@inproceedings{oai:ipsj.ixsq.nii.ac.jp:00216180,
 author = {Yutaro, Kobayashi and Hiroshi, Fujimoto and Takuya, Azumi and Yutaro, Kobayashi and Hiroshi, Fujimoto and Takuya, Azumi},
 book = {Proceedings of Asia Pacific Conference on Robot IoT System Development and Platform},
 month = {Jan},
 note = {Embedded systems, such as automotive systems, are becoming larger and more complex, requiring high computing power and low power consumption. To meet these requirements, multi-/many-core processors and MATLAB/Simulink are increasingly used. Moreover, to support multi-/many-core processors, model-based parallelization tools have been developed. However, the problem of model-based parallelization tools estimated time for each Simulink block has a large error compared to the execution time. Moreover, it is that only hardware information is used to estimate the execution time of parallelized C code. Therefore, the estimation method is proposed to improve the execution time of each Simulink block in comparison with existing methods. Also, a new estimation method is proposed that uses both software and hardware information to estimate the overall execution time. The execution time of the Simulink model is estimated by the conventional method, and the proposed method is measured and compared with the actual execution time to evaluate the proposed method. The experimental results show that the execution time of the parallelized model can be reduced by improving the estimation execution time of each block. It was also found that the use of hardware and software information improved the estimation of the execution time of the parallelized model., Embedded systems, such as automotive systems, are becoming larger and more complex, requiring high computing power and low power consumption. To meet these requirements, multi-/many-core processors and MATLAB/Simulink are increasingly used. Moreover, to support multi-/many-core processors, model-based parallelization tools have been developed. However, the problem of model-based parallelization tools estimated time for each Simulink block has a large error compared to the execution time. Moreover, it is that only hardware information is used to estimate the execution time of parallelized C code. Therefore, the estimation method is proposed to improve the execution time of each Simulink block in comparison with existing methods. Also, a new estimation method is proposed that uses both software and hardware information to estimate the overall execution time. The execution time of the Simulink model is estimated by the conventional method, and the proposed method is measured and compared with the actual execution time to evaluate the proposed method. The experimental results show that the execution time of the parallelized model can be reduced by improving the estimation execution time of each block. It was also found that the use of hardware and software information improved the estimation of the execution time of the parallelized model.},
 pages = {21--28},
 publisher = {情報処理学会},
 title = {Performance Estimation for Embedded Many-core Processor with Software/Hardware Performance Description},
 volume = {2021},
 year = {2022}
}