A compute-in-memory chip based on resistive random-access memory

Realizing increasingly complex artificial intelligence (AI) functionalities directly on edge devices calls for unprecedented energy efficiency of edge hardware. Compute-in-memory (CIM) based on resistive random-access memory (RRAM)(1) promises to meet such demand by storing AI model weights in dense...

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Detalles Bibliográficos
Autores principales: Wan, Weier, Kubendran, Rajkumar, Schaefer, Clemens, Eryilmaz, Sukru Burc, Zhang, Wenqiang, Wu, Dabin, Deiss, Stephen, Raina, Priyanka, Qian, He, Gao, Bin, Joshi, Siddharth, Wu, Huaqiang, Wong, H.-S. Philip, Cauwenberghs, Gert
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9385482/
https://www.ncbi.nlm.nih.gov/pubmed/35978128
http://dx.doi.org/10.1038/s41586-022-04992-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9385482/
https://www.ncbi.nlm.nih.gov/pubmed/35978128
http://dx.doi.org/10.1038/s41586-022-04992-8

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