TensorNetwork: accelerating tensor network computations and improving the coding experience
APA
Milsted, A. (2019). TensorNetwork: accelerating tensor network computations and improving the coding experience. Perimeter Institute. https://pirsa.org/19060029
MLA
Milsted, Ashley. TensorNetwork: accelerating tensor network computations and improving the coding experience. Perimeter Institute, Jun. 13, 2019, https://pirsa.org/19060029
BibTex
@misc{ pirsa_PIRSA:19060029, doi = {10.48660/19060029}, url = {https://pirsa.org/19060029}, author = {Milsted, Ashley}, keywords = {Condensed Matter}, language = {en}, title = {TensorNetwork: accelerating tensor network computations and improving the coding experience}, publisher = {Perimeter Institute}, year = {2019}, month = {jun}, note = {PIRSA:19060029 see, \url{https://pirsa.org}} }
California Institute of Technology
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Abstract
Tensor networks are powerful computational tools, widely used in condensed matter physics, and increasingly in high-energy physics, with promising applications to machine learning problems. Developed in collaboration with Google and X, we present TensorNetwork: a new software package that makes it easier to code tensor network algorithms and, by using a framework like TensorFlow as a backend, to accelerate computations using specialized hardware (GPUs, TPUs) and integrate tensor networks into machine-learning projects.