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A Unified Sparse Matrix Data Format for Efficient General Sparse Matrix-Vector Multiplication on Modern Processors with Wide SIMD Units

  • Published:2014-01 Issue:5 Volume:36 Page:C401-C423
  • ISSN:1064-8275
  • Container-title:SIAM Journal on Scientific Computing
  • language:en
  • Short-container-title:SIAM J. Sci. Comput.

Author:

Kreutzer Moritz,Hager Georg,Wellein Gerhard,Fehske Holger,Bishop Alan R.

Publisher

Society for Industrial & Applied Mathematics (SIAM)

Subject

Applied Mathematics,Computational Mathematics

Cited by 153 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. Sparse Matrix-Vector Multiplication with Reduced-Precision Memory Accessor;2023 IEEE 16th International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC);2023-12-18

2. DASP: Specific Dense Matrix Multiply-Accumulate Units Accelerated General Sparse Matrix-Vector Multiplication;Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis;2023-11-11

3. HASpMV: Heterogeneity-Aware Sparse Matrix-Vector Multiplication on Modern Asymmetric Multicore Processors;2023 IEEE International Conference on Cluster Computing (CLUSTER);2023-10-31

4. Development of an unstructured mesh gyrokinetic particle-in-cell code for exascale fusion plasma simulations on GPUs;Computer Physics Communications;2023-10

5. Orthogonal Layers of Parallelism in Large-Scale Eigenvalue Computations;ACM Transactions on Parallel Computing;2023-09-22
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