high performance computing on graphics processing units: hgpu.org

In this paper, there are depicted optimization solutions for the segmented sum algorithmic function, developed using the Compute Unified Device Architecture (CUDA), a powerful and efficient solution for optimizing a wide range of applications. The parallel-segmented sum is often used in building many data processing algorithms and through its optimization, one can improve the overall performance of these algorithms. In order to evaluate the usefulness of the optimization solutions and the performance of the developed segmented sum algorithmic function, I benchmark this function and analyse the obtained experimental results.