Abstract
Graph-based computations are used in many applications. Increasing size of analyzed data and its complexity make graph analysis a challenging task. In this paper we present performance evaluation of Java implementation of Graph500 benchmark. It has been developed with the help of the PCJ (Parallel Computations in Java) library for parallel and distributed computations in Java. PCJ is based on a PGAS (Partitioned Global Address Space) programming paradigm, where all communication details such as threads or network programming are hidden. In this paper, we present Java implementation details of first and second kernel from Graph500 benchmark. The results are compared with the existing MPI implementations of Graph500 benchmark, showing good scalability of PCJ library.
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Notes
- 1.
PCJ has been appreciated as an efficient way of programming parallel applications, receiving HPC Challenge Class 2 Best Productivity Award [12].
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This work has been performed using the PL-Grid infrastructure. Partial support from CHIST-ERA consortium is acknowledged.
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Ryczkowska, M., Nowicki, M., Bala, P. (2016). The Performance Evaluation of the Java Implementation of Graph500. In: Wyrzykowski, R., Deelman, E., Dongarra, J., Karczewski, K., Kitowski, J., Wiatr, K. (eds) Parallel Processing and Applied Mathematics. Lecture Notes in Computer Science(), vol 9574. Springer, Cham. https://doi.org/10.1007/978-3-319-32152-3_21
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