Author:
Ohshima Satoshi,Katagiri Takahiro,Matsumoto Masaharu
Cited by
8 articles.
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1. Optimal Scheduling for the Performance Optimization of SpMV Computation using Machine Learning Techniques;2024 7th International Conference on Information and Computer Technologies (ICICT);2024-03-15
2. Efficiently Running SpMV on Multi-Core DSPs for Block Sparse Matrix;2023 IEEE 29th International Conference on Parallel and Distributed Systems (ICPADS);2023-12-17
3. Efficient and High-Performance Sparse Matrix-Vector Multiplication on a Many-Core Array;2022 IEEE 15th International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC);2022-12
4. Research on Accelerating the Performance of SpMV Based on AVX2 Instruction Set;Proceedings of the 2020 4th High Performance Computing and Cluster Technologies Conference & 2020 3rd International Conference on Big Data and Artificial Intelligence;2020-07-03
5. Towards an Auto-Tuned and Task-Based SpMV (LASs Library);OpenMP: Portable Multi-Level Parallelism on Modern Systems;2020