ASPLOS

PyTorch 2: Faster Machine Learning Through Dynamic Python Bytecode Transformation and Graph Compilation

This paper introduces two extensions to the popular PyTorch machine learning framework, TorchDynamo and TorchInductor, which implement …

Jason Ansel, Edward Yang, Horace He, Natalia Gimelshein, Animesh Jain, Michael Voznesensky, Bin Bao, Peter Bell, David Berard, Evgeni Burovski, Geeta Chauhan, Anjali Chourdia, Will Constable, Alban Desmaison, Zachary DeVito, Elias Ellison, Will Feng, Jiong Gong, Michael Gschwind, Brian Hirsh, Sherlock Huang, Kshiteej Kalambarkar, Laurent Kirsch, Michael Lazos, Mario Lezcano, Yanbo Liang, Jason Liang, Yinghai Lu, C. K. Luk, Bert Maher, Yunjie Pan, Christian Puhrsch, Matthias Reso, Mark Saroufim, Marcos Yukio Siraichi, Helen Suk, Shunting Zhang, Michael Suo, Phil Tillet, Xu Zhao, Eikan Wang, Keren Zhou, Richard Zou, Xiaodong Wang, Ajit Mathews, William Wen, Gregory Chanan, Peng Wu, Soumith Chintala

DrGPUM: Guiding Memory Optimization for GPU-Accelerated Applications

GPUs are widely used in today’s computing platforms to accelerate applications in various domains. However, scarce GPU memory resources …

Mao Lin, Keren Zhou, Pengfei Su

ValueExpert: Exploring Value Patterns in GPU-Accelerated Applications

General-purpose GPUs have become common in modern computing systems to accelerate applications in many domains, including machine …

Keren Zhou, Yueming Hao, John Mellor-Crummey, Xiaozhu Meng, Xu Liu