Alternatives and similar repositories for Exact

Users that are interested in Exact are comparing it to the libraries listed below

• VITA-Group / Unified-LTH-GNN
  [ICML 2021] "A Unified Lottery Tickets Hypothesis for Graph Neural Networks", Tianlong Chen*, Yongduo Sui*, Xuxi Chen, Aston Zhang, Zhang…
  ☆67Updated 2 years ago
• mengyangniu / ogbn-papers100m-sage
  ☆13Updated 4 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
• 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
• VITA-Group / Large_Scale_GCN_Benchmarking
  This is an authors' implementation of the NIPS 2022 dataset and Benchmark Track Paper "A Comprehensive Study on Large Scale Graph Trainin…
  ☆65Updated 2 years ago
• jasperzhong / GNNFlow
  Distributed Deep Graph Learning Framework for Dynamic Graphs
  ☆18Updated last year
• 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
• camlsys / degree-quant
  ICLR 2021
  ☆48Updated 4 years ago
• devnkong / VQ-GNN
  Official implementation of our VQ-GNN paper (NeurIPS2021)
  ☆38Updated 4 years ago
• chenzhao / light-dist-gnn
  ☆46Updated 3 years ago
• mlsysAE2022 / ae_mlsys_gnn
  ☆10Updated 3 years ago
• szzhang17 / Scaling-Up-Graph-Neural-Networks-Via-Graph-Coarsening
  Code for the KDD 2021 paper "Scaling Up Graph Neural Networks Via Graph Coarsening"
  ☆27Updated last year
• abhijangda / nextdoor-experiments
  ☆12Updated 2 years ago
• IntelLabs / SAR
  ☆35Updated 5 months ago
• PASSIONLab / CAGNET
  ☆47Updated 7 months ago
• Oceanusity / awesome-gnns-on-large-scale-graphs
  ☆138Updated 2 years ago
• cornell-zhang / Polynormer
  Polynormer: Polynomial-Expressive Graph Transformer in Linear Time (ICLR'24)
  ☆42Updated last year
• sigeisler / robustness_of_gnns_at_scale
  This repository contains the official implementation of the paper "Robustness of Graph Neural Networks at Scale" (NeurIPS, 2021).
  ☆30Updated 2 years ago
• xiezhq-hermann / graphiler
  Graphiler is a compiler stack built on top of DGL and TorchScript which compiles GNNs defined using user-defined functions (UDFs) into ef…
  ☆59Updated 3 years ago
• tedzhouhk / GCNP
  ☆16Updated 3 years ago
• BUAA-CI-LAB / Literatures-on-GNN-Acceleration
  A reading list for deep graph learning acceleration.
  ☆256Updated 3 months ago
• PKU-DAIR / SGL
  A scalable graph learning toolkit for extremely large graph datasets. (WWW'22, 🏆 Best Student Paper Award)
  ☆157Updated last year
• xxcclong / GNN-Computing
  Artifact for PPoPP20 "Understanding and Bridging the Gaps in Current GNN Performance Optimizations"
  ☆40Updated 4 years ago
• MortezaRamezani / llcg
  Source code for Learn Locally Correct Globally
  ☆14Updated 4 years ago
• ch-wan / awesome-gnn-systems
  A list of awesome GNN systems.
  ☆332Updated last week
• facebookresearch / shaDow_GNN
  [NeurIPS 2021]: Improve the GNN expressivity and scalability by decoupling the depth and receptive field of state-of-the-art GNN architec…
  ☆137Updated 3 years ago
• iDC-NEU / NeutronStream
  ☆11Updated 2 years ago
• dgSPARSE / dgNN
  [Mlsys'22] Understanding gnn computational graph: A coordinated computation, io, and memory perspective
  ☆22Updated 2 years ago
• cornell-zhang / GraphZoom
  GraphZoom: A Multi-level Spectral Approach for Accurate and Scalable Graph Embedding (ICLR'20 Oral)
  ☆114Updated 2 years ago
• YukeWang96 / GNNAdvisor_OSDI21
  Artifact for OSDI'21 GNNAdvisor: An Adaptive and Efficient Runtime System for GNN Acceleration on GPUs.
  ☆68Updated 2 years ago