基于GPU的并行MSD算法研究
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摘要
通用计算机的遥测信号处理系统通用性、灵活性强,不受硬件平台限制,便于开发、升级和维护,能够有效克服传统硬件平台的不足。多符号检测(MSD)算法性能优良,具有计算量大、并行度高的特点,适合在通用计算机上进行处理。针对如何提高处理速度,在通用计算机平台上研究基于图形处理器(GPU)的并行MSD算法,通过使用GPU对MSD算法并行加速,提高算法运算效率。实验结果表明,在同样条件下,基于GPU的并行MSD算法较串行算法最大可提速约134倍,能够有效提高处理速度。
The telemetry signal processing system based on general-purpose computer has multiple advantages which can effectively overcome the shortcomings of current hardware devices,such as high versatility and flexibility,low cost,no limits of hardware platform,and easy upgrade and maintenance. The multi-symbol detection( MSD) algorithm has such characteristics as large computing and high parallelism and better performance,and it is suitable for processing on a general-purpose computer. For the method to improve processing efficiency,this paper studies parallel MSD algorithm based on GPU on general-purpose computer platform. The results show that the processing speed of parallel MSD algorithm is about 134 times higher than sequential algorithm.
The telemetry signal processing system based on general-purpose computer has multiple advantages which can effectively overcome the shortcomings of current hardware devices,such as high versatility and flexibility,low cost,no limits of hardware platform,and easy upgrade and maintenance. The multi-symbol detection( MSD) algorithm has such characteristics as large computing and high parallelism and better performance,and it is suitable for processing on a general-purpose computer. For the method to improve processing efficiency,this paper studies parallel MSD algorithm based on GPU on general-purpose computer platform. The results show that the processing speed of parallel MSD algorithm is about 134 times higher than sequential algorithm.
引文
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[2]RICE M,SATORIUS E.Equalization Techniques for Multipath Mitigation in Aeronautical Telemetry[C]∥Military Communications Conference.MILCOM.IEEE,2004:65-70.
[3]盛骤,谢式千,潘承毅.概率论与数理统计(第4版)[M].北京:高等教育出版社,2010.
[4]刘毅.CPM信号载波同步研究[D].西安:西安电子科技大学,2008.
[5]刘培志,宿红毅,罗壮,等.面向海量数据高性能计算的cpu/gpu协同处理方法[P].中国:CN102708088 A,2012.
[6]赵炳财.基于GPU技术的并行运算应用研究[D].长沙:国防科学技术大学,2012.
[7]张舒,褚艳利.GPU高性能运算之CUDA[M].北京:中国水利水电出版社,2009.
[8]李梓博,侯孝民,郑海昕,等.基于MSD的PCM/FM信号解调参数性能研究[J].无线电工程,2014,(8):38-40.