ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2304.04976
  4. Cited By
Partitioner Selection with EASE to Optimize Distributed Graph Processing

Partitioner Selection with EASE to Optimize Distributed Graph Processing

11 April 2023
Nikolai Merkel
R. Mayer
Tawkir Ahmed Fakir
Hans-Arno Jacobsen
ArXivPDFHTML

Papers citing "Partitioner Selection with EASE to Optimize Distributed Graph Processing"

4 / 4 papers shown
Title
Can Graph Reordering Speed Up Graph Neural Network Training? An
  Experimental Study
Can Graph Reordering Speed Up Graph Neural Network Training? An Experimental Study
Nikolai Merkel
Pierre Toussing
R. Mayer
Hans-Arno Jacobsen
GNN
20
1
0
17 Sep 2024
CUTTANA: Scalable Graph Partitioning for Faster Distributed Graph
  Databases and Analytics
CUTTANA: Scalable Graph Partitioning for Faster Distributed Graph Databases and Analytics
Milad Rezaei Hajidehi
Sraavan Sridhar
Margo Seltzer
28
2
0
13 Dec 2023
An Experimental Comparison of Partitioning Strategies for Distributed
  Graph Neural Network Training
An Experimental Comparison of Partitioning Strategies for Distributed Graph Neural Network Training
Nikolai Merkel
Daniel Stoll
R. Mayer
Hans-Arno Jacobsen
GNN
17
1
0
29 Aug 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
29
23
0
23 May 2023
1