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PCJ - a PGAS library for Java

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Abstract

This paper presents the performance of the PCJ -- a new library for Java language that helps to perform parallel and distributed calculations. The library is motivated by partitioned global address space (PGAS) model represented by Co-Array Fortran, Unified Parallel C or Titanium. PCJ has ability to work on the multicore systems hiding details of inter- and intranode communication. In the PCJ, each task has its own local memory and stores and access variables only locally. Some variables can be shared between tasks and that variables can be accessed, read and modified by other tasks. The library provides methods to perform basic operations like synchronization of tasks, get and put values in asynchronous one-sided way. Additionally the library offers methods for creating groups of tasks, broadcasting and monitoring variables. The PCJ library fully complies with Java standards therefore the programmer does not have to use additional libraries, which are not part of the standard Java distribution. In this paper the PCJ library with the support for multicore, multithreaded systems is presented. It has been used to run example HPC benchmark suite applications on the multicore nodes. The results show good performance and scalability compared to native MPI and OpenMP implementations of the same algorithms. It is noteworthy that the PCJ library has great promise to be successful in scientific applications.
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Chapter
In this paper we present PCJ - a new library for parallel computations in Java inspired by the partitioned global address space approach. We present design details together with the examples of usage for basic operations such as a point-point communication, synchronization or broadcast. The PCJ library is easy to use and allows for a fast development of the parallel programs. It allows to develop distributed applications in easy way, hiding communication details which allows user to focus on the implementation of the algorithm rather than on network or threads programming. The objects and variables are local to the program threads however some variables can be marked shared which allows to access them from different nodes. For shared variables PCJ offers one-sided communication which allows for easy access to the data stored at the different nodes. The parallel programs developed with PCJ can be run on the distributed systems with different Java VM running on the nodes. In the paper we present evaluation of the performance of the PCJ communication on the state of art hardware. The results are compared with the native MPI implementation showing good performance and scalability of the PCJ.
Parallel computations in Java with PCJ library
  • M Nowicki
  • P Ba
  • La
M. Nowicki, P. Ba la. Parallel computations in Java with PCJ library In: W. W. Smari and V. Zeljkovic (Eds.) 2012 International Conference on High Performance Computing and Simulation (HPCS), IEEE 2012 pp. 381-387