Author:
Al Mamun Fahad,Vrudhula Sarma,Vasileska Dragica,Barnaby Hugh,Sanchez Esqueda Ivan
Funder
Jet Propulsion Laboratory
Subject
Materials Chemistry,Electrical and Electronic Engineering,Condensed Matter Physics,Electronic, Optical and Magnetic Materials
Reference54 articles.
1. A. Kumar, “Enabling AI with heterogeneous integration.” Reprint-from-ChipScale_Nov-Dec_2020-IBM.
2. G. W. Burr, P. Narayanan, R. M. Shelby, S. Sidler, I. Boybat, C. Di Nolfo, and Y. Leblebici, “Large-scale neural networks implemented with non-volatile memory as the synaptic weight element: Comparative performance analysis (accuracy, speed, and power),” in: Technical Digest - International Electron Devices Meeting, IEDM, Institute of Electrical and Electronics Engineers Inc., Feb. 2015, pp. 4.4.1-4.4.4. 10.1109/IEDM.2015.7409625.
3. On-chip deep neural network storage with multi-level eNVM;Donato,2018
4. Compute-in-Memory Chips for Deep Learning: Recent Trends and Prospects;Yu;IEEE Circuits Syst Mag,2021
5. Integration and Co-design of Memristive Devices and Algorithms for Artificial Intelligence;Wang;iScience,2020