| GPU-based spatially divided predictive partitioned vector quantization for gifts ultraspectral data compression | |
|---|---|
| 學年 | 99 |
| 學期 | 2 |
| 發表日期 | 2011-07-24 |
| 作品名稱 | GPU-based spatially divided predictive partitioned vector quantization for gifts ultraspectral data compression |
| 作品名稱（其他語言） | |
| 著者 | Wei, Shih-chieh; Huang, Bormin |
| 作品所屬單位 | 淡江大學資訊管理學系 |
| 出版者 | IEEE Geosicence and Remote Sensing Society |
| 會議名稱 | Geoscience and Remote Sensing Symposium (IGARSS), 2011 IEEE International |
| 會議地點 | Vancouver, Canada |
| 摘要 | Predictive partitioned vector quantization (PPVQ) has been proven to be an effective lossless compression scheme for ultraspectral sounder data. In previous work, we have identified the two most time-consuming stages of PPVQ for implementation on GPU. By using 4 GPUs and a spectral division design in sharing the workload, we showed a 42x speedup on NASA's Geostationary Imaging Fourier Transform Spectrometer (GIFTS) dataset compared to its original single-threaded CPU code. In this paper, an alternative spatial division design is developed to run on 4 GPUs. The experiment on the GIFTS dataset shows that a 72x speedup can be further achieved by this new design of the GPU-based PPVQ compression scheme. |
| 關鍵字 | GIFTS sounder data;Graphic processor unit;data compression |
| 語言 | en |
| 收錄於 | |
| 會議性質 | 國際 |
| 校內研討會地點 | |
| 研討會時間 | 20110724~20110729 |
| 通訊作者 | |
| 國別 | CAN |
| 公開徵稿 | Y |
| 出版型式 | |
| 出處 | Geoscience and Remote Sensing Symposium (IGARSS), 2011 IEEE International, pp.221-224 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/62343 ) |
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