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FeatGraph: A Flexible and Efficient Backend for Graph Neural Network
  Systems

FeatGraph: A Flexible and Efficient Backend for Graph Neural Network Systems

26 August 2020
Yuwei Hu
Zihao Ye
Minjie Wang
Jiali Yu
Da Zheng
Mu Li
Zheng-Wei Zhang
Zhiru Zhang
Yida Wang
    GNN
ArXivPDFHTML

Papers citing "FeatGraph: A Flexible and Efficient Backend for Graph Neural Network Systems"

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
Performance Optimization of Deep Learning Sparse Matrix Kernels on Intel
  Max Series GPU
Performance Optimization of Deep Learning Sparse Matrix Kernels on Intel Max Series GPU
Mohammad Zubair
Christoph Bauinger
14
0
0
01 Nov 2023
STAG: Enabling Low Latency and Low Staleness of GNN-based Services with
  Dynamic Graphs
STAG: Enabling Low Latency and Low Staleness of GNN-based Services with Dynamic Graphs
Jiawen Wang
Quan Chen
Deze Zeng
Zhuo Song
Chen Chen
Minyi Guo
GNN
24
2
0
27 Sep 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
The Evolution of Distributed Systems for Graph Neural Networks and their
  Origin in Graph Processing and Deep Learning: A Survey
The Evolution of Distributed Systems for Graph Neural Networks and their Origin in Graph Processing and Deep Learning: A Survey
Jana Vatter
R. Mayer
Hans-Arno Jacobsen
GNN
AI4TS
AI4CE
40
23
0
23 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
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
34
56
0
19 May 2022
TorchSparse: Efficient Point Cloud Inference Engine
TorchSparse: Efficient Point Cloud Inference Engine
Haotian Tang
Zhijian Liu
Xiuyu Li
Yujun Lin
Song Han
3DPC
9
97
0
21 Apr 2022
Motif Prediction with Graph Neural Networks
Motif Prediction with Graph Neural Networks
Maciej Besta
Raphael Grob
Cesare Miglioli
Nico Bernold
Grzegorz Kwa'sniewski
...
Raghavendra Kanakagiri
Saleh Ashkboos
Lukas Gianinazzi
Nikoli Dryden
Torsten Hoefler
24
37
0
26 May 2021
DistGNN: Scalable Distributed Training for Large-Scale Graph Neural
  Networks
DistGNN: Scalable Distributed Training for Large-Scale Graph Neural Networks
Vasimuddin
Sanchit Misra
Guixiang Ma
Ramanarayan Mohanty
E. Georganas
A. Heinecke
Dhiraj D. Kalamkar
Nesreen Ahmed
Sasikanth Avancha
GNN
25
119
0
14 Apr 2021
Computing Graph Neural Networks: A Survey from Algorithms to
  Accelerators
Computing Graph Neural Networks: A Survey from Algorithms to Accelerators
S. Abadal
Akshay Jain
Robert Guirado
Jorge López-Alonso
Eduard Alarcón
GNN
27
225
0
30 Sep 2020
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
194
745
0
03 Sep 2019
1