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Journal articles on the topic 'Parallel Java'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Baker, Mark. "Parallel programming with Java." Software Focus 1, no. 1 (2000): 29. http://dx.doi.org/10.1002/1529-7950(200009)1:1<29::aid-swf7>3.0.co;2-k.

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2

Kuchen, Herbert, and Steffen Ernsting. "Data Parallel Skeletons in Java." Procedia Computer Science 9 (2012): 1817–26. http://dx.doi.org/10.1016/j.procs.2012.04.200.

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3

Esquembre, F., W. Christian, and M. Belloni. "Parallel programming with Easy Java Simulations." American Journal of Physics 86, no. 1 (2018): 54–67. http://dx.doi.org/10.1119/1.5012510.

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4

Carpenter, Bryan, Guansong Zhang, Geoffrey Fox, Xinying Li, and Yuhong Wen. "HPJava: data parallel extensions to Java." Concurrency: Practice and Experience 10, no. 11-13 (1998): 873–77. http://dx.doi.org/10.1002/(sici)1096-9128(199809/11)10:11/13<873::aid-cpe402>3.0.co;2-q.

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5

Ferrari, Adam. "JPVM: network parallel computing in Java." Concurrency: Practice and Experience 10, no. 11-13 (1998): 985–92. http://dx.doi.org/10.1002/(sici)1096-9128(199809/11)10:11/13<985::aid-cpe404>3.0.co;2-a.

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6

LEE, BU-SUNG, YAN GU, WENTONG CAI, and ALFRED HENG. "PERFORMANCE EVALUATION OF JPVM." Parallel Processing Letters 09, no. 03 (1999): 401–10. http://dx.doi.org/10.1142/s0129626499000372.

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PVM for Java (JPVM) is a parallel programming environment that provides a set of Parallel Virtual Machine (PVM)-like class libraries developed using Java. JPVM inherits the attributes of Java, especially Java support of heterogeneous system. However, it also has the disadvantage of poor performance when compared to native codes. Java performance has been considerably improved with the recent introduction of Just in Time (JIT) compilers. This paper evaluates JPVM, with and without JIT compilation, using some well-known parallel processing benchmarks. It will also highlight some of the areas that limit the use of Java in parallel processing on distributed systems. The objective of the paper is to provide some performance indications of using Java in network-based parallel computing environments.

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7

Launay, Pascale, and Jean-Louis Pazat. "Easing parallel programming for clusters with Java." Future Generation Computer Systems 18, no. 2 (2001): 253–63. http://dx.doi.org/10.1016/s0167-739x(00)00096-0.

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8

Silva, Lu�s Moura, Paulo Martins, and Jo�o Gabriel Silva. "Heterogeneous parallel computing using Java and WMPI." Concurrency: Practice and Experience 12, no. 11 (2000): 1077–91. http://dx.doi.org/10.1002/1096-9128(200009)12:11<1077::aid-cpe521>3.0.co;2-#.

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9

Mehrabi, Mostafa, Nasser Giacaman, and Oliver Sinnen. "@PT: Unobtrusive parallel programming with Java annotations." Concurrency and Computation: Practice and Experience 31, no. 1 (2018): e4831. http://dx.doi.org/10.1002/cpe.4831.

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10

Christiansen, Bernd O., Peter Cappello, Mihai F. Ionescu, Michael O. Neary, Klaus E. Schauser, and Daniel Wu. "Javelin: Internet-based parallel computing using Java." Concurrency: Practice and Experience 9, no. 11 (1997): 1139–60. http://dx.doi.org/10.1002/(sici)1096-9128(199711)9:11<1139::aid-cpe349>3.0.co;2-k.

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11

Cowie, James. "JTED: parallel discrete-event simulation in Java." Concurrency: Practice and Experience 10, no. 11-13 (1998): 993–97. http://dx.doi.org/10.1002/(sici)1096-9128(199809/11)10:11/13<993::aid-cpe405>3.0.co;2-c.

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12

GAMESS, ERIC. "EXECUTION OF SEQUENTIAL AND PARALLEL JAVA BYTECODE IN A METACOMPUTING SYSTEM." Parallel Processing Letters 13, no. 01 (2003): 53–64. http://dx.doi.org/10.1142/s0129626403001148.

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In this paper, we address the goal of executing Java parallel applications in a group of nodes of a Beowulf cluster transparently chosen by a metacomputing system oriented to efficient execution of Java bytecode, with support for scientific computing. To this end, we extend the Java virtual machine by providing a message passing interface and quick access to distributed high performance resources. Also, we introduce the execution of parallel linear algebra methods for large objects from sequential Java applications by invoking SPLAM, our parallel linear algebra package.

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13

Germain‐Renaud, Cécile, and Vincent Néri. "Java-Based Coupling for Parallel Predictive-Adaptive Domain Decomposition." Scientific Programming 7, no. 2 (1999): 185–89. http://dx.doi.org/10.1155/1999/812589.

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Adaptive domain decomposition exemplifies the problem of integrating heterogeneous software components with intermediate coupling granularity. This paper describes an experiment where a data‐parallel (HPF) client interfaces with a sequential computation server through Java. We show that seamless integration of data‐parallelism is possible, but requires most of the tools from the Java palette: Java Native Interface (JNI), Remote Method Invocation (RMI), callbacks and threads.

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14

Yoshida, Akimasa, Yuki Ochi, and Nagatsugu Yamanouchi. "Parallel Java Code Generation for Layer-unified Coarse Grain Task Parallel Processing." IPSJ Online Transactions 7 (2014): 168–78. http://dx.doi.org/10.2197/ipsjtrans.7.168.

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15

BALA DHANDAYUTHAPANI, VEERASAMY, and NASIRA G.M. "APPROACHING DEVELOPMENTS ON PARALLEL PROGRAMMING MODELS THROUGH JAVA." i-manager’s Journal on Software Engineering 10, no. 3 (2016): 14. http://dx.doi.org/10.26634/jse.10.3.4900.

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16

Häuser, J., T. Ludewig, R. D. Williams, et al. "A test suite for high-performance parallel Java." Advances in Engineering Software 31, no. 8-9 (2000): 687–96. http://dx.doi.org/10.1016/s0965-9978(00)00029-6.

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17

Noll, Albert, and Thomas Gross. "Online feedback-directed optimizations for parallel Java code." ACM SIGPLAN Notices 48, no. 10 (2013): 713–28. http://dx.doi.org/10.1145/2544173.2509518.

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18

Gravvanis, George A., and Victor N. Epitropou. "Java multithreading‐based parallel approximate arrow‐type inverses." Concurrency and Computation: Practice and Experience 20, no. 10 (2008): 1151–72. http://dx.doi.org/10.1002/cpe.1262.

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19

Castilla, I., R. M. Aguilar, and Y. Callero. "Java for parallel discrete event simulation: a survey." International Journal of Simulation and Process Modelling 6, no. 4 (2011): 250. http://dx.doi.org/10.1504/ijspm.2011.048006.

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20

Jamaluddin, Muhammad Na’im Fikri, Azlan Ismail, Amir Abd Rashid, and Talha Takleh Omar Takleh. "Performance comparison of java based parallel programming models." Indonesian Journal of Electrical Engineering and Computer Science 16, no. 3 (2019): 1577. http://dx.doi.org/10.11591/ijeecs.v16.i3.pp1577-1583.

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<span lang="EN-MY">Parallel programming has been implemented in many areas to solve various computational problem with the aim, to improve the performance and scalability of the software application. There are a few parallel programming models commonly used, namely, threads, and message passing (distributed) models. Furthermore, various APIs have been proposed to implement these models based on two popular languages, notably, C/C++ and Java. A few studies have been done to compare the performance of parallel programming models, specifically, pure versus hybrid model. However, most of existing comparisons targeted on MPI/OpenMP based on C/C++ language. In this paper, our aim is to explore the performance comparison between threads, message passing and hybrid model in Java, specifically using Java multithreading and MPJ Express. For this reason, we have chosen a problem called word count occurrence which is significant in Natural Language Processing and use it to design and implement the parallel programs. We then present their performance and discuss the results.</span>

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21

Takagi, Hiromitsu, Satoshi Matsuoka, Hidemoto Nakada, Satoshi Sekiguchi, Mitsuhisa Satoh, and Umpei Nagashima. "Ninflet: a migratable parallel objects framework using Java." Concurrency: Practice and Experience 10, no. 11-13 (1998): 1063–78. http://dx.doi.org/10.1002/(sici)1096-9128(199809/11)10:11/13<1063::aid-cpe414>3.0.co;2-1.

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22

Yalamanchilli, Narendar, and William Cohen. "Communication performance of Java-based parallel virtual machines." Concurrency: Practice and Experience 10, no. 11-13 (1998): 1189–96. http://dx.doi.org/10.1002/(sici)1096-9128(199809/11)10:11/13<1189::aid-cpe398>3.0.co;2-z.

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23

Spahi, Enis, and D. Altilar. "ITU-PRP: Parallel and Distributed Computing Middleware for Java Developers." International Journal of Business & Technology 3, no. 1 (2014): 2–13. http://dx.doi.org/10.33107/ijbte.2014.3.1.01.

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ITU-PRP provides a Parallel Programming Framework for Java Developers on which they can adapt their sequential application code to operate on a distributed multi-host parallel environment. Developers would implement parallel models, such as Loop Parallelism, Divide and Conquer, Master-Slave and Fork-Join by the help of an API Library provided under framework. Produced parallel applications would be submitted to a middleware called Parallel Running Platform (PRP), on which parallel resources for parallel processing are being organized and performed. The middleware creates Task Plans (TP) according to application’s parallel model, assigns best available resource Hosts, in order to perform fast parallel processing. Task Plans will be created dynamically in real time according to resources actual utilization status or availability, instead of predefined/preconfigured task plans. ITU-PRP achieves better efficiency on parallel processing over big data sets and distributes divided base data to multiple hosts to be operated by Coarse-Grained parallelism. According to this model distributed parallel tasks would operate independently with minimal interaction until processing ends.

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24

YU, SUN, and WEI ZHANG. "REVIEW OF PARALLEL TECHNIQUES AND ITS IMPLICATION FOR JAVA." Journal of Circuits, Systems and Computers 19, no. 07 (2010): 1465–81. http://dx.doi.org/10.1142/s0218126610006761.

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This paper surveys the state-of-the-art parallel techniques for multiprocessor architectures, and studies its implication for Java programs, which are typically compiled at run-time. First, this paper overviews basic techniques of program parallelization in traditional static compilers, followed by a survey of successful parallelizing compilers. Then this paper introduces the latest research topics in this area, particularly focusing on the efforts of combining parallelizing techniques with Java virtual machines, including parallel compilation and parallel real-time garbage collection. Finally, this paper summaries the opportunities and challenges of parallelizing Java computing on multicore platforms.

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25

BAKER, MARK, and GARRY SMITH. "ESTABLISHING A RELIABLE JINI INFRASTRUCTURE FOR PARALLEL APPLICATIONS." Parallel Processing Letters 11, no. 02n03 (2001): 203–21. http://dx.doi.org/10.1142/s0129626401000531.

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Java is becoming an increasingly popular language for developing distributed and parallel scientific and engineering applications. Jini is a Java-based infrastructure developed by Sun that can allegedly provide all the services necessary to support distributed applications. It is the aim of this paper to explore and investigate the services and properties that Jini actually provides and match these against the needs of high performance distributed and parallel applications written in Java. The motivation for this work is the need to develop a distributed infrastructure to support an MPI-like interface to Java known as MPJ. In the first part of the paper we discuss the needs of MPJ, the parallel environment that we wish to support. In particular we look at aspects such as reliability and ease of use. We then move on to sketch out the Jini architecture and review the components and services that Jini provides. In the third part of the paper we critically explore a Jini infrastructure that could be used to support MPJ. Here we are particularly concerned with Jini's ability to support reliably a cocoon of MPJ processes executing in a heterogeneous envirnoment. In the final part of the paper we summarise our findings and report on future work being undertaken on Jini and MPJ.

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26

LIU, Tao, Bin FAN, Cheng-Yong WU, and Zhao-Qing ZHANG. "Dataflow-Style Java Parallel Programming Model and Runtime Optimization." Journal of Software 19, no. 9 (2008): 2181–90. http://dx.doi.org/10.3724/sp.j.1001.2008.02181.

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27

Evripidou, Paraskevas, George Samaras, Christoforos Panayiotou, and Evaggelia Pitoura. "The PaCMAn Metacomputer: parallel computing with Java mobile agents." Future Generation Computer Systems 18, no. 2 (2001): 265–80. http://dx.doi.org/10.1016/s0167-739x(00)00098-4.

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28

Aldinucci, M., M. Danelutto, and P. Teti. "An advanced environment supporting structured parallel programming in Java." Future Generation Computer Systems 19, no. 5 (2003): 611–26. http://dx.doi.org/10.1016/s0167-739x(02)00172-3.

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29

Leung, Alan, Ondřej Lhoták, and Ghulam Lashari. "Parallel execution of Java loops on Graphics Processing Units." Science of Computer Programming 78, no. 5 (2013): 458–80. http://dx.doi.org/10.1016/j.scico.2011.06.004.

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30

Bocchino, Robert L., Vikram S. Adve, Danny Dig, et al. "A type and effect system for deterministic parallel Java." ACM SIGPLAN Notices 44, no. 10 (2009): 97–116. http://dx.doi.org/10.1145/1639949.1640097.

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31

van Heiningen, Willem, Steve MacDonald, and Tim Brecht. "Babylon: middleware for distributed, parallel, and mobile Java applications." Concurrency and Computation: Practice and Experience 20, no. 10 (2008): 1195–224. http://dx.doi.org/10.1002/cpe.1264.

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32

Garti, Dror, Shem-Tov Cohen, Amnon Barak, Arie Keren, and Ricardo Szmit. "Object Mobility for Performance Improvements of Parallel Java Applications." Journal of Parallel and Distributed Computing 60, no. 10 (2000): 1311–24. http://dx.doi.org/10.1006/jpdc.2000.1655.

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33

Kambites, M. E., J. Obdr?�lek, and J. M. Bull. "An OpenMP-like interface for parallel programming in Java." Concurrency and Computation: Practice and Experience 13, no. 8-9 (2001): 793–814. http://dx.doi.org/10.1002/cpe.579.

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34

Shende, Sameer, and Allen D. Malony. "Integration and application of TAU in parallel Java environments." Concurrency and Computation: Practice and Experience 15, no. 35 (2003): 501–19. http://dx.doi.org/10.1002/cpe.655.

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35

Neary, Michael O., and Peter Cappello. "Advanced eager scheduling for Java-based adaptive parallel computing." Concurrency and Computation: Practice and Experience 17, no. 7-8 (2005): 797–819. http://dx.doi.org/10.1002/cpe.855.

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36

Getov, Vladimir, Susan Flynn Hummel, and Sava Mintchev. "High-performance parallel programming in Java: exploiting native libraries." Concurrency: Practice and Experience 10, no. 11-13 (1998): 863–72. http://dx.doi.org/10.1002/(sici)1096-9128(199809/11)10:11/13<863::aid-cpe387>3.0.co;2-7.

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37

Bizarro, Pedro, Luís M. Silva, and João Gabriel Silva. "JWarp: a Java library for parallel discrete-event simulations." Concurrency: Practice and Experience 10, no. 11-13 (1998): 999–1005. http://dx.doi.org/10.1002/(sici)1096-9128(199809/11)10:11/13<999::aid-cpe406>3.0.co;2-s.

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38

Krawiec, Jerzy. "The impact of parallel programming on performance of Java program." Prace Naukowe Akademii im. Jana Długosza w Częstochowie. Technika, Informatyka, Inżynieria Bezpieczeństwa 5 (2017): 25–38. http://dx.doi.org/10.16926/tiib.2017.05.02.

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39

TUO, Qing, and Yao-hu SONG. "Bit-split parallel algorithm for quick sorting based on Java." Journal of Computer Applications 32, no. 9 (2013): 2455–57. http://dx.doi.org/10.3724/sp.j.1087.2012.02455.

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40

Jacob, Matthias, Michael Philippsen, and Martin Karrenbach. "Large‐scale parallel geophysical algorithms in Java: A feasibility study." Leading Edge 17, no. 12 (1998): 1662–66. http://dx.doi.org/10.1190/1.1437910.

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41

Baker, Mark. "Special Issue: Message passing interface-based parallel programming with Java." Concurrency: Practice and Experience 12, no. 11 (2000): 1017–18. http://dx.doi.org/10.1002/1096-9128(200009)12:11<1017::aid-cpe537>3.0.co;2-n.

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42

Radoi, Cosmin, and Danny Dig. "Effective Techniques for Static Race Detection in Java Parallel Loops." ACM Transactions on Software Engineering and Methodology 24, no. 4 (2015): 1–30. http://dx.doi.org/10.1145/2729975.

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43

Anisimov, A. V., and A. V. Derevyanchenko. "The System PARCS-JAVA for Parallel Computations on Computer Networks." Cybernetics and Systems Analysis 41, no. 1 (2005): 17–26. http://dx.doi.org/10.1007/s10559-005-0037-4.

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44

Kähkönen, Kari, Olli Saarikivi, and Keijo Heljanko. "LCT: A Parallel Distributed Testing Tool for Multithreaded Java Programs." Electronic Notes in Theoretical Computer Science 296 (August 2013): 253–59. http://dx.doi.org/10.1016/j.entcs.2013.09.002.

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45

Huerta Yero, Eduardo Javier, Fabiano de Oliveira Lucchese, Francisco Sérgio Sambatti, Miriam von Zuben, and Marco Aurélio Amaral Henriques. "JoiN: The implementation of a Java-based massively parallel grid." Future Generation Computer Systems 21, no. 5 (2005): 791–810. http://dx.doi.org/10.1016/j.future.2004.12.004.

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46

Möller, Maximilian, Marius Schneider, Martin Wegner, and Torsten Schaub. "Centurio, a General Game Player: Parallel, Java- and ASP-based." KI - Künstliche Intelligenz 25, no. 1 (2010): 17–24. http://dx.doi.org/10.1007/s13218-010-0077-4.

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47

Taboada, Guillermo L., Juan Touriño, and Ramón Doallo. "F-MPJ: scalable Java message-passing communications on parallel systems." Journal of Supercomputing 60, no. 1 (2009): 117–40. http://dx.doi.org/10.1007/s11227-009-0270-0.

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48

Jacob, Matthias, Michael Philippsen, and Martin Karrenbach. "Large-scale parallel geophysical algorithms in Java: a feasibility study." Concurrency: Practice and Experience 10, no. 11-13 (1998): 1143–53. http://dx.doi.org/10.1002/(sici)1096-9128(199809/11)10:11/13<1143::aid-cpe394>3.0.co;2-w.

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49

Malinowski, Artur. "Modern Platform for Parallel Algorithms Testing: Java on Intel Xeon Phi." International Journal of Information Technology and Computer Science 7, no. 9 (2015): 8–14. http://dx.doi.org/10.5815/ijitcs.2015.09.02.

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50

Solayman, Haleema Essa. "A Comparison of Scheduling parallel program tasks based on Java Applet." International Journal of Advanced Trends in Computer Science and Engineering 9, no. 2 (2020): 1394–403. http://dx.doi.org/10.30534/ijatcse/2020/75922020.

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