TorchTPU - A Hybrid Eager/Compiled Architecture for Native PyTorch Execution on TPU
Google and Meta have released TorchTPU, an open-source backend designed to enable native PyTorch execution on Google Cloud TPUs. This tool supports both eager execution and compilation via torch.compile and XLA, aiming to simplify model migration and improve performance compared to the existing PyTorch/XLA framework. By serving as a more direct integration, it offers developers a streamlined way to run machine learning workloads on specialized hardware.
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- AarXiv CS.AI↗Claudio Basile, Michael Voznesensky, Gunhyun Park, Ben Wilson, Parker Holloway, Zhanyong Wan, Vlad Belous, Manish Khanna, Paul Ganssle, Kevin Gleason, Andrew Dame, Brendan Folie, Bhavya Bahl, Haifeng Jin, Pedro Goncalves Mokarzel, Arian Arfaian, Luke Boyer, Chi Zhang, Yiling Yuan, Adam Mainz, Aditya Patel, Huangze Tang, Jay Gan, Lizzie Liang, Will Froom, Tushar Agarwal, Karlo Basioli, Theotime Combes, Emilio Cota, Minos Papadopoulos, Tudor Pipernea, Yarong Mu, Qi Zhou, Yaoshiang Ho, Aleksey Vlasenko, Alexander Brauckmann, Ziyin Huang, Jack Oh, Jerry Hsu, Tanvi Bajpai, Jialei Chen, Wenjun Gu, Chintan Shah, Chris Chan, Sayce Falk, Chris Jones, Rob Torres, Kat Ko, Lee Howes, Freya Azad, Andi Gavrilescu, Joe Pamer, Bill Jia16h ago
- MMarkTechPost↗Asif Razzaq4h ago