• 中国精品科技期刊
  • CCF推荐A类中文期刊
  • 计算领域高质量科技期刊T1类
Advanced Search
Song Lihua, Guo Yanfei, Wang Qin. Algorithm-Level Low-Power Technology for the Channel Decoding Coprocessor of the Network Processor[J]. Journal of Computer Research and Development, 2012, 49(8): 1641-1648.
Citation: Song Lihua, Guo Yanfei, Wang Qin. Algorithm-Level Low-Power Technology for the Channel Decoding Coprocessor of the Network Processor[J]. Journal of Computer Research and Development, 2012, 49(8): 1641-1648.

Algorithm-Level Low-Power Technology for the Channel Decoding Coprocessor of the Network Processor

More Information
  • Published Date: August 14, 2012
  • In this paper, a new low power reed-solomon decoding algorithm (LP-RSA) is proposed, with the scenario that the RS decoder is integrated as a coprocessor of network processor. The proposed LP-RSA could dynamically judge the number of error symbols in advance and then close the unnecessary polynomial operations as soon as possible. By inserting the dynamic error pre-judgment circuit, the implemented coprocessor of RS decoder, which complies with the proposed LP-RSA, could turn the unnecessary processing circuits into sleep status to prevent the unavailable toggling of them and reduce the power of the coprocessor of RS decoder as well as the power of network processor. Under the same testing environment, the proposed LP-RSA allows the RS coprocessor achieving about 66.1% gain in power saving. At the same time, the proposed algorithm will help to extend the application range of network processor in the communication system with low power characteristic.
  • Related Articles

    [1]Pan Xuan, Xu Sihan, Cai Xiangrui, Wen Yanlong, Yuan Xiaojie. Survey on Deep Learning Based Natural Language Interface to Database[J]. Journal of Computer Research and Development, 2021, 58(9): 1925-1950. DOI: 10.7544/issn1000-1239.2021.20200209
    [2]Li Yin. Test Suite Generating for Stateful Web Services Using Interface Contract[J]. Journal of Computer Research and Development, 2017, 54(3): 609-622. DOI: 10.7544/issn1000-1239.2017.20151045
    [3]Dong Yongquan, Li Qingzhong, Ding Yanhui, Peng Zhaohui. Constrained Conditional Random Fields for Semantic Annotation of Web Data[J]. Journal of Computer Research and Development, 2012, 49(2): 361-371.
    [4]Tian Jianwei and Li Shijun. Retrieving Deep Web Data Based on Hierarchy Tree Model[J]. Journal of Computer Research and Development, 2011, 48(1): 94-102.
    [5]Kou Yue, Li Dong, Shen Derong, Yu Ge, Nie Tiezheng. D-EEM: A DOM-Tree Based Entity Extraction Mechanism for Deep Web[J]. Journal of Computer Research and Development, 2010, 47(5): 858-865.
    [6]Ding Guohui, Wang Guoren, and Zhao Yuhai. Multi-Schema Integration Based on Usage and Clustering Approach[J]. Journal of Computer Research and Development, 2010, 47(5): 824-831.
    [7]Shen Derong, Ma Ye, Nie Tiezheng, Kou Yue, and Yu Ge. A Query Relaxation Strategy Applied in a Deep Web Data Integration System[J]. Journal of Computer Research and Development, 2010, 47(1): 88-95.
    [8]Ma Anxiang, Zhang Bin, Gao Kening, Qi Peng, and Zhang Yin. Deep Web Data Extraction Based on Result Pattern[J]. Journal of Computer Research and Development, 2009, 46(2): 280-288.
    [9]Qu Yuzhong, Hu Wei, Zheng Dongdong, and Zhong Xinyu. Mapping Between Relational Database Schemas and Ontologies: The State of the Art[J]. Journal of Computer Research and Development, 2008, 45(2): 300-309.
    [10]Zhang Weiming and Song Junfeng. Study on Domain Ontology Representation, Reasoning and Integration for the Semantic Web[J]. Journal of Computer Research and Development, 2006, 43(1): 101-108.

Catalog

    Article views (720) PDF downloads (587) Cited by()

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return