基于GPU架构的SAR回波仿真实现与优化

为了能够有效提高基于时域的SAR回波仿真的运行速度，本文提出了一种基于GPU架构的SAR回波仿真优化实现方法。该方法结合GPU的计算密度高、高度并行的特点并利用CUDA流在GPU上同时执行多个任务，实现任务并行、指令并行和数据并行的三重并行，极大地挖掘了回波模拟全过程的并行性，缩短了回波仿真的运算时间。实验结果表明，该方法相对于传统的CPU上的串行算法平均加速比达到128倍，可用于实时信号处理。

Implementation And Optimization Of SAR Echo Simulation Based on GPU

To enhance the computational efficiency of SAR echo data simulation, an efficient raw echo data simulation method for SAR is presented in this paper. Combining the characteristics of high computation density, high parallelism and CUDA stream , this method achieves tasks parallelism, instructions parallelism and data parallelism, which largely exploited the parallelism in SAR echo simulation and shortened computing time. The results show that this method obtain the speedup about 128 times compared with CPU. And the method is suitable for real-time signal processing.