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, Ł. Górski, P. Bała Performance evaluation of parallel computing and Big Data processing with Java and PCJ library CUG 2018

3. 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)

4. 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)

5. 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)

6. 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

7. 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

8. 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

9. 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

10. 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

11. 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

12. 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