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We have repurposed Google Tensor Processing Units (TPUs), application-specific chips developed for machine learning, into large-scale dense linear algebra supercomputers.
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2021
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Li Li, Stephan Hoyer, Ryan Pederson, Ruoxi Sun, Ekin Dogus Cubuk, Patrick Francis Riley, and Kieron Burke, “Kohn-Sham equations as regularizer: building prior knowledge into machine-learned physics,” Phys. Rev. Lett. 126
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2021
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Kun Yang, Yi-Fan Chen, Georgios Roumpos, Chris Colby, and John Anderson, “High performance Monte Carlo simulation of Ising model on TPU clusters,” in Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis , SC ’19 (Association for Computing Machinery, New York, NY, USA, 2019)
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Martin Ganahl et al., “Tensor Processing Units for Simulating Quantum Circuits,” Sandbox@Alphabet, in preparation
Cited in the paper.
Ross Shillito, Alexandru Petrescu, Joachim Cohen, Jackson Beall, Markus Hauru, Martin Ganahl, Adam G. M. Lewis, Alexandre Blais, and Guifre Vidal, “Classical simulation of superconducting quantum hardware using Tensor Processing Units,” Sandbox@Alphabet, in preparation
Cited in the paper.
Ryan Pederson et al., “Tensor Processing Units for Quantum Chemistry,” Sandbox@Alphabet, in preparation
Cited in the paper.
John Kozlowski et al., “Acceleration and scaling of Couple Cluster methods with Tensor Processing Units,” Sandbox@Alphabet, in preparation
Cited in the paper.
Martin Ganahl et al., “Density Matrix Renormalization Group using Tensor Processing Units,” Sandbox@Alphabet, in preparation
Cited in the paper.
2021
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https://tensorflow.org/xla , accessed: 2021-10-01
2021
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