Publications

Our publications provide insight into some of our leading-edge research.

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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
Task-Based Tensor Computations on Modern GPUs
Rohan Yadav, Michael Garland, Alex Aiken, Michael Bauer
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
Adaptive Algebraic Reuse of Reordering in Cholesky Factorizations with Dynamic Sparsity Patterns
Behrooz Zarebavani, Danny Kaufman, David Levin, Maryam Mehri Dehnavi
Composing Distributed Computations Through Task and Kernel Fusion
Rohan Yadav, Shiv Sundrum, Wonchan Lee, Michael Garland, Michael Bauer, Alex Aiken, Fredrik Kjolstad
Automatic Tracing in Task-Based Runtime Systems
Rohan Yadav, Michael Bauer, David Broman, Michael Garland, Alex Aiken, Fredrik Kjolstad

2021

GPS: A Global Publish-Subscribe Model for Multi-GPU Memory Management
Harini Muthukrishnan, Daniel Lustig, David Nellans, Thomas Wenisch
Best Paper nominee
IEEE Micro Top Picks in Computer Architecture (Honorable Mention)
EMOGI: Efficient Memory-access for Out-of-memory Graph-traversal in GPUs
Seung Won Min, Vikram Sharma Mailthody, Zaid Qureshi, Jinjun Xiong, Eiman Ebrahimi, Wen-mei Hwu
Large Graph Convolutional Network Training with GPU-Oriented Data Communication Architecture
Seung Won Min, Kun Wu, Sitao Huang, Mert Hidayetoglu, Jinjun Xiong, Eiman Ebrahimi, Deming Chen, Wen-mei Hwu
Suraksha: A Quantitative AV Safety Evaluation Framework to Analyze Safety Implications of Perception Design Choices
Hengyu Zhao, Siva Hari, Timothy Tsai, Michael B. Sullivan, Steve Keckler, Jishen Zhao
Efficient Multi-GPU Shared Memory via Automatic Optimization of Fine-Grained Transfers
Harini Muthukrishnan, David Nellans, Daniel Lustig, Jeffrey Fessler, Thomas Wenisch
Demystifying GPU Reliability: Comparing and Combining Beam Experiments, Fault Simulation, and Profiling
Fernando Fernandes dos Santos, Siva Hari, Pedro Martins Basso, Luigi Carro, Paolo Rech
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
Large Graph Convolutional Network Training with GPU-Oriented Data Communication Architecture
Seung Won Min, Kun Wu, Sitao Huang, Mert Hidayetoglu, Jinjun Xiong, Eiman Ebrahimi, Deming Chen, Wen-mei Hwu
Scaling Implicit Parallelism via Dynamic Control Replication
Michael Bauer, Wonchan Lee, Elliott Slaughter, Zhihao Jia, Mario Di Renzo, Manolis Papadakis, Galen Shipman, Patrick McCormick, Michael Garland, Alex Aiken