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March 28, 20260 citationsOpen Access

Accelerating Image Filtering Processes on Nvidia Graphics Processor Using Cuda Technology

SJShakhzod JavlievTashkent University of Information Technology KTKhurshid TuraevTashkent University of Information Technology

Key Points

The aim is to evaluate the efficiency of parallel image filtering on large-scale data using GPU technology.
Parallel filtering performed on an NVIDIA graphics processor using CUDA.
Comparison made with sequential processing on a CPU.
Performance metrics evaluated based on execution speed.
GPU-based processing achieved up to ~235 times faster performance than CPU processing.
High efficiency of GPU and CUDA technology for large image processing confirmed.

Abstract

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.

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