Level-Synchronous BFS Algorithm Implemented in Java Using PCJ Library

Graph processing is used in many fields of science such as sociology, risk prediction or biology. Although analysis of graphs is important it also poses numerous challenges especially for large graphs which have to be processed on multicore systems. In this paper, we present PGAS (Partitioned Global Address Space) version of the level-synchronous BFS (Breadth First Search) algorithm and its implementation written in Java. Java so far is not extensively used in high performance computing, but because of its popularity, portability, and increasing capabilities is becoming more widely exploit especially for data analysis. The level-synchronous BFS has been implemented using a PCJ (Parallel Computations in Java) library. In this paper, we present implementation details and compare its scalability and performance with the MPI implementation of Graph500 benchmark. We show good scalability and performance of our implementation in comparison with MPI code written in C. We present challenges we faced and optimizations we used in our implementation necessary to obtain good performance.