publié le: 2020
Networks of low-power Internet of Things do not have always access to enough computing power to support mainstream cryptographic schemes; such schemes...
Neuromorphic computing based on spiking neural network (SNN) shows good energy-efficiency. However, it is inefficient for SNN to perform the convoluti...
Computing-in-memory (CIM) is proposed to alleviate the processor-memory data transfer bottleneck in traditional von Neumann architectures, and spintro...
Recent advances in deep neural network demand more than millions of parameters to handle and mandate the high-performance computing resources with imp...
publié le: 2021
Spin Transfer Torque Magnetic Random Access Memory (STT-MRAM) is a promising candidate as a universal on-chip memory technology due to its non-volatil...