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GPUによる相互相関PIVの高速化に関する研究
http://hdl.handle.net/2261/48987
http://hdl.handle.net/2261/48987dcf2511f-1463-4bc8-b2b6-e8bdfa831f51
| 名前 / ファイル | ライセンス | アクション |
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本文(fulltext) (3.9 MB)
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要旨(summary) (585.1 kB)
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| Item type | 学位論文 / Thesis or Dissertation(1) | |||||
|---|---|---|---|---|---|---|
| 公開日 | 2012-10-12 | |||||
| タイトル | ||||||
| タイトル | GPUによる相互相関PIVの高速化に関する研究 | |||||
| 言語 | ||||||
| 言語 | jpn | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | Direct cross-correlation PIV | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | FFT-based cross correlation PIV | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | Hybrid cross-correlation PIV | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | GPGPU | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | Multi-GPU | |||||
| 資源タイプ | ||||||
| 資源 | http://purl.org/coar/resource_type/c_46ec | |||||
| タイプ | thesis | |||||
| 著者 |
田良島, 周平
× 田良島, 周平 |
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| 著者別名 | ||||||
| 識別子Scheme | WEKO | |||||
| 識別子 | 9014 | |||||
| 姓名 | タラシマ, シュウヘイ | |||||
| 著者所属 | ||||||
| 著者所属 | 東京大学大学院新領域創成科学研究科環境学研究系人間環境学専攻 | |||||
| 著者所属 | ||||||
| 著者所属 | Department of Human and Engineered Environmental Studies, Graduate School of Frontier Sciences, The University of Tokyo | |||||
| Abstract | ||||||
| 内容記述タイプ | Abstract | |||||
| 内容記述 | This study aims to develop a fast Particle Image Velocimetry (PIV) software by Graphics Processing Unit(GPU). This summary consists of 3 parts. In the first part, the methods to accelerate recursive direct/FFT-based cross-correlation PIV by GPU are discussed. After the comparison, GPU accelerated cross-correlation PIVs are implemented on GPU and about 800 times faster processing is achieved compared to using single CPU. In the second part, the methods to accelerate these PIVs by multiple GPUs (multi-GPU) are also discussed. By parallelizing single GPU accelerated PIV by multi-GPU, about 85% of the theoretical performance can be obtained compared to using single GPU. In the third part, recursive hybrid cross-correlation PIV scheme is proposed, which uses FFT-based method in the former step and use direct method in the latter step. Real PIV images are used to validate hybrid cross-correlation PIV and the advantages in terms of its range, precision, and time cost are shown. | |||||
| 書誌情報 | 発行日 2011-03-24 | |||||
| 日本十進分類法 | ||||||
| 主題Scheme | NDC | |||||
| 主題 | 547 | |||||
| 学位名 | ||||||
| 学位名 | 修士(環境学) | |||||
| 学位 | ||||||
| 値 | master | |||||
| 研究科・専攻 | ||||||
| 新領域創成科学研究科環境学研究系人間環境学専攻 | ||||||
| 学位授与年月日 | ||||||
| 学位授与年月日 | 2011-03-24 | |||||
| 学位記番号 | ||||||
| 修創域第3976号 | ||||||
