PCJ is a library for Java language that helps to perform parallel and distributed calculations. The current version is able to work on the multicore systems connected with the typical interconnect such as ethernet or infiniband providing users with the uniform view across nodes.
Download PCJ library (jar file of 29.04.2017 ver. 5.0.6) Latest (bug fixing release)!
Download PCJ manual (pdf) for PCJ 5 New!
The PCJ library can be used with no cost at BSD license. It requires Java 8 and no additional tools or comilers. The PCJ library for Java 7 is available in the dowload section.
The source code is available at GitHub: https://github.com/hpdcj/pcj
Version 5.0.6 fixes some bugs occuring with the massive communication.
Version 5.0.3 contains support for Intel KNL chips.
Version 5 introduces asyncPut() and asyncGet() methods; put() and get() methods are now synchronous. There is new handling of shared variables. The code developed for PCJ 4 hast to be modified. For details please reffer to the JavaDoc file.
The usage should be acknowledged by reference to the PCJ web site and/or reference to the papers:
- M. Nowicki, M. Ryczkowska, Ł. Górski, M. Szynkiewicz, P. Bała PCJ - a Java library for heterogenous parallel computing In: X. Zhuang (Ed.) Recent Advances in Information Science (Recent Advances in Computer Engineering Series vol 36) WSEAS Press 2016 pp. 66-72
- M. Nowicki, Ł. Górski, P. Grabarczyk, P. Bała PCJ - Java library for high performance computing in PGAS model In: W. W. Smari and V. Zeljkovic (Eds.) 2012 International Conference on High Performance Computing and Simulation (HPCS) IEEE 2014 pp. 202-209
- M. Nowicki, P. Bała PCJ-new approach for parallel computations in java In: P. Manninen, P. Oster (Eds.) Applied Parallel and Scientific Computing, LNCS 7782, Springer, Heidelberg (2013) pp. 115-125
- M. Nowicki, P. Bała 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
Usage of the PCJ:
- M Ryczkowska, M Nowicki, P Bala Level-synchronous BFS algorithm implemented in Java using PCJ Library In: 2016 International Conference on Computational Science and Computational Intelligence (CSCI), Las Vegas, NV, USA}, 2016, pp. 596-601
- Ł Górski, F Rakowski, P Bała A case study of software load balancing policies implemented with the PGAS programming model In: W. W. Smari, V. Zejkovic (Eds) (eds.) 2016 International Conference on High Performance Computing \& Simulation (HPCS),
IEEE 2016, pp. 443 - 448
- M Ryczkowska, M Nowicki, P Bala The Performance Evaluation of the Java Implementation of Graph500 In: R. Wyrzykowski et all (eds.) Parallel Processing and Applied Mathematics, Springer 2016 pp. 221-230
- Ł Górski, F Rakowski, P Bała Parallel Differential Evolution in the PGAS Programming Model Implemented with PCJ Java Library In: R. Wyrzykowski et all (eds.) Parallel Processing and Applied Mathematics, Springer 2015, pp. 448-458
- M Nowicki, M Marchwiany, M Szpindler, P Bała On-line Service for Teaching Parallel Programming In:Euro-Par 2015: Parallel Processing Workshops, Springer 2015, pp. 78-89
- M. Ryczkowska Evaluating PCJ library for graph problems-Graph500 in PCJ In: W. W. Smari and V. Zeljkovic (Eds.) 2012 International Conference on High Performance Computing and Simulation (HPCS) IEEE 2014 pp. 1005-1007
Contact: firstname.lastname@example.org email@example.com
HPC Challenge Class 2 Best Productivity Award
PCJ received HPC Challenge Class 2 Best Productivity Award, which recognize the efficient way of programming parallel applications.
The awards were announced on November 18, 2014, in New Orleans, Louisiana, at SC14, the International Conference for High Performance Computing, Networking, Storage and Analysis.
The HPC Challenge benchmarks are benchmark programs designed to evaluate the overall performance of supercomputers in terms of processing performance based on 28 frequently used computational patterns in the field of scientific computation. At the contest using the HPC Challenge benchmarks, which takes place once a year, there are two classes of awards: Class 1, which measures benchmark performance values, and Class 2, which measures the productivity of programming language implementations.
The HPC Challenge Class 2 Award is a contest for programming languages used in developing HPC applications. This award is designed to evaluate both programming language productivity and performance for HPC Challenge.
PCJ (http://pcj.icm.edu.pl) is a library for Java language that helps to perform parallel and distributed calculations. It is able to work on the multicore systems connected with the typical interconnect such as ethernet or infiniband providing users with the uniform view across nodes. Current development of the PCJ library is realized with the EU support within CHIST-ERA framework.