason Clemons, Jeff Pool, Minsoo Rhu, Steve Keckler, Yuan Xie