Research Article
Optimization Bottleneck Analysis in GPU-Based Aiming at SAR Imaging
@INPROCEEDINGS{10.1007/978-3-319-60753-5_5, author={Wang Shi-Yu and Zhang Sheng-Bing and An Jian-Feng and Huang Xiao-Ping and Wang Dang-Hui}, title={Optimization Bottleneck Analysis in GPU-Based Aiming at SAR Imaging}, proceedings={Industrial IoT Technologies and Applications. Second EAI International Conference, Industrial IoT 2017, Wuhu, China, March 25--26, 2017, Proceedings}, proceedings_a={INDUSTRIALIOT}, year={2017}, month={9}, keywords={GPU SAR imaging Parallel computing Optimization bottleneck analysis}, doi={10.1007/978-3-319-60753-5_5} }- Wang Shi-Yu
Zhang Sheng-Bing
An Jian-Feng
Huang Xiao-Ping
Wang Dang-Hui
Year: 2017
Optimization Bottleneck Analysis in GPU-Based Aiming at SAR Imaging
INDUSTRIALIOT
Springer
DOI: 10.1007/978-3-319-60753-5_5
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.