CMOS plus stochastic nanomagnets enabling heterogeneous computers for probabilistic inference and learning

CMOS plus stochastic nanomagnets enabling heterogeneous computers for probabilistic inference and learning

Abstract Extending Moore’s law by augmenting complementary-metal-oxide semiconductor (CMOS) transistors with emerging nanotechnologies (X) has become increasingly important. One important class of problems involve sampling-based Monte Carlo algorithms used in probabilistic machine learning, optimiza...

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Bibliographic Details
Main Authors: Nihal Sanjay Singh, Keito Kobayashi, Qixuan Cao, Kemal Selcuk, Tianrui Hu, Shaila Niazi, Navid Anjum Aadit, Shun Kanai, Hideo Ohno, Shunsuke Fukami, Kerem Y. Camsari
Format: Article
Language:English
Published: Nature Portfolio 2024-03-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-024-46645-6

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