In this article, we propose an efficient and robust spike-driven convolutional neural network
(SCNN) based on the NOR flash computing array (NFCA), which is mapped by the …

In this paper, a novel hardware implementation of analog deep neural network (DNN) based
on NOR Flash Computing Array (NFCA) is presented. The approach eliminates additional …

Deep learning neural network (DNN) can provide efficient approaches to process the
increasing unstructured data, such as images, audio, and video. To improve the computing …

Convolution is one of the key operations in signal processing and machine learning
applications. In this paper, we propose a novel convolution computing paradigm based on …

The advancement of artificial intelligence applications is promoted by developing deep
neural networks (DNNs) with increasing sizes and putting forward higher computing power …

A convolutional neural network (CNN) core that can be readily mapped to a 3D NAND flash
array was demonstrated in a standard 65nm CMOS process. Logic-compatible embedded …

A novel flash-based computing in-memory scheme is presented to accelerate the multiply-
accumulate (MAC) operation. Based on the novel scheme the hardware implementation and …

With the rapid development of machine learning, the demand for high-efficient computing
becomes more and more urgent. To break the bottleneck of the traditional Von Neumann …

Layer-by-layer Adaptively Optimized Error Correcting Code (ECC) is proposed to improve
the reliability of triple-level cell (TLC) NAND flash-based SSD for the scene recognition …

We present a processing-in-memory (PIM)-based hardware platform, referred to as
MONETA, for on-chip acceleration of inference and learning in hybrid convolutional spiking …