LightSpMV: Faster CSR-based sparse matrix-vector multiplication on CUDA-enabled GPUs-Reference-Cited by-同舟云学术

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LightSpMV: Faster CSR-based sparse matrix-vector multiplication on CUDA-enabled GPUs

Published:2015-07 Issue: Volume: Page:
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Container-title:2015 IEEE 26th International Conference on Application-specific Systems, Architectures and Processors (ASAP)
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Author:

Liu Yongchao,Schmidt Bertil

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/7227129/7245687/07245713.pdf?arnumber=7245713

Cited by 35 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. Bitmap-Based Sparse Matrix-Vector Multiplication with Tensor Cores;Proceedings of the 53rd International Conference on Parallel Processing;2024-08-12

2. VNEC: A Vectorized Non-Empty Column Format for SpMV on CPUs;2024 IEEE International Parallel and Distributed Processing Symposium (IPDPS);2024-05-27

3. Revisiting thread configuration of SpMV kernels on GPU: A machine learning based approach;Journal of Parallel and Distributed Computing;2024-03

4. Efficiently Running SpMV on Multi-core DSPs for Banded Matrix;Lecture Notes in Computer Science;2024

5. G-Sparse: Compiler-Driven Acceleration for Generalized Sparse Computation for Graph Neural Networks on Modern GPUs;2023 32nd International Conference on Parallel Architectures and Compilation Techniques (PACT);2023-10-21

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