About PCJ
Java library for parallel computing in PGAS (Partitioned Global Address Space) paradigm.
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Java library for parallel computing in PGAS (Partitioned Global Address Space) paradigm.
Last updated
Was this helpful?
PCJ is Java library for parallel computing in Java. It is based on the PGAS (Partitioned Global Address Space) paradigm. It allows for easy implementation in Java of any parallel algorithm. PCJ application can be run on laptop, workstation, cluster and HPC system including large supercomputers. It has been demonstrated that PCJ applications scale up to 200 000 cores.
Recently we have run PCJ application on the coud (AWS EC2) using both x86 and arm processors. Therefore you can run PCJ on most popular architectures indluding Intel KNL, Power, ARM and of course x86.
Current version of the librarry is 5.3.3. Compare to 5.2 and 5.1 it has improved performance due to use of shifted tree communication. New methos has been added: PCJ.scatter(), PCJ.splitGroup(). New collective communication methods are avaliable: PCJ.collect(), PCJ.asyncCollect(),
For more changes see:
You can use PCJ Library by adding jar file to your project.
PCJ Library is also available on Maven Central Repository. For maven project, just add this dependency to your pom.xml
file.
If you are using gradle, add those lines to your build.gradle
file:
If you wish to compile project by your own, use these instructions:
to package the jar: ./gradlew assemble
or gradlew.bat assemble
to create javadoc: ./gradlew javadoc
or gradlew.bat javadoc
Execute ./gradlew eclipse
, start eclipse
, and use File -> Import : Existing Projects into Workspace
. See for more information.
M. Nowicki, Ł. Górski, P. Bała 2018 International Conference on High Performance Computing & Simulation (HPCS), pp:12-20 IEEE, 2018
M. Nowicki, M. Ryczkowska, Ł. Górski, M. Szynkiewicz, P. Bała 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 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 In: P. Manninen, P. Oster (Eds.) Applied Parallel and Scientific Computing, LNCS 7782, Springer, Heidelberg (2013) pp. 115-125
M. Nowicki, P. Bała In: W. W. Smari and V. Zeljkovic (Eds.) 2012 International Conference on High Performance Computing and Simulation (HPCS) IEEE 2012 pp. 381-387