Alternatives and similar repositories for graphlearn-for-pytorch

Users that are interested in graphlearn-for-pytorch are comparing it to the libraries listed below

• quiver-team / torch-quiver
  PyTorch Library for Low-Latency, High-Throughput Graph Learning on GPUs.
  ☆301Updated 2 years ago
• IllinoisGraphBenchmark / IGB-Datasets
  Largest realworld open-source graph dataset - Worked done under IBM-Illinois Discovery Accelerator Institute and Amazon Research Awards a…
  ☆85Updated 5 months ago
• ch-wan / awesome-gnn-systems
  A list of awesome GNN systems.
  ☆332Updated this week
• amazon-science / tgl
  ☆216Updated last year
• chenzhao / light-dist-gnn
  ☆46Updated 3 years ago
• MITIBMxGraph / SALIENT
  The official SALIENT system described in the paper "Accelerating Training and Inference of Graph Neural Networks with Fast Sampling and P…
  ☆40Updated 2 years ago
• PKU-DAIR / SGL
  A scalable graph learning toolkit for extremely large graph datasets. (WWW'22, 🏆 Best Student Paper Award)
  ☆157Updated last year
• marius-team / marius
  Large scale graph learning on a single machine.
  ☆165Updated 8 months ago
• Oceanusity / awesome-gnns-on-large-scale-graphs
  ☆138Updated 2 years ago
• iDC-NEU / NeutronStream
  ☆11Updated 2 years ago
• KnightKingWalk / KnightKing
  A general-purpose, distributed graph random walk engine.
  ☆109Updated 2 years ago
• GATECH-EIC / PipeGCN
  [ICLR 2022] "PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication" by Cheng Wan, Y…
  ☆33Updated 2 years ago
• GATECH-EIC / BNS-GCN
  [MLSys 2022] "BNS-GCN: Efficient Full-Graph Training of Graph Convolutional Networks with Partition-Parallelism and Random Boundary Node …
  ☆56Updated 2 years ago
• rapidsai / wholegraph
  WholeGraph - large scale Graph Neural Networks
  ☆105Updated 11 months ago
• jasperzhong / GNNFlow
  Distributed Deep Graph Learning Framework for Dynamic Graphs
  ☆18Updated last year
• PASSIONLab / CAGNET
  ☆47Updated 7 months ago
• MITIBMxGraph / SALIENT_artifact
  Artifact evaluation of the paper "Accelerating Training and Inference of Graph Neural Networks with Fast Sampling and Pipelining"
  ☆23Updated 3 years ago
• zhiqi-0 / PaGraph
  SoCC'20 and TPDS'21: Scaling GNN Training on Large Graphs via Computation-aware Caching and Partitioning.
  ☆50Updated 2 years ago
• fabiopetroni / VGP
  A software package for one-pass Vertex-cut balanced Graph Partitioning.
  ☆32Updated 10 years ago
• anilpacaci / streaming-graph-partitioning
  Experimental Setup for Performance Analysis of Streaming Algorithms
  ☆32Updated 3 years ago
• K-Wu / pytorch-direct_dgl
  Large Graph Convolutional Network Training with GPU-Oriented Data Communication Architecture (accepted by PVLDB)
  ☆44Updated 2 years ago
• TuGraph-family / TuGraph-AntGraphLearning
  Ant Graph Learning (AGL) provides a comprehensive solution for graph learning tasks at an industrial scale.
  ☆91Updated last year
• saurabhdash / GCN_Partitioning
  Graph Partitoning Using Graph Convolutional Networks
  ☆66Updated 3 years ago
• rusty1s / pyg_autoscale
  Implementation of "GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings" in PyTorch
  ☆165Updated 3 years ago
• dmlc / GNNLens2
  Visualization tool for Graph Neural Networks
  ☆254Updated 3 years ago
• concept-inversion / C-SAW
  A Framework for Graph Sampling and Random Walk on GPUs.
  ☆38Updated 9 months ago
• pyg-team / pyg-lib
  Low-Level Graph Neural Network Operators for PyG
  ☆217Updated last week
• PeterSH6 / MSPipe
  ☆15Updated last year
• iDC-NEU / NeutronStarLite
  A Distributed System for GNN Training
  ☆124Updated last year
• abhijangda / nextdoor-experiments
  ☆12Updated 2 years ago