GATECH-EIC / PipeGCN
[ICLR 2022] "PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication" by Cheng Wan, Youjie Li, Cameron R. Wolfe, Anastasios Kyrillidis, Nam Sung Kim, Yingyan Lin
☆31Updated last year
Alternatives and similar repositories for PipeGCN:
Users that are interested in PipeGCN are comparing it to the libraries listed below
- ☆46Updated 2 years ago
- Ginex: SSD-enabled Billion-scale Graph Neural Network Training on a Single Machine via Provably Optimal In-memory Caching☆36Updated 7 months ago
- SoCC'20 and TPDS'21: Scaling GNN Training on Large Graphs via Computation-aware Caching and Partitioning.☆50Updated last year
- [MLSys 2022] "BNS-GCN: Efficient Full-Graph Training of Graph Convolutional Networks with Partition-Parallelism and Random Boundary Node …☆53Updated last year
- ☆9Updated 2 years ago
- Artifact for OSDI'23: MGG: Accelerating Graph Neural Networks with Fine-grained intra-kernel Communication-Computation Pipelining on Mult…☆39Updated 11 months ago
- Artifact for OSDI'21 GNNAdvisor: An Adaptive and Efficient Runtime System for GNN Acceleration on GPUs.☆64Updated last year
- ☆27Updated 6 months ago
- ☆11Updated 2 years ago
- Distributed Multi-GPU GNN Framework☆36Updated 4 years ago
- 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
- Artifact for PPoPP20 "Understanding and Bridging the Gaps in Current GNN Performance Optimizations"☆39Updated 3 years ago
- ☆30Updated 8 months ago
- A Factored System for Sample-based GNN Training over GPUs☆42Updated last year
- Graph Sampling using GPU☆51Updated 2 years ago
- Artifact for USENIX ATC'23: TC-GNN: Bridging Sparse GNN Computation and Dense Tensor Cores on GPUs.☆45Updated last year
- [HPCA 2022] GCoD: Graph Convolutional Network Acceleration via Dedicated Algorithm and Accelerator Co-Design☆35Updated 2 years ago
- Artifact evaluation of the paper "Accelerating Training and Inference of Graph Neural Networks with Fast Sampling and Pipelining"☆24Updated 2 years ago
- ☆8Updated 2 years ago
- ☆43Updated 3 weeks ago
- A Framework for Graph Sampling and Random Walk on GPUs.☆39Updated 2 weeks ago
- Artifact for PPoPP22 QGTC: Accelerating Quantized GNN via GPU Tensor Core.☆27Updated 3 years ago
- FGNN's artifact evaluation (EuroSys 2022)☆17Updated 2 years 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
- Repo for the IISWC 2018 submission☆9Updated 2 years ago
- ☆105Updated 3 years ago
- ☆73Updated 3 years ago
- Open source code of BGL NSDI 2023☆15Updated last year
- ☆10Updated 3 years ago
- ☆12Updated 2 years ago