ИСТИНА

An important trend in modern supercomputing is a frequent usage of co-processors, such as GPUs and Intel Xeon PHIs. The recent generation of Intel Knights Landing processors provide high performance computational power with a large amount of high-bandwidth memory, what makes them a perfect platform for graph-processing. The presented study describes implementation approaches to large-scale graph processing on Intel KNL processors; as a sample problem, the transitive closure computation is discussed. Based on the joint analysis of algorithm properties and architecture features, the performance tuning has been performed, including graph storage format optimizations, efficient usage of memory hierarchy and vectorization. As a result, an optimized algorithm implementation for the transitive closure problem solution has been developed. The proposed implementation has been studied using different approaches, aimed at demonstrating advantages and disadvantages of Intel KNL architecture in solving graph-processing problems.