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GPU-Accelerated Computation of Time-Evolving Electromagnetic Backscattering Field From Large Dynamic Sea Surfaces

机译:GPU加速计算大动态海面延长电磁反向散射场的计算

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An efficient facet-based composite scattering model (FBCSM) is developed for calculating the time-evolving electromagnetic (EM) scattering field (TESF) to study the normalized radar cross section and Doppler spectrum characteristics from dynamic sea surfaces. The dynamic sea surface comprises two-scale profiles: small-scale capillary ripples modulated by large-scale gravity waves, which are modeled by millions of small facets. In microwave bands, two scattering mechanisms, quasi-specular scattering with respect to gravity waves and Bragg scattering with respect to ripples, are taken into account in the FBCSM for computation of the time-evolving EM scattering field under diverse polarizations. However, it may be very time-consuming and difficult to calculate the TESF due to the high resolution and dynamic complexity of the large dynamic sea surface. In this paper, the NVIDIA Tesla K80 graphics processing unit (GPU) with the compute unified device architecture is utilized to improve the computational performance of the TESF. The whole GPU-based TESF computation includes the optimal use of temporary variables, shared memory, constant memory and register, fast-math compiler options, asynchronous data transfer, and the most suitable block size and number of registers. By utilizing the proposed five improvement strategies, a significant speedup of $1200 imes $ can be achieved for computation of TESF from large dynamic sea surfaces for microwave bands compared with the single-threaded C program executed on the Intel(R) Core(TM) i5-3450 CPU.
机译:开发了一种有效的基于面基复合散射模型(FBCSM),用于计算时间不断发展的电磁(EM)散射场(TESF),以研究来自动态海面的标准化雷达横截面和多普勒频谱特性。动态海面包括两刻度的轮廓:由大规模重力波调制的小规模毛细血管涟漪,其由数百万小方面建模。在微波条带中,在FBCSM中考虑了两个散射机构,相对于涟漪相对于涟漪散射散射,用于计算各种偏振下的时间不断发展的EM散射场。然而,由于大动态海面的高分辨率和动态复杂性,它可能会非常耗时且难以计算TESF。本文利用计算统一设备架构的NVIDIA TESLA K80图形处理单元(GPU)来提高TESF的计算性能。基于GPU的TESF计算包括临时变量,共享内存,常量存储器和寄存器,快速数学编译器选项,异步数据传输以及最合适的块大小和寄存器数量的最佳使用。通过利用提出的五种改进策略,可以实现1200美元倍以上的大量加速,以便与在英特尔(R)核心(TM)上执行的单线程C程序相比,从大型动态海面计算微波频带的TESF I5-3450 CPU。

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