FAST LOCAL FLOW-BASED METHOD USING PARALLEL MULTI-CORE CPUS ARCHITECTURE - Moneim, Wafaa Abdel; Salem, Rashed; Hassan, Mohamed (Institute of Advanced Engineering and Science, 2020)
Large graphs are available in everywhere such as social networks, chemistry, web link analysis, biology, image processing, and computer networks. Traditional methods of clustering are not suitable to solve this problem due to the computation is very costly. This problem is solved by local graph clustering using a given vertex set as input without working on the complete graph to detect a good cluster. SimpleLocal is introduced and analyzed for locally-biased graph-based learning. This algorithm detects a best conductance cuts close to seed vertices set. In this paper, a new Parallel SimpleLocal (PSL) system is proposed using multi-core CPUs. OMP parallel library is utilized to parallelize the first and second stages of 3StageFlow algorithm where the SimpleLocal algorithm is used it for enhancing the runtime. The experiments are performed on two applications which are image segmentation and community detection. From the experiments, the proposed method improves the runtimes with 72.75% using 4-cores and 81.01% when using 8-cores over the sequential single core