| 引用本文: | 牟卫华,倪少杰,白洋,等.采用向量内积的并行相关算法.[J].国防科技大学学报,2017,39(5):50-55.[点击复制] |
| MOU Weihua,NI Shaojie,BAI Yang,et al.Parallel correlation algorithm based on vector dot product[J].Journal of National University of Defense Technology,2017,39(5):50-55[点击复制] |
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| 采用向量内积的并行相关算法 |
| 牟卫华1,2, 倪少杰1, 白洋3, 孙广富1,2, 欧钢1,2 |
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(1. 国防科技大学 电子科学学院， 湖南 长沙 410073;2.
2. 北斗卫星导航产品2301质量检测中心， 湖南 长沙 410073;3. 空军工程大学 装备管理与安全工程学院， 陕西 西安 710051)
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| 摘要: |
| 针对软件接收机相关器计算的实时性问题，通过分析扩频信号的接收过程，建立一种基于向量内积的并行相关信号接收模型。利用图形处理单元中大量的浮点运算单元进行矩阵与向量运算，并行计算各通道相关值，提高了信号相关运算的实时性。仿真验证结果表明，利用基于GPU的向量内积软件并行相关算法计算25 MHz采样率时长1 ms的信号相关值，25个通道共150个相关运算耗时967 μs，与CPU上基于数学核心函数库的实现相比速度约提高了61.4倍，能够实现宽带扩频信号软件实时相关接收。 |
| 关键词: 相关器 向量内积 软件接收机 并行计算 图形处理单元 |
| DOI：10.11887/j.cn.201705009 |
| 投稿日期：2017-02-15 |
| 基金项目:国家自然科学基金资助项目（41604016） |
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| Parallel correlation algorithm based on vector dot product |
| MOU Weihua1,2, NI Shaojie1, BAI Yang3, SUN Guangfu1,2, OU Gang1,2 |
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(1. College of Electronic Science, National University of Defense Technology, Changsha 410073, China;2.
2. BeiDou Satellite Navigation Product 2301 Quality Testing Center, Changsha 410073, China;3. Equipment Management and Security Engineering College, Air Force Engineering University, Xi′an 710051, China)
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| Abstract: |
| For solving the real-time problem of the software correlator, a parallel receiving model of spread spectrum signal based on vector dot product was proposed. The calculation speed of the signal correlation was improved by parallel computing correlation value of each channel with a large number of ALU in GPU(graphics processing unit). Simulation results show that, 25 channels with 150 correlation computation consume 967 μs in all for 1 ms signal of 25 MHz sampling rate by using the vector dot product parallel correlation algorithms based on GPU. Compared with the implementation on CPU based on MKL(math kernel library), the proposed method speeds up to 61.4 times, and the real-time correlation of the broadband spread spectrum signals in software can be realized. |
| Keywords: correlator vector dot product software receiver parallel computing GPU |
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