CoSPARSE: A Software and Hardware Reconfigurable SpMV Framework for Graph Analytics

Author:

Feng Siying,Sun Jiawen,Pal Subhankar,He Xin,Kaszyk Kuba,Park Dong-hyeon,Morton Magnus,Mudge Trevor,Cole Murray,O'Boyle Michael,Chakrabarti Chaitali,Dreslinski Ronald

Funder

Air Force Research Laboratory

Publisher

IEEE

Cited by 12 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. Machine Learning-Based Kernel Selector for SpMV Optimization in Graph Analysis;ACM Transactions on Parallel Computing;2024-06-08

2. FEASTA: A Flexible and Efficient Accelerator for Sparse Tensor Algebra in Machine Learning;Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 3;2024-04-27

3. Dedicated Hardware Accelerators for Processing of Sparse Matrices and Vectors: A Survey;ACM Transactions on Architecture and Code Optimization;2024-02-15

4. SPADE: A Flexible and Scalable Accelerator for SpMM and SDDMM;Proceedings of the 50th Annual International Symposium on Computer Architecture;2023-06-17

5. A Speed- and Energy-Driven Holistic Training Framework for Sparse CNN Accelerators;2023 Design, Automation & Test in Europe Conference & Exhibition (DATE);2023-04

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