[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
☆34Mar 15, 2023Updated 3 years ago
Alternatives and similar repositories for PipeGCN
Users that are interested in PipeGCN are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- [MLSys 2022] "BNS-GCN: Efficient Full-Graph Training of Graph Convolutional Networks with Partition-Parallelism and Random Boundary Node …☆56Oct 6, 2023Updated 2 years ago
- ☆13Feb 16, 2023Updated 3 years ago
- SoCC'20 and TPDS'21: Scaling GNN Training on Large Graphs via Computation-aware Caching and Partitioning.☆51May 23, 2023Updated 3 years ago
- ☆47Sep 5, 2022Updated 3 years ago
- Adaptive Message Quantization and Parallelization for Distributed Full-graph GNN Training☆24Mar 1, 2024Updated 2 years ago
- Managed Database hosting by DigitalOcean • AdPostgreSQL, MySQL, MongoDB, Kafka, Valkey, and OpenSearch available. Automatically scale up storage and focus on building your apps.
- A Factored System for Sample-based GNN Training over GPUs☆46Jul 26, 2023Updated 2 years ago
- Source code for Learn Locally Correct Globally☆14Nov 15, 2021Updated 4 years ago
- Accepted paper of SIGMOD 2023, DUCATI: A Dual-Cache Training System for Graph Neural Networks on Giant Graphs with the GPU☆16Dec 15, 2023Updated 2 years ago
- Artifact evaluation of the paper "Accelerating Training and Inference of Graph Neural Networks with Fast Sampling and Pipelining"☆23Mar 7, 2022Updated 4 years ago
- Ginex: SSD-enabled Billion-scale Graph Neural Network Training on a Single Machine via Provably Optimal In-memory Caching☆43Jul 10, 2024Updated last year
- A list of awesome GNN systems.☆345Updated this week
- High performance RDMA-based distributed feature collection component for training GNN model on EXTREMELY large graph☆55Jul 3, 2022Updated 4 years ago
- Large Graph Convolutional Network Training with GPU-Oriented Data Communication Architecture (accepted by PVLDB)☆44Jul 1, 2023Updated 3 years ago
- ☆43Jun 13, 2025Updated last year
- Virtual machines for every use case on DigitalOcean • AdGet dependable uptime with 99.99% SLA, simple security tools, and predictable monthly pricing with DigitalOcean's virtual machines, called Droplets.
- Large scale graph learning on a single machine.☆167Feb 25, 2025Updated last year
- ☆49Apr 11, 2025Updated last year
- [FPGA 2020] Open sourced implementation for the ACM/SIGDA FPGA '20 paper titled "GraphACT: Accelerating GCN Training on CPU-FPGA Heteroge…☆19Mar 6, 2021Updated 5 years ago
- A Distributed System for GNN Training☆123Sep 29, 2024Updated last year
- GPU-initiated Large-scale GNN System [ATC 23]☆19Oct 30, 2024Updated last year
- C++17 implementation of einops for libtorch - clear and reliable tensor manipulations with einstein-like notation☆12Oct 16, 2023Updated 2 years ago
- A reading list for deep graph learning acceleration.☆253Jul 26, 2025Updated 11 months ago
- ☆21Mar 23, 2022Updated 4 years ago
- ☆12Dec 8, 2022Updated 3 years ago
- GPU virtual machines on DigitalOcean Gradient AI • AdGet to production fast with high-performance AMD and NVIDIA GPUs you can spin up in seconds. The definition of operational simplicity.
- RPCNIC: A High-Performance and Reconfigurable PCIe-attached RPC Accelerator [HPCA2025]☆15Dec 9, 2024Updated last year
- [PACT'24] GraNNDis. A fast and unified distributed graph neural network (GNN) training framework for both full-batch (full-graph) and min…☆10Aug 13, 2024Updated last year
- Transforming Graphs for Efficient Irregular Graph Processing on GPUs☆51Nov 15, 2022Updated 3 years ago
- HeliosArtifact☆22Sep 27, 2022Updated 3 years ago
- Artifact for OSDI'21 GNNAdvisor: An Adaptive and Efficient Runtime System for GNN Acceleration on GPUs.☆71Mar 2, 2023Updated 3 years ago
- ☆24Oct 31, 2023Updated 2 years ago
- Distributed Multi-GPU GNN Framework☆36Jun 26, 2020Updated 6 years ago
- [DATE 2023] Pipe-BD: Pipelined Parallel Blockwise Distillation☆12Jul 13, 2023Updated 2 years ago
- Dorylus: Affordable, Scalable, and Accurate GNN Training☆76May 31, 2021Updated 5 years ago
- Bare Metal GPUs on DigitalOcean Gradient AI • AdPurpose-built for serious AI teams training foundational models, running large-scale inference, and pushing the boundaries of what's possible.
- Graph Sampling using GPU☆52Mar 17, 2022Updated 4 years ago
- Artifact for PPoPP20 "Understanding and Bridging the Gaps in Current GNN Performance Optimizations"☆42Nov 16, 2021Updated 4 years ago
- ☆19Jul 1, 2020Updated 6 years ago
- Largest realworld open-source graph dataset - Worked done under IBM-Illinois Discovery Accelerator Institute and Amazon Research Awards a…☆86Jun 16, 2025Updated last year
- A software package for one-pass Vertex-cut balanced Graph Partitioning.☆32Aug 2, 2015Updated 10 years ago
- Fastest software for special tensor operations☆21Nov 23, 2023Updated 2 years ago
- SHADE: Enable Fundamental Cacheability for Distributed Deep Learning Training☆36Mar 1, 2023Updated 3 years ago