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 …
This brief presents three strategies, including initialization based on Look Up Table (LUT), postprocessing based on bit flipping and hard decision based on the posterior information, to reduce the number of decoding cycles (DCs) for stochastic …
An area-efficient multirate low-density parity-check convolutional code (LDPC-CC) decoder is presented in this brief. Using the layered decoding algorithm, the decoder achieves a bet- ter performance than the message-passing algorithm; the extrinsic- …