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Journal articles on the topic 'Parallelisation'

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Author: Grafiati

Published: 4 June 2021

Last updated: 22 June 2024

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1

Ierotheou, C. S., S. P. Johnson, P. F. Leggett, M. Cross, E. W. Evans, H. Jin, M. Frumkin, and J. Yan. "The Semi-Automatic Parallelisation of Scientific Application Codes Using a Computer Aided Parallelisation Toolkit." Scientific Programming 9, no. 2-3 (2001): 163–73. http://dx.doi.org/10.1155/2001/327048.

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The shared-memory programming model can be an effective way to achieve parallelism on shared memory parallel computers. Historically however, the lack of a programming standard using directives and the limited scalability have affected its take-up. Recent advances in hardware and software technologies have resulted in improvements to both the performance of parallel programs with compiler directives and the issue of portability with the introduction of OpenMP. In this study, the Computer Aided Parallelisation Toolkit has been extended to automatically generate OpenMP-based parallel programs with nominal user assistance. We categorize the different loop types and show how efficient directives can be placed using the toolkit's in-depth interprocedural analysis. Examples are taken from the NAS parallel benchmarks and a number of real-world application codes. This demonstrates the great potential of using the toolkit to quickly parallelise serial programs as well as the good performance achievable on up to 300 processors for hybrid message passing-directive parallelisations.

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2

Wolffs, Zef, Patrick Bos, Lydia Brenner, Wouter Verkerke, and Ivo van Vulpen. "Efficient Parallelization of RooFit Computations for Accelerated Higgs Combination Fits." EPJ Web of Conferences 295 (2024): 06007. http://dx.doi.org/10.1051/epjconf/202429506007.

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In the context of High Energy Physics (HEP) analyses the advent of large-scale combination fits forms an increasing computational challenge for the underlying software frameworks on which these fits rely. RooFit, being the central tool for HEP statistical model creation and fitting, intends to address this challenge through an efficient and versatile parallelisation framework on top of which two parallel implementations were developed in the present research. The first implementation, the parallelisation of the gradient, shows good scaling behaviour and is sufficiently robust to consistently minimize real large-scale fits. The latter, the parallelisation of the line search, is still work in progress for some specific likelihood components but shows promising results in realistic testcases. Enabling just gradient parallelisation speeds up the full fit of a recently published Higgs combination from the ATLAS experiment by a factor of 4.6 with sixteen workers. As the improvements presented in this research are currently publicly available in ROOT 6.28, we invite users to enable at least gradient parallelisation for robust accelerated fitting with RooFit.

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3

Kriauzienė, Rima, Andrej Bugajev, and Raimondas Čiegis. "A THREE-LEVEL PARALLELISATION SCHEME AND APPLICATION TO THE NELDER-MEAD ALGORITHM." Mathematical Modelling and Analysis 25, no. 4 (October 13, 2020): 584–607. http://dx.doi.org/10.3846/mma.2020.12139.

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We consider a three-level parallelisation scheme. The second and third levels define a classical two-level parallelisation scheme and some load balancing algorithm is used to distribute tasks among processes. It is well-known that for many applications the efficiency of parallel algorithms of these two levels starts to drop down after some critical parallelisation degree is reached. This weakness of the twolevel template is addressed by introduction of one additional parallelisation level. s an alternative to the basic solver some new or modified algorithms are considered on this level. The idea of the proposed methodology is to increase the parallelisation degree by using possibly less efficient algorithms in comparison with the basic solver. As an example we investigate two modified Nelder-Mead methods. For the selected application, a Schro¨dinger equation is solved numerically on the second level, and on the third level the parallel Wang’s algorithm is used to solve systems of linear equations with tridiagonal matrices. A greedy workload balancing heuristic is proposed, which is oriented to the case of a large number of available processors. The complexity estimates of the computational tasks are model-based, i.e. they use empirical computational data.

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4

Kaber, Sidi-Mahmoud, Amine Loumi, and Philippe Parnaudeau. "Parallel Solution of Linear Systems." East Asian Journal on Applied Mathematics 6, no. 3 (July 20, 2016): 278–89. http://dx.doi.org/10.4208/eajam.210715.250316a.

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AbstractComputational scientists generally seek more accurate results in shorter times, and to achieve this a knowledge of evolving programming paradigms and hardware is important. In particular, optimising solvers for linear systems is a major challenge in scientific computation, and numerical algorithms must be modified or new ones created to fully use the parallel architecture of new computers. Parallel space discretisation solvers for Partial Differential Equations (PDE) such as Domain Decomposition Methods (DDM) are efficient and well documented. At first glance, parallelisation seems to be inconsistent with inherently sequential time evolution, but parallelisation is not limited to space directions. In this article, we present a new and simple method for time parallelisation, based on partial fraction decomposition of the inverse of some special matrices. We discuss its application to the heat equation and some limitations, in associated numerical experiments.

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5

Janssen, R., M. Dracopoulos, K. Parrott, E. Slessor, P. Alotto, P. Molfino, M. Nervi, and J. Simkin. "Parallelisation of electromagnetic simulation codes." IEEE Transactions on Magnetics 34, no. 5 (1998): 3423–26. http://dx.doi.org/10.1109/20.717806.

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6

Hershey, J. E., K. Molnar, and A. Hassan. "Parallelisation of suboptimal spectrum search." Electronics Letters 28, no. 18 (1992): 1721. http://dx.doi.org/10.1049/el:19921094.

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7

AL-Sudani, Asaad A. M. "SYSTEM PARALLELISATION FOR COMPUTER VISION." Journal of Engineering 9, no. 02 (June 1, 2003): 249–64. http://dx.doi.org/10.31026/j.eng.2003.02.08.

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This paper delineates the parallelisation of a computer vision system. It presents the system proposal and the relevant design phases of a laboratory based model. This model involves special purpose hardware implementing the early stages of processing with very high data rate. It Incorporates facilities enabling the user to capture, retain, retrieve, compare, and analyse video images. The output of this hardware is to be processed by a software running in a parallel processor. The latter is a VMEbus-based multiprocessing machine accommodating the system hardware and ensures for better flexibility. It also participates in a reasonable distribution of the systern processing power. The kernel philosophy here depends on the concept of modularisation to attain higher degree of design consistency. It believes that the spatiotemporal pixel variation of two adjacent video frames involves sufficient information to detect movement. This implies pixel encoding and motion parameters estimation. The system software is based on a data compressive technique (Strip Encoding of Adjacent Frames) to solve the bottlenecks problem in the whole system throughput. The research hereby attempts to attain a match in the degree of sophistication between the system hardware and software structures. This yields to make the system processing power better meets the system applications requirements. The research investigates the above presented design phases along with their logical, functional, technical, and modular specifications. The research is adequate for development in a wide range of applications (requiring parallel architectures for image processing) like: Artificial Intelligence, Features Extraction and Pattern Recognition, Expert Systems, Computer Vision and Robotic Vision, Industrial Control, and other civil and military applications.

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8

Padalko, Mikhail Alexandrovich, Yuriy Andreevich Shevchenko, Vitalii Yurievich Kapitan, and Konstantin Valentinovich Nefedev. "Parallel Computing of Edwards—Anderson Model." Algorithms 15, no. 1 (December 27, 2021): 13. http://dx.doi.org/10.3390/a15010013.

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A scheme for parallel computation of the two-dimensional Edwards—Anderson model based on the transfer matrix approach is proposed. Free boundary conditions are considered. The method may find application in calculations related to spin glasses and in quantum simulators. Performance data are given. The scheme of parallelisation for various numbers of threads is tested. Application to a quantum computer simulator is considered in detail. In particular, a parallelisation scheme of work of quantum computer simulator.

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9

Liu, Jun-Jie, Kang-Too Tsang, and Yu-Hui Deng. "A variant RSA acceleration with parallelisation." International Journal of Parallel, Emergent and Distributed Systems 37, no. 3 (January 12, 2022): 318–32. http://dx.doi.org/10.1080/17445760.2021.2024535.

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10

Boukerram, Abdallah, and Samira Ait Kaci Azzou. "Parallelisation of Algorithms of Mathematical Morphology." Journal of Computer Science 2, no. 8 (August 1, 2006): 615–18. http://dx.doi.org/10.3844/jcssp.2006.615.618.

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11

BERRUYER, GILLES, and ANDREW HAMMERSLEY. "Parallelisation of an Interactive Fitting Algorithm." International Journal of Modern Physics C 02, no. 01 (March 1991): 254–62. http://dx.doi.org/10.1142/s0129183191000287.

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The rational and suitability of implementing model fitting algorithms on vector and parallel computers are discussed. A particular maximum likelihood based algorithm for fitting of two-dimensional “Gaussian” peaks was investigated in detail and adapted to a system of four transputers. Analysis of the algorithm shows it well suited to both vectorisation and parallelisation; this result being applicable to other fitting methods. The transputer implementation gave an increase in performance (5–10 times faster) compared to the host computer, allowing the model fitting procedure to approach acceptable response times.

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12

Cui, Zhengtao, Baxter E. Vieux, Henry Neeman, and Fekadu Moreda. "Parallelisation of a distributed hydrologic model." International Journal of Computer Applications in Technology 22, no. 1 (2005): 42. http://dx.doi.org/10.1504/ijcat.2005.006802.

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13

Trelles, O. "On the parallelisation of bioinformatics applications." Briefings in Bioinformatics 2, no. 2 (January 1, 2001): 181–94. http://dx.doi.org/10.1093/bib/2.2.181.

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14

Rahim, Lukman Ab, Krishna Mohan Kudiri, and Shiladitya Bahattacharjee. "Framework for parallelisation on big data." PLOS ONE 14, no. 5 (May 23, 2019): e0214044. http://dx.doi.org/10.1371/journal.pone.0214044.

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15

Lam, Yuet Ming, José Gabriel F. Coutinho, Chun Hok Ho, Philip Heng Wai Leong, and Wayne Luk. "Multiloop Parallelisation Using Unrolling and Fission." International Journal of Reconfigurable Computing 2010 (2010): 1–10. http://dx.doi.org/10.1155/2010/475620.

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A technique for parallelising multiple loops in a heterogeneous computing system is presented. Loops are first unrolled and then broken up into multiple tasks which are mapped to reconfigurable hardware. A performance-driven optimisation is applied to find the best unrolling factor for each loop under hardware size constraints. The approach is demonstrated using three applications: speech recognition, image processing, and the N-Body problem. Experimental results show that a maximum speedup of 34 is achieved on a 274 MHz FPGA for the N-Body over a 2.6 GHz microprocessor, which is 4.1 times higher than that of an approach without unrolling.

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16

Fleury, M., A. C. Downton, and A. F. Clark. "Pipelined parallelisation of automatic face inspection." Machine Vision and Applications 12, no. 4 (December 1, 2000): 203–11. http://dx.doi.org/10.1007/s001380050140.

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17

Maillard, J., and J. Silva. "Track parallelisation in GEANT detector simulations." Computer Physics Communications 95, no. 1 (May 1996): 17–22. http://dx.doi.org/10.1016/0010-4655(95)00107-7.

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18

Djanali, Vivien, Steven W. Armfield, Michael P. Kirkpatrick, and Stuart Norris. "Parallel Speed-Up of Preconditioned Fractional Step Navier-Stokes Solvers." Applied Mechanics and Materials 493 (January 2014): 215–20. http://dx.doi.org/10.4028/www.scientific.net/amm.493.215.

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Parallel performance of a fractional step Navier-Stokes solver is investigated. Parallelisation is performed using Message Passing Interface, with domain partitioning. Block preconditioning is applied to the solution of the pressure Poisson equation, which is often the bottleneck in the computation of the fractional step method. Preconditioners tested are classes of incomplete matrix decompositions and sparse approximate inverses. The computational domain is decomposed into eight parts of about equal size in terms of the number of cells, and solved on eight parallel processors. Several aspects of the parallelisation, such as domain splitting directions, speed-up and scalability of the preconditioners, are discussed.

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19

Ierotheou, C. S., S. P. Johnson, M. Cross, and P. F. Leggett. "Computer aided parallelisation tools (CAPTools) — conceptual overview and performance on the parallelisation of structured mesh codes." Parallel Computing 22, no. 2 (February 1996): 163–95. http://dx.doi.org/10.1016/0167-8191(95)00004-6.

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20

Mishra, Rituraj, Achille Marchand, Corentin Jacquemmoz, and Jean-Nicolas Dumez. "Ultrafast diffusion-based unmixing of 1H NMR spectra." Chemical Communications 57, no. 19 (2021): 2384–87. http://dx.doi.org/10.1039/d0cc07757g.

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21

Niculescu, Virginia, and Robert Manuel Ştefănică. "Tries-Based Parallel Solutions for Generating Perfect Crosswords Grids." Algorithms 15, no. 1 (January 13, 2022): 22. http://dx.doi.org/10.3390/a15010022.

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A general crossword grid generation is considered an NP-complete problem and theoretically it could be a good candidate to be used by cryptography algorithms. In this article, we propose a new algorithm for generating perfect crosswords grids (with no black boxes) that relies on using tries data structures, which are very important for reducing the time for finding the solutions, and offers good opportunity for parallelisation, too. The algorithm uses a special tries representation and it is very efficient, but through parallelisation the performance is improved to a level that allows the solution to be obtained extremely fast. The experiments were conducted using a dictionary of almost 700,000 words, and the solutions were obtained using the parallelised version with an execution time in the order of minutes. We demonstrate here that finding a perfect crossword grid could be solved faster than has been estimated before, if we use tries as supporting data structures together with parallelisation. Still, if the size of the dictionary is increased by a lot (e.g., considering a set of dictionaries for different languages—not only for one), or through a generalisation to a 3D space or multidimensional spaces, then the problem still could be investigated for a possible usage in cryptography.

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22

Giacaman, Nasser, and Oliver Sinnen. "Object-Oriented Parallelisation of Java Desktop Programs." IEEE Software 28, no. 1 (January 2011): 32–38. http://dx.doi.org/10.1109/ms.2010.135.

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23

Weng, Tien Hsiung, Kuan Ching Li, Mario Donato Marino, Huimin Lu, and Yi Siang Chen. "On parallelisation of image dehazing with OpenMP." International Journal of Embedded Systems 11, no. 4 (2019): 427. http://dx.doi.org/10.1504/ijes.2019.10022123.

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24

Kulabukhova, Nataliia. "Natural parallelisation paradigm on accelerator physics example." International Journal of Web and Grid Services 15, no. 4 (2019): 340. http://dx.doi.org/10.1504/ijwgs.2019.10024789.

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25

Kulabukhova, Nataliia. "Natural parallelisation paradigm on accelerator physics example." International Journal of Web and Grid Services 15, no. 4 (2019): 340. http://dx.doi.org/10.1504/ijwgs.2019.103216.

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26

Heng, Alfred C. K., and Malcolm Y. H. Low. "Loop parallelisation tool for message-passing systems." Microprocessors and Microsystems 20, no. 7 (March 1997): 409–21. http://dx.doi.org/10.1016/s0141-9331(96)01107-6.

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27

Vollebregt, E. A. H. "Parallelisation of algorithms for advection diffusion problems." Simulation Practice and Theory 3, no. 4-5 (December 1995): 273–86. http://dx.doi.org/10.1016/0928-4869(95)00032-2.

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28

Gladwell, I., and R. I. Hay. "Vector- and parallelisation of ODE BVP codes." Parallel Computing 12, no. 3 (December 1989): 343–50. http://dx.doi.org/10.1016/0167-8191(89)90092-6.

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29

Pethick, Andrew, and Brett Harris. "Macro-parallelisation for controlled source electromagnetic applications." Journal of Applied Geophysics 124 (January 2016): 91–105. http://dx.doi.org/10.1016/j.jappgeo.2015.11.013.

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30

Kannan, Venkatesh, and G. W. Hamilton. "Functional Program Transformation for Parallelisation Using Skeletons." International Journal of Parallel Programming 46, no. 1 (May 23, 2017): 152–72. http://dx.doi.org/10.1007/s10766-017-0510-5.

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31

Iman Fitri Ismail, Akmal Nizam Mohammed, Bambang Basuno, Siti Aisyah Alimuddin, and Mustafa Alas. "Evaluation of CFD Computing Performance on Multi-Core Processors for Flow Simulations." Journal of Advanced Research in Applied Sciences and Engineering Technology 28, no. 1 (September 11, 2022): 67–80. http://dx.doi.org/10.37934/araset.28.1.6780.

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Previous parallel computing implementations for Computational Fluid Dynamics (CFD) focused extensively on Complex Instruction Set Computer (CISC). Parallel programming was incorporated into the previous generation of the Raspberry Pi Reduced Instruction Set Computer (RISC). However, it yielded poor computing performance due to the processing power limits of the time. This research focuses on utilising two Raspberry Pi 3 B+ with increased processing capability compared to its previous generation to tackle fluid flow problems using numerical analysis and CFD. Parallel computing elements such as Secure Shell (SSH) and the Message Passing Interface (MPI) protocol were implemented for Advanced RISC Machine (ARM) processors. The parallel network was then validated by a processor call attempt and core execution test. Parallelisation of the processors enables the study of fluid flow and computational fluid dynamics (CFD) problems, such as validation of the NACA 0012 airfoil and an additional case of the Laplace equation for computing the temperature distribution via the parallel system. The experimental NACA 0012 data was validated using the parallel system, which can simulate the airfoil's physics. Each core was enabled and tested to determine the system's performance in parallelising the execution of various programming algorithms such as pi calculation. A comparison of the execution time for the NACA 0012 validation case yielded a parallelisation efficiency above 50%. The case studies confirmed the Raspberry Pi 3 B+'s successful parallelisation independent of external software and machines, making it a self-sustaining compact demonstration cluster of parallel computers for CFD.

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32

DASH, S. K. "On the parallelisation of weather and climate models." MAUSAM 52, no. 1 (December 29, 2021): 191–200. http://dx.doi.org/10.54302/mausam.v52i1.1687.

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The numerical models used for weather forecasting and climate studies need very large computing resources. The current research in the field indicates that for accurate forecasts, one needs to use models at very high resolution, sophisticated data assimilation techniques and physical parameterisation schemes and multi-model ensemble integrations. In fact the spatial resolution required for accurate forecasts may demand computing power which is prohibitively high considering the processing power of a single processor of any supercomputer. During the last two decades, the developments in computing technology show the emergence of parallel computers with a number of processors which are capable of supplying enormously large computing power as against a single computer. Today, a cluster of workstations or personal computers can be used in parallel to integrate a global climate model for a long time. However, there are bottlenecks to be overcome in order to achieve maximum efficiency. Inter-processor communication is the key issue in case of global weather and climate models. The present paper aims at discussing the status of parallelisation of weather and climate models at leading centres of operational forecasting and research, the inherent parallelism in weather and climate models, the problems encountered in inter-processing communication and various ways of achieving maximum parallel efficiency.

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33

Asproulis, Nikolaos, and Dimitris Drikakis. "HPC Parallelisation of Boundary Conditions in Multiscale Methods." Journal of Algorithms & Computational Technology 8, no. 4 (December 2014): 357–68. http://dx.doi.org/10.1260/1748-3018.8.4.357.

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34

Andonov, D. A., P. J. Bryanston-Cross, and S. T. Kitson. "Parallelisation methodology for a turbine-blade design program." Computing & Control Engineering Journal 1, no. 6 (1990): 266. http://dx.doi.org/10.1049/cce:19900075.

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35

Saman, M. Y., and D. J. Evans. "Loop parallelisation for pvm-based distributed-memory systems." International Journal of Computer Mathematics 74, no. 3 (January 2000): 265–78. http://dx.doi.org/10.1080/00207160008804941.

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36

Cui, Xiangda, Wagdi G. Habashi, and Vincent Casseau. "MPI Parallelisation of 3D Multiphase Smoothed Particle Hydrodynamics." International Journal of Computational Fluid Dynamics 34, no. 7-8 (June 30, 2020): 610–21. http://dx.doi.org/10.1080/10618562.2020.1785436.

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37

Kadlec, J., F. M. F. Gaston, and G. W. Irwin. "The block regularised parameter estimator and its parallelisation." Automatica 31, no. 8 (August 1995): 1125–36. http://dx.doi.org/10.1016/0005-1098(95)00015-o.

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38

Neal, Jeffrey, Timothy Fewtrell, and Mark Trigg. "Parallelisation of storage cell flood models using OpenMP." Environmental Modelling & Software 24, no. 7 (July 2009): 872–77. http://dx.doi.org/10.1016/j.envsoft.2008.12.004.

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39

MCAVANEY, CHRISTOPHER, and ANDRZEJ GOSCINSKI. "AUTOMATIC PARALLELISATION AND EXECUTION OF APPLICATIONS ON CLUSTERS." Journal of Interconnection Networks 02, no. 03 (September 2001): 331–43. http://dx.doi.org/10.1142/s0219265901000427.

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Parallel execution is a very efficient means of processing vast amounts of data in a small amount of time. Creating parallel applications has never been easy, and requires much knowledge of the task and the execution environment used to execute parallel processes. The process of creating parallel applications can be made easier through using a compiler that automatically parallelises a supplied application. Executing the parallel application is also simplified when a well designed execution environment is used. Such an execution environment provides very powerful operations to the programmer transparently. Combining both a parallelising compiler and execution environment and providing a fully automated parallelisation and execution tool is the aim of this research. The advantage of using such a fully automated tool is that the user does not need to provide any additional input to gain the benefits of parallel execution. This report shows the tool and how it transparently supports the programmer creating parallel applications and supports their execution.

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40

Müller, Eike H., Rupert Ford, Matthew C. Hort, Lois Huggett, Graham Riley, and David J. Thomson. "Parallelisation of the Lagrangian atmospheric dispersion model NAME." Computer Physics Communications 184, no. 12 (December 2013): 2734–45. http://dx.doi.org/10.1016/j.cpc.2013.06.022.

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41

Ajtonyi, István, and Gábor Terstyánszky. "Real-Time Requirements and Parallelisation in Fault Diagnosis." IFAC Proceedings Volumes 28, no. 5 (May 1995): 471–77. http://dx.doi.org/10.1016/s1474-6670(17)47268-5.

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42

Schmidt, F., W. Dax, and M. Luger. "Experiences with the parallelisation of Monte Carlo problems." Progress in Nuclear Energy 24, no. 1-3 (January 1990): 141–51. http://dx.doi.org/10.1016/0149-1970(90)90031-y.

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43

Hall, J. A. J. "Towards a practical parallelisation of the simplex method." Computational Management Science 7, no. 2 (October 11, 2008): 139–70. http://dx.doi.org/10.1007/s10287-008-0080-5.

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44

Epicoco, I., S. Mocavero, F. Macchia, M. Vichi, T. Lovato, S. Masina, and G. Aloisio. "Performance and results of the high-resolution biogeochemical model PELAGOS025 within NEMO." Geoscientific Model Development Discussions 8, no. 12 (December 16, 2015): 10585–625. http://dx.doi.org/10.5194/gmdd-8-10585-2015.

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Abstract. The present work aims at evaluating the scalability performance of a high-resolution global ocean biogeochemistry model (PELAGOS025) on massive parallel architectures and the benefits in terms of the time-to-solution reduction. PELAGOS025 is an on-line coupling between the physical ocean model NEMO and the BFM biogeochemical model. Both the models use a parallel domain decomposition along the horizontal dimension. The parallelisation is based on the message passing paradigm. The performance analysis has been done on two parallel architectures, an IBM BlueGene/Q at ALCF (Argonne Leadership Computing Facilities) and an IBM iDataPlex with Sandy Bridge processors at CMCC (Euro Mediterranean Center on Climate Change). The outcome of the analysis demonstrated that the lack of scalability is due to several factors such as the I/O operations, the memory contention, the load unbalancing due to the memory structure of the BFM component and, for the BlueGene/Q, the absence of a hybrid parallelisation approach.

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45

Fairbrother-Browne, Aine, Sonia García-Ruiz, Regina Hertfelder Reynolds, Mina Ryten, and Alan Hodgkinson. "ensemblQueryR: fast, flexible and high-throughput querying of Ensembl LD API endpoints in R." Gigabyte 2023 (September 14, 2023): 1–10. http://dx.doi.org/10.46471/gigabyte.91.

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We present ensemblQueryR, an R package for querying Ensembl linkage disequilibrium (LD) endpoints. This package is flexible, fast and user-friendly, and optimised for high-throughput querying. ensemblQueryR uses functions that are intuitive and amenable to custom code integration, familiar R object types as inputs and outputs as well as providing parallelisation functionality. For each Ensembl LD endpoint, ensemblQueryR provides two functions, permitting both single- and multi-query modes of operation. The multi-query functions are optimised for large query sizes and provide optional parallelisation to leverage available computational resources and minimise processing time. We demonstrate improved computational performance of ensemblQueryR over an exisiting tool in terms of random access memory (RAM) usage and speed, delivering a 10-fold speed increase whilst using a third of the RAM. Finally, ensemblQueryR is near-agnostic to operating system and computational architecture through Docker and singularity images, making this tool widely accessible to the scientific community.

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46

Jaruga, A., S. Arabas, D. Jarecka, H. Pawlowska, P. K. Smolarkiewicz, and M. Waruszewski. "libmpdata++ 0.1: a library of parallel MPDATA solvers for systems of generalised transport equations." Geoscientific Model Development Discussions 7, no. 6 (November 26, 2014): 8179–273. http://dx.doi.org/10.5194/gmdd-7-8179-2014.

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Abstract. This paper accompanies first release of libmpdata++, a C++ library implementing the Multidimensional Positive-Definite Advection Transport Algorithm (MPDATA). The library offers basic numerical solvers for systems of generalised transport equations. The solvers are forward-in-time, conservative and non-linearly stable. The libmpdata++ library covers the basic second-order-accurate formulation of MPDATA, its third-order variant, the infinite-gauge option for variable-sign fields and a flux-corrected transport extension to guarantee non-oscillatory solutions. The library is equipped with a non-symmetric variational elliptic solver for implicit evaluation of pressure gradient terms. All solvers offer parallelisation through domain decomposition using shared-memory parallelisation. The paper describes the library programming interface, and serves as a user guide. Supported options are illustrated with benchmarks discussed in the MPDATA literature. Benchmark descriptions include code snippets as well as quantitative representations of simulation results. Examples of applications include: homogeneous transport in one, two and three dimensions in Cartesian and spherical domains; shallow-water system compared with analytical solution (originally derived for a 2-D case); and a buoyant convection problem in an incompressible Boussinesq fluid with interfacial instability. All the examples are implemented out of the library tree. Regardless of the differences in the problem dimensionality, right-hand-side terms, boundary conditions and parallelisation approach, all the examples use the same unmodified library, which is a key goal of libmpdata++ design. The design, based on the principle of separation of concerns, prioritises the user and developer productivity. The libmpdata++ library is implemented in C++, making use of the Blitz++ multi-dimensional array containers, and is released as free/libre and open-source software.

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Jaruga, A., S. Arabas, D. Jarecka, H. Pawlowska, P. K. Smolarkiewicz, and M. Waruszewski. "libmpdata++ 1.0: a library of parallel MPDATA solvers for systems of generalised transport equations." Geoscientific Model Development 8, no. 4 (April 8, 2015): 1005–32. http://dx.doi.org/10.5194/gmd-8-1005-2015.

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Abstract. This paper accompanies the first release of libmpdata++, a C++ library implementing the multi-dimensional positive-definite advection transport algorithm (MPDATA) on regular structured grid. The library offers basic numerical solvers for systems of generalised transport equations. The solvers are forward-in-time, conservative and non-linearly stable. The libmpdata++ library covers the basic second-order-accurate formulation of MPDATA, its third-order variant, the infinite-gauge option for variable-sign fields and a flux-corrected transport extension to guarantee non-oscillatory solutions. The library is equipped with a non-symmetric variational elliptic solver for implicit evaluation of pressure gradient terms. All solvers offer parallelisation through domain decomposition using shared-memory parallelisation. The paper describes the library programming interface, and serves as a user guide. Supported options are illustrated with benchmarks discussed in the MPDATA literature. Benchmark descriptions include code snippets as well as quantitative representations of simulation results. Examples of applications include homogeneous transport in one, two and three dimensions in Cartesian and spherical domains; a shallow-water system compared with analytical solution (originally derived for a 2-D case); and a buoyant convection problem in an incompressible Boussinesq fluid with interfacial instability. All the examples are implemented out of the library tree. Regardless of the differences in the problem dimensionality, right-hand-side terms, boundary conditions and parallelisation approach, all the examples use the same unmodified library, which is a key goal of libmpdata++ design. The design, based on the principle of separation of concerns, prioritises the user and developer productivity. The libmpdata++ library is implemented in C++, making use of the Blitz++ multi-dimensional array containers, and is released as free/libre and open-source software.

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Dong, Youkou, Dingtao Yan, and Lan Cui. "An Efficient Parallel Framework for the Discrete Element Method Using GPU." Applied Sciences 12, no. 6 (March 18, 2022): 3107. http://dx.doi.org/10.3390/app12063107.

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The discrete element method (DEM), a discontinuum-based method to simulate the interaction between neighbouring particles of granular materials, suffers from intensive computational workload caused by massive particle numbers, irregular particle shapes, and complicated interaction modes from the meso-scale representation of the macro information. To promote the efficiency of the DEM and enlarge the modelling scales with a higher realism of the particle shapes, parallel computing on the graphics processing unit (GPU) is developed in this paper. The potential data race between the computing cores in the parallelisation is tackled by establishing the contact pair list with a hybrid technique. All the computations in the DEM are made on the GPU cores. Three benchmark cases, a triaxial test of a sand specimen, cone penetration test and granular flow due to a dam break, are used to evaluate the performance of the GPU parallel strategy. Acceleration of the GPU parallel simulations over the conventional CPU sequential counterparts is quantified in terms of speedup. The average speedups with the GPU parallelisation are 84, 73, and 60 for the benchmark cases.

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Epicoco, Italo, Silvia Mocavero, Francesca Macchia, Marcello Vichi, Tomas Lovato, Simona Masina, and Giovanni Aloisio. "Performance and results of the high-resolution biogeochemical model PELAGOS025 v1.0 within NEMO v3.4." Geoscientific Model Development 9, no. 6 (June 10, 2016): 2115–28. http://dx.doi.org/10.5194/gmd-9-2115-2016.

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Abstract. The present work aims at evaluating the scalability performance of a high-resolution global ocean biogeochemistry model (PELAGOS025) on massive parallel architectures and the benefits in terms of the time-to-solution reduction. PELAGOS025 is an on-line coupling between the Nucleus for the European Modelling of the Ocean (NEMO) physical ocean model and the Biogeochemical Flux Model (BFM) biogeochemical model. Both the models use a parallel domain decomposition along the horizontal dimension. The parallelisation is based on the message passing paradigm. The performance analysis has been done on two parallel architectures, an IBM BlueGene/Q at ALCF (Argonne Leadership Computing Facilities) and an IBM iDataPlex with Sandy Bridge processors at the CMCC (Euro Mediterranean Center on Climate Change). The outcome of the analysis demonstrated that the lack of scalability is due to several factors such as the I/O operations, the memory contention, the load unbalancing due to the memory structure of the BFM component and, for the BlueGene/Q, the absence of a hybrid parallelisation approach.

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Downton, A. C. "Top down structured parallelisation of embedded image processing applications." IEE Proceedings - Vision, Image, and Signal Processing 141, no. 6 (1994): 431. http://dx.doi.org/10.1049/ip-vis:19941556.

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