Accelerating and Characterizing Seam Carving Using a Heterogeneous CPU-GPU System
Department of Electrical, Computer, and Biomedical Engineering, University of Rhode Island, Kingston, RI, USA
The 2012 International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA’12), 2012
Seam carving has been widely used for contentaware resizing of images and videos with little to no perceptible distortion. Unfortunately, for high-resolution videos and large images it becomes computationally unfeasible to do the resizing in real-time using small-scale CPU systems. In this paper, we exploit the highly parallel computational capabilities of CUDA-enabled Graphics Processing Units (GPUs) for accelerating the content-aware resizing of videos and images. The performance results show that our implementation of the seam carving algorithm achieves up to 100x and 14x speed-ups on the computationally-intensive part of the algorithm compared to the faster single-threaded and the faster multithreaded CPU implementations, respectively, on the systems tested. The overall resizing operation is over 6x and 2x faster than the best single-threaded and multithreaded CPU implementations, respectively, which demonstrates the potential to resize videos and large images in real-time.
September 5, 2012 by hgpu
