首页> 外文期刊>Microwave and optical technology letters >MULTILEVEL FAST MULTIPOLE ALGORITHM ENHANCED BY GPU PARALLEL TECHNIQUE FOR ELECTROMAGNETIC SCATTERING PROBLEMS
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MULTILEVEL FAST MULTIPOLE ALGORITHM ENHANCED BY GPU PARALLEL TECHNIQUE FOR ELECTROMAGNETIC SCATTERING PROBLEMS

机译:GPU并行技术增强的电磁散射问题的多级快速多极算法

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Along with the development of graphics processing Units (GPUS) in floating point operations and programmability, GPU has increasingly become an attractive alternative to the central processing unit (CPU) for some of compute-intensive and parallel tasks. In this article, the multilevel fast multipole algorithm (MLFMA) combined with graphics hardware acceleration technique is applied to analyze electromagnetic scattering from complex target. Although it is possible to perform scattering simulation of electrically large targets on a personal computer (PC) through the MLFMA, a large CPU time is required for the execution of aggregation, translation, and deaggregation operations. Thus GPU computing technique is used for the parallel processing of MLFMA and a significant speedup of matrix vector product (MVP) can be observed. Following the programming model of compute unified device architecture (CUDA), several kernel functions characterized by the single instruction multiple data (SIMD) mode are abstracted from components of the MLFMA and executed by multiple processors of the GPU. Numerical results demonstrate the efficiency of GPU accelerating technique for the MLFMA.
机译:随着浮点运算和可编程性中图形处理单元(GPUS)的发展,对于某些计算密集型和并行任务,GPU逐渐成为中央处理器(CPU)的有吸引力的替代方案。本文将多级快速多极算法(MLFMA)与图形硬件加速技术相结合,用于分析复杂目标的电磁散射。尽管可以通过MLFMA在个人计算机(PC)上对大型电子目标进行散射仿真,但是执行聚合,转换和解聚合操作需要大量的CPU时间。因此,GPU计算技术用于MLFMA的并行处理,并且可以观察到矩阵向量乘积(MVP)的显着加速。遵循计算统一设备体系结构(CUDA)的编程模型,从MLFMA的组件中提取了几个具有单指令多数据(SIMD)模式特征的内核功能,并由GPU的多个处理器执行。数值结果证明了MLFMA GPU加速技术的效率。

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