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GPU Acceleration of Graph Algorithms
Lorenc, David ; Andriushchenko, Roman (referee) ; Češka, Milan (advisor)
In this bachelor thesis, I will deal with the acceleration of the Breadth-first search (BFS) algorithm on a graphics card. This is an algorithm designed to traverse the graph in breadth. I will explain the basic parallelization techniques divided according to Flynn’s classification. I will also discuss the existing methods of parallelizing BFS on GPU. I will then perform structured experiments of all approaches on the same dataset, compare and evaluate the results. It is very difficult for someone new to the field to navigate through it, due to its vastness, I wanted to create a work that will guide a programmer new to parallelization on GPUs and give them an easier insight into the subject. Furthermore, I focused on structured testing of different approaches from different works and evaluated them for the sake of reviewing the performance of the approaches in one place. Thus, the reader can see which one is most suitable for his/her need. A clear explanation of the theory behind parallelization techniques and problems, and a description of the hardware and software concepts of NVDIA Cuda. An introduction to the possibilities of representing graphs in memory and an explanation of why graph representation using a neighborhood list is used. Description of the different approaches and their testing, based on the results of the evaluation of the effectiveness of the approaches.
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