| 奇异值分解算法优化 |
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| 引用本文： | 王佰玲,田志宏,张永铮.奇异值分解算法优化[J].电子学报,2010,38(10):2234-2239. |
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| 作者姓名： | 王佰玲 田志宏 张永铮 |
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| 作者单位： | 1. 北京大学信息科学与技术学院,北京 100871;2. 哈尔滨工业大学计算机学院,黑龙江哈尔滨 150001;3. 中国科学院计算技术研究所,北京 100190 |
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| 摘 要： | 奇异值分解算法在信号处理、图像处理、信息安全等领域均有重要应用.针对该算法存在的性能问题,提出了基于gamma:1驱动的数据重用模型,提高计算负载平衡性,降低数据通信量;给出基于多处理器的并行分解模型,数值试验均表明算法具有较高的并行加速比和效率.
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| 关 键 词： | 数据挖掘 文本聚类 奇异值分解 矩阵计算 |
| 收稿时间： | 2009-02-16 |
Optimization of Singular Vector Decomposition Algorithm |
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| WANG Bai-ling,TIAN Zhi-hong,ZHANG Yong-zheng.Optimization of Singular Vector Decomposition Algorithm[J].Acta Electronica Sinica,2010,38(10):2234-2239. |
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| Authors: | WANG Bai-ling TIAN Zhi-hong ZHANG Yong-zheng |
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| Affiliation: | 1. Scholl of Electronics Engineering and Computer Science,Peking University,Beijing 100871,China;2. School of Computer Science and Technology,Harbin Institute of Technology,Harbin,Heilongjiang 150001,China;3. Institute of Computing Technology,Chinese Academy of Sciences,Beijing 100190,China |
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| Abstract: | Singular Vector Decomposition(SVD) has been used in signal processing,image computing,information security,and etc.In order to improve the performance of SVD,proposed a gamma:1 computing model to reuse matrix data to increase data load balance and decrease data communication;and a multi-core based parallelized computing model is given to increase the performance and expendability.At last,a prototype on a multi-core processor was implemented.The result demonstrates the accuracy of the proposed algorithm and ... |
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| Keywords: | data mining document clustering singular vector decomposition matrix computing |
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