SDMA: An Efficient and Flexible Sparse-Dense Matrix-Multiplication Architecture for GNNs
Author:
Affiliation:
1. University Of Science and Technology Of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10035104/10035106/10035246.pdf?arnumber=10035246
Reference43 articles.
1. AWB-GCN: A Graph Convolutional Network Accelerator with Runtime Workload Rebalancing
2. MatRaptor: A Sparse-Sparse Matrix Multiplication Accelerator Based on Row-Wise Product
3. Gamma: leveraging Gustavson’s algorithm to accelerate sparse matrix multiplication
4. BlockGNN: Towards Efficient GNN Acceleration Using Block-Circulant Weight Matrices
5. Multilevel algorithms for partitioning power-law graphs
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