CSR5
Author:
Affiliation:
1. University of Copenhagen, Copenhagen, Denmark
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/2751205.2751209
Reference31 articles.
1. Fast Sparse Matrix-Vector Multiplication on GPUs for Graph Applications
2. An efficient two-dimensional blocking strategy for sparse matrix-vector multiplication on GPUs
3. Implementing sparse matrix-vector multiplication on throughput-oriented processors
4. Reduced-Bandwidth Multithreaded Algorithms for Sparse Matrix-Vector Multiplication
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1. Automatically optimized component model computation for power system simulation on GPU;Electric Power Systems Research;2024-10
2. Bitmap-Based Sparse Matrix-Vector Multiplication with Tensor Cores;Proceedings of the 53rd International Conference on Parallel Processing;2024-08-12
3. CAMLB-SpMV: An Efficient Cache-Aware Memory Load-Balancing SpMV on CPU;Proceedings of the 53rd International Conference on Parallel Processing;2024-08-12
4. SuperCSR: A Space-Time-Efficient CSR Representation for Large-scale Graph Applications on Supercomputers;Proceedings of the 53rd International Conference on Parallel Processing;2024-08-12
5. Implementation and optimization of SpMV algorithm based on SW26010P many-core processor and stored in BCSR format;Scientific Reports;2024-07-17
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