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Revisiting Huffman Coding: Toward Extreme Performance on Modern GPU Architectures.

, , , , , , and . IPDPS, page 881-891. IEEE, (2021)

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cuSZ: An Efficient GPU-Based Error-Bounded Lossy Compression Framework for Scientific Data., , , , , , , , , and 1 other author(s). PACT, page 3-15. ACM, (2020)TSM2: optimizing tall-and-skinny matrix-matrix multiplication on GPUs., , , , , , , , , and . ICS, page 106-116. ACM, (2019)Fixed-PSNR Lossy Compression for Scientific Data., , , , and . CLUSTER, page 314-318. IEEE Computer Society, (2018)Optimizing Lossy Compression Rate-Distortion from Automatic Online Selection between SZ and ZFP., , , , and . IEEE Trans. Parallel Distributed Syst., 30 (8): 1857-1871 (2019)H-GCN: A Graph Convolutional Network Accelerator on Versal ACAP Architecture., , , , , , and . FPL, page 200-208. IEEE, (2022)Accelerating Lossy Compression on HPC Datasets via Partitioning Computation for Parallel Processing., , , , , , , and . HPCC/SmartCity/DSS, page 1791-1797. IEEE, (2019)Optimizing Huffman Decoding for Error-Bounded Lossy Compression on GPUs., , , , , and . IPDPS, page 717-727. IEEE, (2022)A novel memory-efficient deep learning training framework via error-bounded lossy compression., , , and . PPoPP, page 485-487. ACM, (2021)DeepSZ: A Novel Framework to Compress Deep Neural Networks by Using Error-Bounded Lossy Compression., , , , , and . HPDC, page 159-170. ACM, (2019)AMRIC: A Novel In Situ Lossy Compression Framework for Efficient I/O in Adaptive Mesh Refinement Applications., , , , , , , , , and 4 other author(s). SC, page 44:1-44:15. ACM, (2023)