Parallel Computing in Java
  • About PCJ
  • HPCC Award
  • Downloads
  • Examples
    • Running PCJ application
    • Hello World
    • Monte Carlo
    • Loop parallelization
    • Reduction
  • Manual
    • Programming model
    • Task management
    • Shared variables
    • Communication
    • Communication - async
  • Publications
  • Projects
    • HPDCJ
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  • Papers describing PCJ:
  • Papers where PCJ is used to develop parallel applications:

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Publications

PCJ 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 interconnects.

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Papers describing PCJ:

  1. M. Nowicki, Ł. Górski, P. Bała , w: Concurrency and Computation: Practice and Experience, Wiley, 2021, ISSN: 1532-0626, eISSN: 1532-0634, Art. no. 6536 s. 1-15,

  2. M. Nowicki, Ł. Górski, P. Bała " In: Proceedings of International Symposium on Grids and Clouds 2021 - Proceedings of Science (ISGC2021), 2021, vol. 378, p. 7;

  3. M. Nowicki, Ł. Górski, P. Bała , In: Euro-Par 2020: Parallel Processing Workshops. Euro-Par 2020, Springer, Cham, 2021, ISBN: 978-3-030-71592-2, pp. 213–224

  4. M. Nowicki, Ł. Górski, P. Bała , In: Journal of Big Data, Springer, 2021, ISSN: 2196-1115, Vol. 8 no. 1, Art no. 62, s. 1-21,

  5. M. Nowicki, Ł. Górski, P. Bała 2018 International Conference on High Performance Computing & Simulation (HPCS), pp:12-20 IEEE, 2018

  6. M. Nowicki, Ł. Górski, P. Bała CUG 2018

  7. M. Nowicki, M. Ryczkowska, Ł. Górski, P. Bała .In: Wyrzykowski R., Dongarra J., Deelman E., Karczewski K. (eds) Parallel Processing and Applied Mathematics. PPAM 2017. Lecture Notes in Computer Science, vol 10778. Springer, Cham, pp 318-327 (2018)

  8. M. Nowicki, Ł. Górski, P. Bała In: Wyrzykowski R., Dongarra J., Deelman E., Karczewski K. (eds) Parallel Processing and Applied Mathematics. PPAM 2017. Lecture Notes in Computer Science, vol 10778. Springer, Cham, pp 288-297 (2018)

  9. M. Szynkiewicz, M. Nowicki In: Wyrzykowski R., Dongarra J., Deelman E., Karczewski K. (eds) Parallel Processing and Applied Mathematics. PPAM 2017. Lecture Notes in Computer Science, vol 10778. Springer, Cham, pp 298-307 (2018)

  10. M. Nowicki, Ł. Górski, M. Ryczkowska, P. Bała In: M. Bubak, M. Turała, K. Wiatr (Eds.) CGW Workshop'17 ACK Cyfronet AGH 2017, pp 39-40

  11. M. Nowicki, P. Bała W: Ł. Kuźmiński, J. Doskocz, P. Kardasz (Red.) Innowacje w polskiej nauce w obszarze matematyki i informatyki. Przegląd aktualnej tematyki badawczej Wydawnictwo Nauka i Biznes 2016. pp 130-140

  12. M. Nowicki, P. Bała W: Materiały konferencyjne – Innowacyjne Projekty Badawcze.Dolnośląski Akcelerator Technologii i Innowacji Sp. z o. o. Wrocław 2.09.2016 p. 30

  13. 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

  14. 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

  15. M. Nowicki, P. Bała In: P. Manninen, P. Oster (Eds.) Applied Parallel and Scientific Computing, LNCS 7782, Springer, Heidelberg (2013) pp. 115-125

  16. 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

Papers where PCJ is used to develop parallel applications:

M. Nowicki, M. Mroczek, D. Mukhedkar, P. Bała, V.N. Pimenoff, L.S. Arroyo Mühr , Briefings in Bioinformatics, Volume 26, Issue 2, March 2025, bbaf155,

M. Nowicki Journal of Big Data 2020 7:101

J. Posner, L. Reitz, C. Fohry Parallel Applications Workshop - Alternatives to MPI, SC'18, Dallas 2018

M. Nowicki, D. Bzhalava, P. Bała J. Comp. Biology 25 (8):871-881, 2018

M. Nowicki, D. Bzhalava, P. Bała In: S. Ibrahim, Kim-Kwang R. Choo, Z. Yan, W. Pedrycz (Eds.) Algorithms and Architectures for Parallel Processing. ICA3PP 2017. Lecture Notes in Computer Science, vol 10393. Springer, Cham ,2017, pp. 503-512

R. Istrate, P. Barkoutsos, M. Dolfi, P. Staar, C. Bekas. In: Wyrzykowski R., Dongarra J., Deelman E., Karczewski K. (eds) Parallel Processing and Applied Mathematics. PPAM 2017. Lecture Notes in Computer Science, vol 10778. Springer, Cham, pp 308-317 (2018)

M Ryczkowska, M Nowicki In: Wyrzykowski R., Dongarra J., Deelman E., Karczewski K. (eds) Parallel Processing and Applied Mathematics. PPAM 2017. Lecture Notes in Computer Science, vol 10778. Springer, Cham, pp 328-337 (2018)

M Ryczkowska, M Nowicki, P Bała 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 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 In: R. Wyrzykowski et all (eds.) Parallel Processing and Applied Mathematics, Springer 2016 pp. 221-230

Ł Górski, F Rakowski, P Bała In: R. Wyrzykowski et all (eds.) Parallel Processing and Applied Mathematics, Springer 2015, pp. 448-458

M Nowicki, M Marchwiany, M Szpindler, P Bała In:Euro-Par 2015: Parallel Processing Workshops, Springer 2015, pp. 78-89

M. Ryczkowska In: W. W. Smari and V. Zeljkovic (Eds.) 2012 International Conference on High Performance Computing and Simulation (HPCS) IEEE 2014 pp. 1005-1007

Performance evaluation of Java/PCJ implementation of parallel algorithms on the cloud (extended version)
DOI: 10.1002/cpe.6536
Scalable computing in Java with PCJ Library. Improved collective operations.
DOI: 10.22323/1.378.0007
Performance Evaluation of Java/PCJ Implementation of Parallel Algorithms on the Cloud
PCJ Java library as a solution to integrate HPC, Big Data and Artificial Intelligence workloads
DOI: 10.1186/s40537-021-00454-6
PCJ – Java Library for Highly Scalable HPC and Big Data Processing
Performance evaluation of parallel computing and Big Data processing with Java and PCJ library
Big Data analytics in Java with PCJ library - performance comparison with Hadoop
Evaluation of the parallel performance of the Java and PCJ on the Intel KNL based systems.
Fault-tolerance mechanisms for the Java parallel codes implemented with the PCJ library.
PCJ as a tool for masivelly parallel data processing.
Programowanie równoległe w języku Java z wykorzystaniem biblioteki PCJ
Programowanie równoległe w języku Java z wykorzystaniem biblioteki PCJ
PCJ - a Java library for heterogenous parallel computing
PCJ - Java library for high performance computing in PGAS model
PCJ-new approach for parallel computations in java
Parallel computations in Java with PCJ library
HPV-KITE: sequence analysis software for rapid HPV genotype detection
https://doi.org/10.1093/bib/bbaf155
Comparison of sort algorithms in Hadoop and PCJ
Comparison of the HPC and Big Data Java Libraries Spark, PCJ and APGAS
Massively Parallel Implementation of Sequence Alignment with BLAST Using PCJ Library
Massively Parallel Sequence Alignment with BLAST through Work Distribution Implemented using PCJ Library
Exploring graph analytics with the PCJ toolbox
Performance comparison of graph BFS implemented in MapReduce and PGAS programming models.
Level-synchronous BFS algorithm implemented in Java using PCJ Library
A case study of software load balancing policies implemented with the PGAS programming model
The Performance Evaluation of the Java Implementation of Graph500
Parallel Differential Evolution in the PGAS Programming Model Implemented with PCJ Java Library
On-line Service for Teaching Parallel Programming
Evaluating PCJ library for graph problems-Graph500 in PCJ