Accelereating cell image analysis with GPU

OData support
Supervisor:
Szántó Péter
Department of Measurement and Information Systems

Imageprocessing is used widely in the industry. Many imageprocessing supporting program exist. The Graphics Processing Unit (GPU) is used to take over the graphical jobs from the CPU. This algorithms can be processed parallel very effectively. The programming of GPU-s for any algorithm became a reality some year ago. This paper writes about how to write a program for GPU with the OpenCL engine to reach better run time. Also discuss the structure and memory types of GPU. You can also read about debugging technics of OpenCL code, and how to optimize your OpenCL code. The paper contains some GPU implemented algorithms. It is a real possibility in the future that image processing supporter programs will use GPU to reach very fast work speed.

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