Impact of Phase-Change Memory Drift on Energy Efficiency and Accuracy of Analog Compute-in-Memory Deep Learning Inference (Invited)

التفاصيل البيبلوغرافية
العنوان: Impact of Phase-Change Memory Drift on Energy Efficiency and Accuracy of Analog Compute-in-Memory Deep Learning Inference (Invited)
المؤلفون: Frank, Martin M., Li, Ning, Rasch, Malte J., Jain, Shubham, Chen, Ching-Tzu, Muralidhar, Ramachandran, Han, Jin-Ping, Narayanan, Vijay, Philip, Timothy M., Brew, Kevin, Simon, Andrew, Saraf, Iqbal, Saulnier, Nicole, Boybat, Irem, Wozniak, Stanislaw, Sebastian, Abu, Narayanan, Pritish, Mackin, Charles, Chen, An, Tsai, Hsinyu, Burr, Geoffrey W.
المصدر: 2023 IEEE International Reliability Physics Symposium (IRPS) Reliability Physics Symposium (IRPS), 2023 IEEE International. :1-10 Mar, 2023
Relation: 2023 IEEE International Reliability Physics Symposium (IRPS)
قاعدة البيانات: IEEE Xplore Digital Library
الوصف
ردمك:9781665456722
تدمد:19381891
DOI:10.1109/IRPS48203.2023.10117874