教師資料查詢 | 類別: 會議論文 | 教師: 魏世杰 Wei Shih-chieh (瀏覽個人網頁)

標題: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
語言英文
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
國別加拿大
公開徵稿Y
出版型式
出處Geoscience and Remote Sensing Symposium (IGARSS), 2011 IEEE International, pp.221-224
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