GROW: A Row-Stationary Sparse-Dense GEMM Accelerator for Memory-Efficient Graph Convolutional Neural Networks-Reference-Cited by-同舟云学术

GROW: A Row-Stationary Sparse-Dense GEMM Accelerator for Memory-Efficient Graph Convolutional Neural Networks

Published:2023-02 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Symposium on High-Performance Computer Architecture (HPCA)
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Author:

Hwang Ranggi¹,Kang Minhoo¹,Lee Jiwon¹,Kam Dongyun²,Lee Youngjoo²,Rhu Minsoo¹

Affiliation:

1. KAIST,School of Electrical Engineering

2. POSTECH,Department of Electrical Engineering

Funder

National Research Foundation of Korea

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10070856/10070923/10070983.pdf?arnumber=10070983

Reference53 articles.

1. Inductive Representation Learning on Large Graphs;hamilton;Proceedings of the International Conference on Neural Information Processing Systems (NIPS),2017

2. A3: Accelerating Attention Mechanisms in Neural Networks with Approximation;ham;Proceedings of the International Symposium on High-Performance Computer Architecture (HPCA),2020

3. Computing’s Energy Problem (and What We Can Do About It);horowitz;IEEE International Solid-State Circuits Conference (ISSCC),2014

4. ExTensor

5. SpArch: Efficient Architecture for Sparse Matrix Multiplication

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