Abstract:

Compared with traditional applications, big data applications present have diffident characteristics, such as high parallelism, large volumes of data, irregular memory access mode,  and poor temporal locality, which bring new challenges to traditional computer architectures. Graph500 which focuses on data intensive loads, is a rating of supercomputer systems. And the Bread First Search (BFS) algorithm is the core of the benchmark. Based on the parallel prototype system designed for big data applications, we implement the BFS algorithm  from the perspectives of 1D partitioning, optimized hybrid algorithm and convenient remote communication design. The performance achieves 803.8 MTEPS under the scale of an input graph of 222 vertexs and 226 edges. Then we analyze the experiment performance and provide a reference for future wok.

Key words: big data processing, Graph500, parallel BFS, parallel prototype system, performance analysis