quiver-team / torch-quiver
PyTorch Library for Low-Latency, High-Throughput Graph Learning on GPUs.
☆296Updated last year
Alternatives and similar repositories for torch-quiver:
Users that are interested in torch-quiver are comparing it to the libraries listed below
- A GPU-accelerated graph learning library for PyTorch, facilitating the scaling of GNN training and inference.☆125Updated 2 months ago
- ☆197Updated last year
- A list of awesome GNN systems.☆299Updated this week
- Implementation of "GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings" in PyTorch☆163Updated 2 years ago
- Low-Level Graph Neural Network Operators for PyG☆180Updated this week
- Large scale graph learning on a single machine.☆161Updated 4 months ago
- The official SALIENT system described in the paper "Accelerating Training and Inference of Graph Neural Networks with Fast Sampling and P…☆38Updated last year
- Visualization tool for Graph Neural Networks☆242Updated 2 years ago
- WholeGraph - large scale Graph Neural Networks☆101Updated 2 months ago
- Largest realworld open-source graph dataset - Worked done under IBM-Illinois Discovery Accelerator Institute and Amazon Research Awards a…☆77Updated last month
- ☆36Updated 7 months ago
- [MLSys 2022] "BNS-GCN: Efficient Full-Graph Training of Graph Convolutional Networks with Partition-Parallelism and Random Boundary Node …☆53Updated last year
- GraphGallery is a gallery for benchmarking Graph Neural Networks, From InplusLab.☆461Updated last year
- ☆347Updated 7 months ago
- PyTorch-Direct code on top of PyTorch-1.8.0nightly (e152ca5) for Large Graph Convolutional Network Training with GPU-Oriented Data Commun…☆45Updated last year
- ☆46Updated 2 years ago
- ☆134Updated last year
- ☆73Updated 3 years ago
- Bag of Tricks for Graph Neural Networks.☆289Updated 6 months ago
- ☆43Updated this week
- [NeurIPS 2021]: Improve the GNN expressivity and scalability by decoupling the depth and receptive field of state-of-the-art GNN architec…☆132Updated 2 years ago
- [TPAMI 2022] "Bag of Tricks for Training Deeper Graph Neural Networks A Comprehensive Benchmark Study" by Tianlong Chen*, Kaixiong Zhou*,…☆126Updated 3 years ago
- A general-purpose, distributed graph random walk engine.☆111Updated last year
- A scalable graph learning toolkit for extremely large graph datasets. (WWW'22, 🏆 Best Student Paper Award)☆148Updated 8 months ago
- SoCC'20 and TPDS'21: Scaling GNN Training on Large Graphs via Computation-aware Caching and Partitioning.☆50Updated last year
- Graphiler is a compiler stack built on top of DGL and TorchScript which compiles GNNs defined using user-defined functions (UDFs) into ef…☆61Updated 2 years ago
- Scalable Graph Neural Networks with Deep Graph Library☆151Updated 4 years ago
- ☆92Updated last year
- Artifact evaluation of the paper "Accelerating Training and Inference of Graph Neural Networks with Fast Sampling and Pipelining"☆24Updated 2 years ago
- [ICLR 2020; IPDPS 2019] Fast and accurate minibatch training for deep GNNs and large graphs (GraphSAINT: Graph Sampling Based Inductive L…☆477Updated 2 years ago