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  • SpInfer: Leveraging Low-Level Sparsity for Efficient Large Language . . .
    Experimental results show that SpInfer significantly outperforms state-of-the-art SpMM implementations (up to 2 14× and 2 27× over Flash-LLM and SparTA, respectively) across a range of sparsity levels (30% to 70%), with substantial improvements in both memory efficiency and end-to-end inference speed (up to 1 58×)
  • SpInfer: Leveraging Low-Level Sparsity for Efficient Large Language . . .
    SpInfer: Efficient Sparse LLM Inference on GPUs EuroSys ’25, March 30-April 3, 2025, Rotterdam, Netherlands wide range of sparsity levels, from low (30%) to moder-ate (70%) To the best of our knowledge, SpInfer is the first to successfully translate Sparse LLM theoretical speedups into real-world performance benefits 2 Background and
  • GitHub - xxyux SpInfer: SpInfer: Leveraging Low-Level Sparsity for . . .
    Check the results in $SpInfer_HOME end2end_inference ds_scripts ds_result About SpInfer: Leveraging Low-Level Sparsity for Efficient Large Language Model Inference on GPUs
  • 哈工大（深圳）计算机学院王强副教授合作论文获ACM EuroSys 2025最佳论文奖-计算机应用研究中心
    论文提出的SpInfer是一个面向GPU的稀疏LLM高性能推理框架。 SpInfer首先设计了一种新型的稀疏格式，通过位图表示最小化非零元素索引开销，并针对GPU张量核心架构进行了优化。
  • Peijie Dong - Homepage
    [2025 02] 🎉🎉 Congratulations to our team (lead by @Ruibo) to get “SpInfer: Leveraging Low-Level Sparsity for Efficient Large Language Model Inference on GPUs” accepted by EuroSys 2025 as Best Paper!!!
  • SpInfer: Leveraging Low-Level Sparsity for Efficient Large Language . . .
    SpInfer: Leveraging Low-Level Sparsity for Efficient Large Language Model Inference on GPUs Ruibo Fan, Xiangrui Yu, Peijie Dong, Zeyu Li, Gu Gong, Qiang Wang, Wei Wang, Xiaowen Chu Published: 01 Jan 2025, Last Modified: 04 May 2025 EuroSys 2025 Everyone Revisions BibTeX CC BY-SA 4 0
  • Chu Xiaowen - Google Sites
    [1 April 2025] The paper “ SpInfer: Leveraging Low-Level Sparsity for Efficient Large Language Model Inference on GPUs ” has received the Best Paper Award of EuroSys 2025
  • HPMLL SpInfer_EuroSys25 - GitHub
    @inproceedings{fan2025spinfer, title={SpInfer: Leveraging Low-Level Sparsity for Efficient Large Language Model Inference on GPUs}, author={Fan, Ruibo and Yu, Xiangrui and Dong, Peijie and Li, Zeyu and Gong, Gu and Wang, Qiang and Wang, Wei and Chu, Xiaowen}, booktitle={Proceedings of the Twentieth European Conference on Computer Systems}, pages={243--260}, year={2025} }


















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