William Wen
ORCID:
0009-0009-1502-9520
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About
Contact & Profiles
A5102974949
Research Areas
- Software Engineering Research
- Parallel Computing and Optimization Techniques
- Software Testing and Debugging Techniques
Menlo School
2024
Jason Ansel
E Yang
Horace He
Natalia Gimelshein
Animesh Jain
and 44
more
Michael Voznesensky
Bin Bao
Peter Bell
David Berard
Evgeni Burovski
Geeta Chauhan
Anjali Chourdia
Will Constable
Alban Desmaison
Zachary DeVito
E. F. D. Ellison
Will Feng
J. 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
Wu Peng
Soumith Chintala
This paper introduces two extensions to the popular PyTorch machine learning framework, TorchDynamo and TorchInductor, which implement torch.compile feature released in 2. is a Python-level just-in-time (JIT) compiler that enables graph compilation programs without sacrificing flexibility of Python. It achieves this by dynamically modifying Python bytecode before execution extracting sequences operations into an FX graph, then JIT compiled using one many extensible backends. TorchInductor...
10.1145/3620665.3640366
article
EN
2024-04-22
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