Fe-GCN: A 3D FeFET Memory Based PIM Accelerator for Graph Convolutional Networks
Author:
Affiliation:
1. Tsinghua University,BNRist, Electronic Engineering,Beijing,China
2. Pennsylvania State University,USA
3. Daimler Greater China Ltd.,China
4. East China Normal University,China
Funder
Tsinghua University
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10238464/10238482/10238622.pdf?arnumber=10238622
Reference32 articles.
1. Technological Design of 3D NAND-Based Compute-in-Memory Architecture for GB-Scale Deep Neural Network
2. S-FLASH: A NAND Flash-based Deep Neural Network Accelerator Exploiting Bit-level Sparsity
3. First demonstration of ferroelectric Si: HfO2 based 3D FE-FET with trench architecture for dense nonvolatile memory application;banerjee;International Memory Workshop (IMW),2021
4. GP3D: 3D NAND Based In-Memory Graph Processing Accelerator
5. Fast graph representation learning with PyTorch Geometric;fey;ArXiv Prepr ArXiv190311027,2019
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