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High Performance Computing

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High Performance Computing

2025

Task-Based Tensor Computations on Modern GPUs

Rohan Yadav, Michael Garland, Alex Aiken, Michael Bauer

PLDI

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

Adaptive Algebraic Reuse of Reordering in Cholesky Factorizations with Dynamic Sparsity Patterns

Behrooz Zarebavani, Danny Kaufman, David Levin, Maryam Mehri Dehnavi

SIGGRAPH

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

2024

Differentiable GPU-Parallelized Task and Motion Planning

William Shen, Caelan Garrett, Ankit Goyal, Tucker Hermans, Fabio Ramos

CORL

2023

Legate Sparse: Distributed Sparse Computing in Python

Rohan Yadav, Wonchan Lee, Melih Elibol, Taylor Patti, Manolis Papadakis, Michael Garland, Alex Aiken, Fredrik Kjolstad, Michael Bauer

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

Visibility Algorithms for Dynamic Dependence Analysis and Distributed Coherence

Michael Bauer, Elliott Slaughter, Sean Treichler, Wonchan Lee, Michael Garland, Alex Aiken

Parsimony: Enabling SIMD/Vector Programming in Standard Compiler Flows

Vijay Kandiah, Daniel Lustig, Oreste Villa, David Nellans, Nikos Hardavellas

Implementing Reinforcement Learning Datacenter Congestion Control in NVIDIA NICs

Benjamin Fuhrer, Yuval Shpigelman, Chen Tessler, Shie Mannor, Gal Chechik, Eitan Zahavy, Gal Dalal

2022

Towards Precision-Aware Fault Tolerance Approaches for Mixed-Precision Applications

Bo Fang, Siva Hari, Timothy Tsai, Xinyi Li, Ganesh Gopalakrishnan, Ignacio Laguna, Kevin Barker, Ang Li

Variable Bitrate Neural Fields

Towaki Takikawa, Alex Evans, Jonathan Tremblay, Thomas Müller, Morgan McGuire, Alec Jacobson, Sanja Fidler

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

Ray/Ribbon Intersections

Alexander Reshetov

GATSPI: GPU Accelerated Gate-Level Simulation for Power Improvement

Yanqing Zhang, Haoxing (Mark) Ren, Akshay Sridharan, Brucek Khailany

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