Optimization bottleneck analysis in GPU-based aiming at SAR imaging

Abstract

Application Defect induced by GPU Aiming at SAR Imaging are studied. It is the first time the issue of application defect induced by GPU is addressed in SAR field. In GPU-based SAR imaging system, application defect induced by resources competition can significantly decrease the granularity of parallelism. To solve this problem, the GPU-based SAR imaging system with CUDA is firstly modeled. Secondly, conditions of parallel granularity loss rate by using CUDA are obtained based on time output feedback scheme. Thirdly, more importantly, find the difficulties and bottlenecks in the optimization of SAR imaging operation is proposed according to the measured conditions of parallel granularity loss rate. Finally, optimization bottleneck analysis through FFT function and linear matrix interpolation scheme, and numerical simulations are made to demonstrate the effectiveness of the proposed scheme.