Primary purpose of graphics processing unit is computer graphics, that is processing images and videos. Graphics processing unit is made of many processing elements which have the ability to do diverse computations. Although the central processing unit is faster in executing one computational operation due to it's higher clock speed, the GPU is the one that can do many operations simultaneously. The ability of parallel execution of tasks and computation makes the GPU useful outside of the area of computer graphics. One of the ways to use the graphics processing unit is OpenCL. OpenCL is a framework used for writing code which can be executed on multiple devices like the GPU, FPGA and even CPU. OpenCL can be used for both task and data parallelism. OpenCL code is written in two parts, the host and kernel code. The kernel is part of the code which can be parallelized. OpenCL kernels are written in OpenCL C programming language which differs from standard C due to some built in functions and extra data types. The rest of the code can be written either in C or C++ languages. The host code is executed on the CPU, and the kernel is executed on the chosen accelerator. OpenCL shouldn't be used for simple tasks or tasks which don't need a whole lot of data. Most of those tasks can be easily written and executed in standard C. OpenCL should be used in tasks that are data heavy, where one set of instructions needs to be done on a large set of data. For example calculating the value of elements of a matrixs with dimensions of 1600x1600. The parameters of the GPU seemingly do not affect the performance of the program, but after comparing the time needed to run the kernel on the GPU it is shown that the adaptive power management, low latency and the use of the shader cache are favorable.