PIMGCN: A ReRAM-Based PIM Design for Graph Convolutional Network Acceleration

Graph Convolutional Network (GCN) is a promising but computing- and memory-intensive learning model. Processing-in-memory (PIM) architecture based on the ReRAM crossbar is a natural fit for GCN inference. It can reduce the data movements and compute the vector-matrix multiplication (VMM) in analog....

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Bibliographic Details

Published in:	2021 58th ACM/IEEE Design Automation Conference (DAC) pp. 583 - 588
Main Authors:	Yang, Tao, Li, Dongyue, Han, Yibo, Zhao, Yilong, Liu, Fangxin, Liang, Xiaoyao, He, Zhezhi, Jiang, Li
Format:	Conference Proceeding
Language:	English
Published:	IEEE 05.12.2021
Subjects:	Accelerator Computer architecture Costs GCN Graphics processing units Optimal scheduling PIM ReRAM Software Software algorithms Virtual machine monitors
Online Access:	Get full text
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