共 50 条
- [1] BRGraph: An efficient graph neural network training system by reusing batch data on GPU CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2022, 34 (15):
- [2] Accelerate Graph Neural Network Training by Reusing Batch Data on GPUs 2021 IEEE INTERNATIONAL PERFORMANCE, COMPUTING, AND COMMUNICATIONS CONFERENCE (IPCCC), 2021,
- [3] POSTER: ParGNN: Efficient Training for Large-Scale Graph Neural Network on GPU Clusters PROCEEDINGS OF THE 29TH ACM SIGPLAN ANNUAL SYMPOSIUM ON PRINCIPLES AND PRACTICE OF PARALLEL PROGRAMMING, PPOPP 2024, 2024, : 469 - 471
- [4] Graph Neural Network Training with Data Tiering PROCEEDINGS OF THE 28TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING, KDD 2022, 2022, : 3555 - 3565
- [7] ByteGNN: Efficient Graph Neural Network Training at Large Scale PROCEEDINGS OF THE VLDB ENDOWMENT, 2022, 15 (06): : 1228 - 1242
- [8] Rethinking Graph Data Placement for Graph Neural Network Training on Multiple GPUs PROCEEDINGS OF THE 36TH ACM INTERNATIONAL CONFERENCE ON SUPERCOMPUTING, ICS 2022, 2022,
- [9] Refurbish Your Training Data: Reusing Partially Augmented Samples for Faster Deep Neural Network Training PROCEEDINGS OF THE 2021 USENIX ANNUAL TECHNICAL CONFERENCE, 2021, : 537 - 550
- [10] GCNTrain: A Unified and Efficient Accelerator for Graph Convolutional Neural Network Training 2022 IEEE 40TH INTERNATIONAL CONFERENCE ON COMPUTER DESIGN (ICCD 2022), 2022, : 730 - 737