3 papers
cs.ET2024
A noise-tolerant, resource-saving probabilistic binary neural network implemented by the SOT-MRAM compute-in-memory system
Yu Gu, Puyang Huang, Tianhao Chen +5
We report a spin-orbit torque(SOT) magnetoresistive random-access memory(MRAM)-based probabilistic binary neural network(PBNN) for resource-saving and hardware noise-tolerant compu…
cs.ET2023
Cryogenic quasi-static embedded DRAM for energy-efficient compute-in-memory applications
Yuhao Shu, Hongtu Zhang, Hao Sun +9
Compute-in-memory (CIM) presents an attractive approach for energy-efficient computing in data-intensive applications. However, the development of suitable memory designs to achiev…
physics.app-ph2023
SOT-MRAM-Enabled Probabilistic Binary Neural Networks for Noise-Tolerant and Fast Training
Puyang Huang, Yu Gu, Chenyi Fu +10
We report the use of spin-orbit torque (SOT) magnetoresistive random-access memory (MRAM) to implement a probabilistic binary neural network (PBNN) for resource-saving applications…