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GE-SpMM: General-purpose Sparse Matrix-Matrix Multiplication on GPUs for
  Graph Neural Networks

GE-SpMM: General-purpose Sparse Matrix-Matrix Multiplication on GPUs for Graph Neural Networks

7 July 2020
Guyue Huang
Guohao Dai
Yu Wang
Huazhong Yang
    GNN
ArXivPDFHTML

Papers citing "GE-SpMM: General-purpose Sparse Matrix-Matrix Multiplication on GPUs for Graph Neural Networks"

12 / 12 papers shown
Title
RDMA-Based Algorithms for Sparse Matrix Multiplication on GPUs
RDMA-Based Algorithms for Sparse Matrix Multiplication on GPUs
Benjamin Brock
A. Buluç
Katherine Yelick
18
2
0
29 Nov 2023
Accel-GCN: High-Performance GPU Accelerator Design for Graph Convolution
  Networks
Accel-GCN: High-Performance GPU Accelerator Design for Graph Convolution Networks
Xiaoru Xie
Hongwu Peng
Amit Hasan
Shaoyi Huang
Jiahui Zhao
Haowen Fang
Wei Zhang
Tong Geng
O. Khan
Caiwen Ding
GNN
30
30
0
22 Aug 2023
AdaptGear: Accelerating GNN Training via Adaptive Subgraph-Level Kernels
  on GPUs
AdaptGear: Accelerating GNN Training via Adaptive Subgraph-Level Kernels on GPUs
Yangjie Zhou
Yaoxu Song
Jingwen Leng
Zihan Liu
Weihao Cui
Zhendong Zhang
Cong Guo
Quan Chen
Li-Wei Li
Minyi Guo
GNN
22
1
0
27 May 2023
STen: Productive and Efficient Sparsity in PyTorch
STen: Productive and Efficient Sparsity in PyTorch
Andrei Ivanov
Nikoli Dryden
Tal Ben-Nun
Saleh Ashkboos
Torsten Hoefler
30
4
0
15 Apr 2023
PiPAD: Pipelined and Parallel Dynamic GNN Training on GPUs
PiPAD: Pipelined and Parallel Dynamic GNN Training on GPUs
Chunyang Wang
Desen Sun
Yunru Bai
GNN
AI4CE
39
15
0
01 Jan 2023
RSC: Accelerating Graph Neural Networks Training via Randomized Sparse
  Computations
RSC: Accelerating Graph Neural Networks Training via Randomized Sparse Computations
Zirui Liu
Sheng-Wei Chen
Kaixiong Zhou
Daochen Zha
Xiao Huang
Xia Hu
29
14
0
19 Oct 2022
Sgap: Towards Efficient Sparse Tensor Algebra Compilation for GPU
Sgap: Towards Efficient Sparse Tensor Algebra Compilation for GPU
Genghan Zhang
Yuetong Zhao
Yanting Tao
Zhongming Yu
Guohao Dai
Sitao Huang
Yuanyuan Wen
Pavlos Petoumenos
Yu Wang
41
4
0
07 Sep 2022
Parallel and Distributed Graph Neural Networks: An In-Depth Concurrency
  Analysis
Parallel and Distributed Graph Neural Networks: An In-Depth Concurrency Analysis
Maciej Besta
Torsten Hoefler
GNN
32
56
0
19 May 2022
GROW: A Row-Stationary Sparse-Dense GEMM Accelerator for
  Memory-Efficient Graph Convolutional Neural Networks
GROW: A Row-Stationary Sparse-Dense GEMM Accelerator for Memory-Efficient Graph Convolutional Neural Networks
Ranggi Hwang
M. Kang
Jiwon Lee
D. Kam
Youngjoo Lee
Minsoo Rhu
GNN
11
20
0
01 Mar 2022
AutoGMap: Learning to Map Large-scale Sparse Graphs on Memristive
  Crossbars
AutoGMap: Learning to Map Large-scale Sparse Graphs on Memristive Crossbars
Bo Lyu
Shengbo Wang
S. Wen
Kaibo Shi
Yin Yang
Lingfang Zeng
Tingwen Huang
19
2
0
15 Nov 2021
Neural Bellman-Ford Networks: A General Graph Neural Network Framework
  for Link Prediction
Neural Bellman-Ford Networks: A General Graph Neural Network Framework for Link Prediction
Zhaocheng Zhu
Zuobai Zhang
Louis-Pascal Xhonneux
Jian Tang
GNN
19
296
0
13 Jun 2021
Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph
  Neural Networks
Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks
Minjie Wang
Da Zheng
Zihao Ye
Quan Gan
Mufei Li
...
J. Zhao
Haotong Zhang
Alex Smola
Jinyang Li
Zheng-Wei Zhang
AI4CE
GNN
189
744
0
03 Sep 2019
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