Study and evaluation of automatic offloading method in mixed offloading destination environment
Heterogeneous hardware other than a small-core central processing unit (CPU) such as a graphics processing unit (GPU), field-programmable gate array (FPGA), or multi-core CPU is increasingly being used. However, to use heterogeneous hardware, programmers must have sufficient technical skills to util...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2022-12-01
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| Series: | Cogent Engineering |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/23311916.2022.2080624 |
| _version_ | 1797758270267457536 |
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| author | Yoji Yamato |
| author_facet | Yoji Yamato |
| author_sort | Yoji Yamato |
| collection | DOAJ |
| description | Heterogeneous hardware other than a small-core central processing unit (CPU) such as a graphics processing unit (GPU), field-programmable gate array (FPGA), or multi-core CPU is increasingly being used. However, to use heterogeneous hardware, programmers must have sufficient technical skills to utilize OpenMP, CUDA, and OpenCL. On the basis of this, we have proposed an environment-adaptive software that enables automatic conversion, configuration, and high-performance operation of once written code, in accordance with the hardware to be placed. However, no techniques have been developed to properly and automatically offload applications in the mixed offloading destination environment such as GPU, FPGA, and multi-core CPU. In this paper, for a new element of environment-adaptive software, we study a method for offloading applications properly and automatically in an environment where the offloading destination is a mix of GPU, FPGA, and multi-core CPU. We evaluate the effectiveness of the proposed method in multiple applications. |
| first_indexed | 2024-03-12T18:27:36Z |
| format | Article |
| id | doaj.art-fc93ee53248b4538a0d6661f209e2947 |
| institution | Directory Open Access Journal |
| issn | 2331-1916 |
| language | English |
| last_indexed | 2024-03-12T18:27:36Z |
| publishDate | 2022-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Cogent Engineering |
| spelling | doaj.art-fc93ee53248b4538a0d6661f209e29472023-08-02T08:28:52ZengTaylor & Francis GroupCogent Engineering2331-19162022-12-019110.1080/23311916.2022.2080624Study and evaluation of automatic offloading method in mixed offloading destination environmentYoji Yamato0Network Service Systems Laboratories, NTT Corporation, 3-9-11 Midori-cho, Musashino-shi, Tokyo 180-8585, JapanHeterogeneous hardware other than a small-core central processing unit (CPU) such as a graphics processing unit (GPU), field-programmable gate array (FPGA), or multi-core CPU is increasingly being used. However, to use heterogeneous hardware, programmers must have sufficient technical skills to utilize OpenMP, CUDA, and OpenCL. On the basis of this, we have proposed an environment-adaptive software that enables automatic conversion, configuration, and high-performance operation of once written code, in accordance with the hardware to be placed. However, no techniques have been developed to properly and automatically offload applications in the mixed offloading destination environment such as GPU, FPGA, and multi-core CPU. In this paper, for a new element of environment-adaptive software, we study a method for offloading applications properly and automatically in an environment where the offloading destination is a mix of GPU, FPGA, and multi-core CPU. We evaluate the effectiveness of the proposed method in multiple applications.https://www.tandfonline.com/doi/10.1080/23311916.2022.2080624Environment-adaptive softwareGPGPUFPGAautomatic offloadingevolutionary computationmixed offloading destination environment |
| spellingShingle | Yoji Yamato Study and evaluation of automatic offloading method in mixed offloading destination environment Cogent Engineering Environment-adaptive software GPGPU FPGA automatic offloading evolutionary computation mixed offloading destination environment |
| title | Study and evaluation of automatic offloading method in mixed offloading destination environment |
| title_full | Study and evaluation of automatic offloading method in mixed offloading destination environment |
| title_fullStr | Study and evaluation of automatic offloading method in mixed offloading destination environment |
| title_full_unstemmed | Study and evaluation of automatic offloading method in mixed offloading destination environment |
| title_short | Study and evaluation of automatic offloading method in mixed offloading destination environment |
| title_sort | study and evaluation of automatic offloading method in mixed offloading destination environment |
| topic | Environment-adaptive software GPGPU FPGA automatic offloading evolutionary computation mixed offloading destination environment |
| url | https://www.tandfonline.com/doi/10.1080/23311916.2022.2080624 |
| work_keys_str_mv | AT yojiyamato studyandevaluationofautomaticoffloadingmethodinmixedoffloadingdestinationenvironment |