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.

Papers describing PCJ:

  1. M. Nowicki, Ł. Górski, P. Bała PCJ – Java Library for Highly Scalable HPC and Big Data Processing 2018 International Conference on High Performance Computing \& Simulation (HPCS), pp:12-20 IEEE, 2018

  2. M. Nowicki, M. Ryczkowska, Ł. Górski, P. Bała Big Data analytics in Java with PCJ library - performance comparison with Hadoop.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)

  3. M. Nowicki, Ł. Górski, P. Bała Evaluation of the parallel performance of the Java and PCJ on the Intel KNL based systems. 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)

  4. M. Szynkiewicz, M. Nowicki Fault-tolerance mechanisms for the Java parallel codes implemented with the PCJ library. 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)

  5. M. Nowicki, Ł. Górski, M. Ryczkowska, P. Bała PCJ as a tool for masivelly parallel data processing. In: M. Bubak, M. Turała, K. Wiatr (Eds.) CGW Workshop'17 ACK Cyfronet AGH 2017, pp 39-40

  6. M. Nowicki, P. Bała Programowanie równoległe w języku Java z wykorzystaniem biblioteki PCJ 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

  7. M. Nowicki, P. Bała Programowanie równoległe w języku Java z wykorzystaniem biblioteki PCJ W: Materiały konferencyjne – Innowacyjne Projekty Badawcze.Dolnośląski Akcelerator Technologii i Innowacji Sp. z o. o. Wrocław 2.09.2016 p. 30

  8. 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

  9. 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

  10. 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

  11. 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

Papers where PCJ is used to develop parallel applications:

  1. M. Nowicki Comparison of sort algorithms in Hadoop and PCJ Jpurnal of big Data 2020 7:101

  2. J. Posner, L. Reitz, C. Fohry Comparison of the HPC and Big Data Java Libraries Spark, PCJ and APGAS Parallel Applications Workshop - Alternatives to MPI, SC'18, Dallas 2018

  3. M. Nowicki, D. Bzhalava, P. Bała Massively Parallel Implementation of Sequence Alignment with BLAST Using PCJ Library J. Comp. Biology 25 (8):871-881, 2018

  4. M. Nowicki, D. Bzhalava, P. Bała Massively Parallel Sequence Alignment with BLAST through Work Distribution Implemented using PCJ Library 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

  5. R. Istrate, P. Barkoutsos, M. Dolfi, P. Staar, C. Bekas Exploring graph analytics with the PCJ toolbox. 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)

  6. M Ryczkowska, M Nowicki Performance comparison of graph BFS implemented in MapReduce and PGAS programming models. 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)

  7. M Ryczkowska, M Nowicki, P Bała 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

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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