A 75kb SRAM in 65nm CMOS for In-Memory Computing Based Neuromorphic Image Denoising

A 915-1220 TOPS/W Hybrid In-Memory Computing based Image Restoration and Region Proposal Integrated Circuit for Neuromorphic Vision Sensors in 65nm CMOS

In this work, we present a hybrid memory bit cell - collocated SRAM and DRAM (CRAM) consisting of 11 transistors for in-memory computing (IMC) based image restoration (IR) and region proposal (RP). A robust RP updated algorithm is proposed to improve the performance. This work demonstrates IMC based global parallel diffusion and column/row-wise projection to achieve a maximal energy efficiency of 1220 TOPS/W for image restoration and 915 TOPS/W when combined with region proposal.

单多晶硅CMOS技术中的温度鲁棒模拟神经形态芯片

Temperature-Resilient Analog Neuromorphic Chip in Single-Polysilicon CMOS Technology

本文提出一种温度补偿机制，在单多晶硅CMOS工艺上实现温度鲁棒的模拟神经形态芯片，用于图像识别，在10-60°C范围内保持分类精度，与软件神经网络误差在2%以内。

An Investigation into Neuromorphic ICs using Memristor-CMOS Hybrid Circuits

The memristance of a memristor depends on the amount of charge flowing through it and when current stops flowing through it, it remembers the state. Thus, memristors are extremely suited for implementation of memory units. Memristors find great application in neuromorphic circuits as it is possible to couple memory and processing, compared to traditional Von-Neumann digital architectures where memory and processing are separate. Neural networks have a layered structure where information passes from one layer to another and each of these layers have the possibility of a high degree of paralleli…

A CMOL-Like Memristor-CMOS Neuromorphic Chip-Core Demonstrating Stochastic Binary STDP

The advent of nanoscale memristors raised hopes of being able to build CMOL (CMOS/nanowire/moLecular) type ultra-dense in-memory-computing circuit architectures. In CMOL, nanoscale memristors would be fabricated at the intersection of nanowires. The CMOL concept can be exploited in neuromorphic hardware by fabricating lower-density neurons on CMOS and placing massive analog synaptic connectivity with nanowire and nanoscale-memristor fabric post-fabricated on top. However, technical problems have hindered such developments for presently available reliable commercial monolithic CMOS-memristor te…

Neuromorphic-P2M: Processing-in-Pixel-in-Memory Paradigm for Neuromorphic Image Sensors

Edge devices equipped with computer vision must deal with vast amounts of sensory data with limited computing resources. Hence, researchers have been exploring different energy-efficient solutions such as near-sensor processing, in-sensor processing, and in-pixel processing, bringing the computation closer to the sensor. In particular, in-pixel processing embeds the computation capabilities inside the pixel array and achieves high energy efficiency by generating low-level features instead of the raw data stream from CMOS image sensors. Many different in-pixel processing techniques and approach…

面向神经形态视觉传感器的高性能、可编程极端边缘智能：利用基于磁畴壁运动的MTJ

Toward High Performance, Programmable Extreme-Edge Intelligence for Neuromorphic Vision Sensors utilizing Magnetic Domain Wall Motion-based MTJ

本文首次提出基于MDWMTJ与CMOS混合的神经形态视觉传感器像素内处理方案，通过器件-电路-算法协同设计实现低功耗并行异步卷积，在保持前端能耗的同时将后端能耗平均降低45.3%，并在两个动态视觉数据集上取得高精度。