1 citations · 2 across the 4 of their papers we have counts for
4 papers
SimAMC: A Fast and Accurate Simulator for Resistive Memory-Based Analog Matrix Computing with Non-Idealities
Junbin Long, Mu Zhou, Saitao Zhang +2
Analog matrix computing (AMC) circuits leverage resistive memory arrays to perform matrix operations in a massively parallel manner, providing an efficient approach for acceleratin…
Modeling Closed-loop Analog Matrix Computing Circuits with Interconnect Resistance
Mu Zhou, Junbin Long, Yubiao Luo +1
Analog matrix computing (AMC) circuits based on resistive random-access memory (RRAM) have shown strong potential for accelerating matrix operations. However, as matrix size grows,…
A 65nm 8b-Activation 8b-Weight SRAM-Based Charge-Domain Computing-in-Memory Macro Using A Fully-Parallel Analog Adder Network and A Single-ADC Interface
Guodong Yin, Mufeng Zhou, Yiming Chen +9
Performing data-intensive tasks in the von Neumann architecture is challenging to achieve both high performance and power efficiency due to the memory wall bottleneck. Computing-in…
GRAPHIC: GatheR-And-Process in Highly parallel with In-SSD Compression Architecture in Very Large-Scale Graph
Yiming Chen, Guohao Dai, Mufeng Zhou +8
Graph convolutional network (GCN), an emerging algorithm for graph computing, has achieved promising performance in graphstructure tasks. To achieve acceleration for data-intensive…