Parallel Algorithm of Harris Corner Detection Based on Multi-GPU

Parallel algorithm of Harris corner detection based on the core concept of Multi-GPU is proposed,so that time-consuming Gaussian image convolution filtering part during the whole image corner detection process can be implemented by many parallel threads.Finally,implementation of this SIMT parallel algorithm using GPU mechanism of shared memory and constant memory and pinned host memory in CUDA is detailed.The Experiments show that the parallel algorithm of Harris corner detection based on Multi-GPU demonstrates substantial improvement up to 60 times speedup than the serial algorithm running in the CPU,is with high efficiency compared with CPU counterpart algorithm,and show great potential for large-scale data processing in real-time processing.