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

標題:GPU acceleration of predictive partitioned vector quantization for ultraspectral sounder data compression
學年100
學期1
出版(發表)日期2011/09/01
作品名稱GPU acceleration of predictive partitioned vector quantization for ultraspectral sounder data compression
作品名稱(其他語言)
著者Wei, Shih-chieh; Huang, Bormin
單位淡江大學資訊管理學系
出版者Piscataway: Institute of Electrical and Electronics Engineers
著錄名稱、卷期、頁數IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 4(3), pp.677-682
摘要For the large-volume ultraspectral sounder data, compression is desirable to save storage space and transmission time. To retrieve the geophysical paramters without losing precision the ultraspectral sounder data compression has to be lossless. Recently there is a boom on the use of graphic processor units (GPU) for speedup of scientific computations. By identifying the time dominant portions of the code that can be executed in parallel, significant speedup can be achieved by using GPU. Predictive partitioned vector quantization (PPVQ) has been proven to be an effective lossless compression scheme for ultraspectral sounder data. It consists of linear prediction, bit depth partitioning, vector quantization, and entropy coding. Two most time consuming stages of linear prediction and vector quantization are chosen for GPU-based implementation. By exploiting the data parallel characteristics of these two stages, a spatial division design shows a speedup of 72x in our four-GPU-based implementation of the PPVQ compression scheme.
關鍵字Graphics processing unit;Vector quantization;Training;Instruction sets;Vectors;Kernel;Pixel
語言英文(美國)
ISSN1939-1404;2151-1535
期刊性質國外
收錄於SCI;
產學合作
通訊作者Huang, Bormin
審稿制度
國別美國
公開徵稿
出版型式,電子版,紙本
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