GNNMark: A Benchmark Suite to Characterize Graph Neural Network Training on GPUs

Author:

Baruah Trinayan,Shivdikar Kaustubh,Dong Shi,Sun Yifan,Mojumder Saiful A,Jung Kihoon,Abellan Jose L.,Ukidave Yash,Joshi Ajay,Kim John,Kaeli David

Publisher

IEEE

Cited by 19 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. HiHGNN: Accelerating HGNNs Through Parallelism and Data Reusability Exploitation;IEEE Transactions on Parallel and Distributed Systems;2024-07

2. NeuraChip: Accelerating GNN Computations with a Hash-based Decoupled Spatial Accelerator;2024 ACM/IEEE 51st Annual International Symposium on Computer Architecture (ISCA);2024-06-29

3. MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training;Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 2;2024-04-27

4. Distributed Graph Neural Network Training: A Survey;ACM Computing Surveys;2024-04-10

5. GME: GPU-based Microarchitectural Extensions to Accelerate Homomorphic Encryption;56th Annual IEEE/ACM International Symposium on Microarchitecture;2023-10-28

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