General matrix multiplication (GEMM) is pervasive in various domains, such as signal processing, computer vision, and machine learning. Conventional binary architectures for GEMM exhibit poor scalability in area and energy efficiency, due to the …
Stochastic Computing (SC) has shown great promise in achieving low hardware area and power consumption for neuromorphic architectures compared to traditional binary-encoded computation, due to its bit-serial data representation and extremely …