With technological advancements, the volume of data to be processed is rapidly increasing. Image-based data, in particular, require significant computational resources, slowing down processing. This study investigates the efficiency of parallel image filtering on large-scale data using GPU. Filtering was performed in parallel on an NVIDIA graphics processor with CUDA technology, and results were compared to sequential CPU processing. The study shows that GPU-based processing with CUDA significantly outperforms CPU execution, achieving up to ~235 times faster performance for large images. These results confirm the high efficiency of GPU and CUDA technology for image processing.
Javliev et al. (Thu,) studied this question.