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TEA+: A Novel Temporal Graph Random Walk Engine with Hybrid Storage Architecture.

, , , , , , , , , , and . ACM Trans. Archit. Code Optim., 21 (2): 37 (June 2024)

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Motif-based Graph Representation Learning with Application to Chemical Molecules., , , , , and . CoRR, (2022)Threshold Factor Track Classification Algorithm Based on Target Motion Model., , , , , , and . UIC/ATC/ScalCom, page 1163-1168. IEEE Computer Society, (2015)Optimizing FPGA-based Accelerator Design for Large-Scale Molecular Similarity Search (Special Session Paper)., , , , , , , , , and 2 other author(s). ICCAD, page 1-7. IEEE, (2021)From reconfigurable SDR to cognitive femto-cell: A practical platform., , and . WCSP, page 1-6. IEEE, (2011)E.T.: re-thinking self-attention for transformer models on GPUs., , , , , , , and . SC, page 25. ACM, (2021)TEA+: A Novel Temporal Graph Random Walk Engine with Hybrid Storage Architecture., , , , , , , , , and 1 other author(s). ACM Trans. Archit. Code Optim., 21 (2): 37 (June 2024)Tango: rethinking quantization for graph neural network training on GPUs., , , , , and . CoRR, (2023)HMC-TRAN: A Tensor-core Inspired Hierarchical Model Compression for Transformer-based DNNs on GPU., , , , , , , , , and . ACM Great Lakes Symposium on VLSI, page 169-174. ACM, (2021)Practical Guide of Using Kendall's \tau in the Context of Forecasting Critical Transitions, , and . (2020)cite arxiv:2010.02478.A length adaptive algorithm-hardware co-design of transformer on FPGA through sparse attention and dynamic pipelining., , , , , , , , , and 1 other author(s). DAC, page 1135-1140. ACM, (2022)