Skip to content
Log in
Sponsored AI AM CLAUDE, A Beginner's Guide: Learn the basics of working with AI AI AM CLAUDE, A Beginner's Guide: Learn the basics of working with AI

Author

Sheng-Le Lin

h-index 3 View on Semantic Scholar

We have 3 of 10 papers

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

Nov 2026

SSpMV: A Sparsity-Aware Framework for Adaptive Sparse Matrix–Vector Multiplication

Sparse Matrix-Vector Multiplication (SpMV) is a fundamental sparse kernel in both scientific computing and artificial intelligence. However, the performance of existing SpMV algorithms is highly sensitive to diverse sparsity patterns, necessitating an adaptive framework that can effectively extract matrix structures an...

Guoqing Xiao, Shi-Jie Zhao, Qin Du et al. · 0 citations
Book Open access Sep 2026

CoTC-SpMM: A Cooperative Tensor–CUDA Cores Scheme for Efficient Sparse Matrix Multiplication

CoTC-SpMM is introduced, a cooperative Tensor–CUDA cores scheme for efficient SpMM on GPUs that first proposes the HTC format to partition sparse matrices into dense and sparse components, enabling specialized kernels to leverage the distinct advantages of different computing units and maximize hardware utilization.

Qi Du, Sheng-Le Lin, Yue-Dan Chen et al. · 0 citations
Book Open access Sep 2026

CoTC-SpMM: A Cooperative Tensor–CUDA Cores Scheme for Efficient Sparse Matrix Multiplication

Sparse Matrix-Matrix Multiplication (SpMM) is a fundamental operation in scientific computing and artificial intelligence. However, the inherent sparsity and irregularity of real-world datasets present significant challenges for developing high-performance SpMM kernels on modern GPUs. Existing approaches typically focu...

Qi Du, Shengle Lin, Yuedan Chen et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.