Kariyappa, S.

Reducing the Impact of Phase-Change Memory Conductance Drift on the Inference of large-scale Hardware Neural Networks

Ambrogio, S., Gallot, M., Spoon, K., Tsai, H., Mackin, C., Wesson, M., Kariyappa, S., Narayanan, P., Liu, C.-C., Kumar, A., et al. (2019) · 2019 IEEE International Electron Devices Meeting (IEDM)

Advanced Memory and Neural ComputingPhase-change materials and chalcogenides

Cited by 76

Noise-Resilient DNN: Tolerating Noise in PCM-Based AI Accelerators via Noise-Aware Training

Kariyappa, S., Tsai, H., Spoon, K., Ambrogio, S., Narayanan, P., Mackin, C., Chen, A., Qureshi, M., & Burr, G. W. (2021) · IEEE Transactions on Electron Devices

Advanced Memory and Neural ComputingLow-power high-performance VLSI design

Cited by 45