A comprehensive and effective parallel airborne synthetic aperture radar (SAR) processing system using the architecture of central processing units (CPU) and graphical processing units (GPU) is proposed first in this paper. By using the techniques of Compute Unified Device Architecture, the SAR processing system is much more efficient and robust, thereby enabling it to work with high efficiency. This paper focuses on the optimizations of motion compensation, subaperture chirp scaling algorithm, phase gradient autofocus (PGA), and even visualization with Open Source Computer Vision Library. Apart from this, it is also the first time the PGA has been run on the architecture of CPU and GPU. Experimental results show a speedup of times compared with a nonoptimized CPU-based approach.