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TDC: Towards Extremely Efficient CNNs on GPUs via Hardware-Aware Tucker Decomposition.

, , , , , , and . PPoPP, page 260-273. ACM, (2023)

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Improving Prediction-Based Lossy Compression Dramatically via Ratio-Quality Modeling., , , , , and . ICDE, page 2494-2507. IEEE, (2022)Revisiting Huffman Coding: Toward Extreme Performance on Modern GPU Architectures., , , , , , and . IPDPS, page 881-891. IEEE, (2021)Bring orders into uncertainty: enabling efficient uncertain graph processing via novel path sampling on multi-accelerator systems., , , , , , , , , and 2 other author(s). ICS, page 11:1-11:14. ACM, (2022)Error-Controlled Lossy Compression Optimized for High Compression Ratios of Scientific Datasets., , , , , , , and . IEEE BigData, page 438-447. IEEE, (2018)GWLZ: A Group-wise Learning-based Lossy Compression Framework for Scientific Data., , , , , and . CoRR, (2024)TAC: Optimizing Error-Bounded Lossy Compression for Three-Dimensional Adaptive Mesh Refinement Simulations., , , , , , and . HPDC, page 135-147. ACM, (2022)Exploring Autoencoder-based Error-bounded Compression for Scientific Data., , , , , , , and . CLUSTER, page 294-306. IEEE, (2021)Significantly Improving Lossy Compression for HPC Datasets with Second-Order Prediction and Parameter Optimization., , , , , , and . HPDC, page 89-100. ACM, (2020)Significantly improving lossy compression quality based on an optimized hybrid prediction model., , , , , , and . SC, page 33:1-33:26. ACM, (2019)Accelerating Relative-error Bounded Lossy Compression for HPC datasets with Precomputation-Based Mechanisms., , , , , , , and . MSST, page 65-78. IEEE, (2019)