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Статті в журналах з теми "Parallel Smoothers"
Xie, Dexuan. "Analysis of a Class of Parallel Multigrid Smoothers." BIT Numerical Mathematics 44, no. 4 (December 2004): 813–28. http://dx.doi.org/10.1007/s10543-004-3830-y.
Повний текст джерелаYang, Xiang, and Rajat Mittal. "Efficient relaxed-Jacobi smoothers for multigrid on parallel computers." Journal of Computational Physics 332 (March 2017): 135–42. http://dx.doi.org/10.1016/j.jcp.2016.12.010.
Повний текст джерелаPoddar, Shashi, and John L. Crassidis. "Adaptive Lag Smoother for State Estimation." Sensors 22, no. 14 (July 15, 2022): 5310. http://dx.doi.org/10.3390/s22145310.
Повний текст джерелаCIEGIS, R., F. GASPAR, and C. RODRIGO. "On The Parallel Multiblock Geometric Multigrid Algorithm." Computational Methods in Applied Mathematics 8, no. 3 (2008): 223–36. http://dx.doi.org/10.2478/cmam-2008-0016.
Повний текст джерелаAxelsson, O. "Analysis of incomplete matrix factorizations as multigrid smoothers for vector and parallel computers." Applied Mathematics and Computation 19, no. 1-4 (July 1986): 3–22. http://dx.doi.org/10.1016/0096-3003(86)90094-9.
Повний текст джерелаJohn, Volker, and Lutz Tobiska. "Numerical performance of smoothers in coupled multigrid methods for the parallel solution of the incompressible Navier-Stokes equations." International Journal for Numerical Methods in Fluids 33, no. 4 (2000): 453–73. http://dx.doi.org/10.1002/1097-0363(20000630)33:4<453::aid-fld15>3.0.co;2-0.
Повний текст джерелаHolmes, Steven J., Peter J. Wright, and Robert J. Fryer. "Evidence from survey data for regional variability in cod dynamics in the North Sea and West of Scotland." ICES Journal of Marine Science 65, no. 2 (January 25, 2008): 206–15. http://dx.doi.org/10.1093/icesjms/fsm192.
Повний текст джерелаGräbel, Jens, Bruno Lang, and Peer Ueberholz. "Performance Optimization for the Parallel Gauss-Seidel Smoother." PAMM 5, no. 1 (December 2005): 831–32. http://dx.doi.org/10.1002/pamm.200510387.
Повний текст джерелаSoanca, Andrada, Alexandra Roman, Andreea Ciurea, Iulia Cristina Micu, Andrei Picos, and Sofia Iozon (Ene). "The evaluation of root surface modifications after different subgingival mechanical instrumentation techniques – an in vitro study." Romanian Journal of Stomatology 69, no. 1 (March 31, 2023): 43–49. http://dx.doi.org/10.37897/rjs.2023.1.8.
Повний текст джерелаWang, Zhaojie, Feifeng Zheng, and Ming Liu. "Identical Parallel Machine Scheduling Considering Workload Smoothness Index." Applied Sciences 13, no. 15 (July 28, 2023): 8720. http://dx.doi.org/10.3390/app13158720.
Повний текст джерелаДисертації з теми "Parallel Smoothers"
Joginipelly, Arjun. "Implementation of Separable & Steerable Gaussian Smoothers on an FPGA." ScholarWorks@UNO, 2010. http://scholarworks.uno.edu/td/98.
Повний текст джерелаFleissner, Florian. "Parallel object oriented simulation with Lagrangian particle methods." Aachen Shaker, 2009. http://d-nb.info/1000976742/04.
Повний текст джерелаGathmann-Hüttemann, Stefan. "Untersuchungen über objektorientierte Design-Patterns für massiv-parallele Teilchensimulationsverfahren anhand von smoothed particle hydrodynamics." [S.l. : s.n.], 2002. http://deposit.ddb.de/cgi-bin/dokserv?idn=964104091.
Повний текст джерелаLundqvist, Viktor. "A smoothed particle hydrodynamic simulation utilizing the parallel processing capabilites of the GPUs." Thesis, Linköping University, Department of Science and Technology, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-21761.
Повний текст джерелаSimulating fluid behavior has proven to be a demanding challenge which requires complex computational models and highly efficient data structures. Smoothed Particle Hydrodynamics (SPH) is a particle based computational model used to simulate fluid behavior that has been found capable of producing convincing results. However, the SPH algorithm is computational heavy which makes it cumbersome to work with.
This master thesis describes how the SPH algorithm can be accelerated by utilizing the GPU’s computational resources. It describes a model for how to distribute the work load on the GPU and presents a suitable data structure. In addition, it proposes a method to represent and handle moving objects in the fluids surroundings. Finally, the performance gain due to the GPU is evaluated by comparing processing times with an identical implementation running solely on the CPU.
Eliasson, André, and Pontus Franzén. "Accelerating IISPH : A Parallel GPGPU Solution Using CUDA." Thesis, Blekinge Tekniska Högskola, Institutionen för kreativa teknologier, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-10429.
Повний текст джерелаGóes, Marciana Lima. "Desenvolvimento de um simulador numérico empregando o método Smoothed Particle Hydrodynamics para a resolução de escoamentos incompressíveis. Implementação computacional em paralelo (CUDA)." Universidade do Estado do Rio de Janeiro, 2012. http://www.bdtd.uerj.br/tde_busca/arquivo.php?codArquivo=4029.
Повний текст джерелаNeste trabalho, foi desenvolvido um simulador numérico baseado no método livre de malhas Smoothed Particle Hydrodynamics (SPH) para a resolução de escoamentos de fluidos newtonianos incompressíveis. Diferentemente da maioria das versões existentes deste método, o código numérico faz uso de uma técnica iterativa na determinação do campo de pressões. Este procedimento emprega a forma diferencial de uma equação de estado para um fluido compressível e a equação da continuidade a fim de que a correção da pressão seja determinada. Uma versão paralelizada do simulador numérico foi implementada usando a linguagem de programação C/C++ e a Compute Unified Device Architecture (CUDA) da NVIDIA Corporation. Foram simulados três problemas, o problema unidimensional do escoamento de Couette e os problemas bidimensionais do escoamento no interior de uma Cavidade (Shear Driven Cavity Problem) e da Quebra de Barragem (Dambreak).
In this work a numerical simulator was developed based on the mesh-free Smoothed Particle Hydrodynamics (SPH) method to solve incompressible newtonian fluid flows. Unlike most existing versions of this method, the numerical code uses an iterative technique in the pressure field determination. This approach employs a differential state equation for a compressible fluid and the continuity equation to calculate the pressure correction. A parallel version of the numerical code was implemented using the Programming Language C/C++ and Compute Unified Device Architecture (CUDA) from the NVIDIA Corporation. The numerical results were validated and the speed-up evaluated for an one-dimensional Couette flow and two-dimensional Shear Driven Cavity and Dambreak problems.
Góes, Josecley Fialho. "Resolução numérica de escoamentos compressíveis empregando um método de partículas livre de malhas e o processamento em paralelo (CUDA)." Universidade do Estado do Rio de Janeiro, 2011. http://www.bdtd.uerj.br/tde_busca/arquivo.php?codArquivo=3082.
Повний текст джерелаThe conventional mesh-based numerical methods have been widely applied to solving problems in Computational Fluid Dynamics. However, in problems involving fluid flow free surfaces, large explosions, large deformations, discontinuities, shock waves etc. these methods suffer from some inherent difficulties which limit their applications to solving these problems. Meshfree particle methods have emerged as an alternative to the conventional grid-based methods. This work introduces the Smoothed Particle Hydrodynamics (SPH), a meshfree Lagrangian particle method to solve compressible flows. Two numerical codes have been developed, serial and parallel versions, using the Programming Language C/C++ and Compute Unified Device Architecture (CUDA). CUDA is NVIDIAs parallel computing architecture that enables dramatic increasing in computing performance by harnessing the power of the Graphics Processing Units (GPUs). The numerical results were validated and the speedup evaluated for the Shock Tube and Blast Wave one-dimensional problems and Shear Driven Cavity Problem.
Yeylaghi, Shahab. "A parallel explicit incompressible smoothed particle hydrodynamics (ISPH) model for nonlinear hydrodynamic applications." Thesis, 2016. http://hdl.handle.net/1828/7661.
Повний текст джерелаGraduate
Xiao, Jun-Yi, and 蕭鈞懌. "Parallel Multilevel Smoothed Aggregation Schwarz Preconditioned Newton-Krylov Algorithms for Poisson-Boltzmann Problem." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/s7re35.
Повний текст джерела國立中央大學
數學系
104
The use of multi-grid (Multigrid method) extending algorithm as preconditioner parallel Newton-Krylov-Schwarz algorithms to reduce the number of iterations and calculation time determined to accelerate the solution of nonlinear equations large relaxation. The group, this nonlinear system is mediated by the finite element method, as in the three-dimensional discrete Poisson-Boltzmann equation; in glial scientific applications, do the three-dimensional numerical simulation of charged colloidal particles in the electrolyte, and to further explore symmetric and asymmetric electrolyte solution for electric field and the potential energy of the impact. Poisson-Boltzmann equation for the description of charged colloidal particles in the electrolyte, the potential energy distribution formula. And conduct research on parallel performance, optimization iterations, and time, and compare the effectiveness of different aggregation methods.
Gathmann-Hüttemann, Stefan [Verfasser]. "Untersuchungen über objektorientierte Design-Patterns für massiv-parallele Teilchensimulationsverfahren anhand von smoothed particle hydrodynamics / vorgelegt von Stefan Gathmann genannt Hüttemann." 2002. http://d-nb.info/964104091/34.
Повний текст джерелаКниги з теми "Parallel Smoothers"
Dubanov, Aleksandr. Computer simulation in pursuit problems. ru: Publishing Center RIOR, 2022. http://dx.doi.org/10.29039/02102-6.
Повний текст джерелаЧастини книг з теми "Parallel Smoothers"
Bolten, Matthias, and Oliver Letterer. "Increasing Arithmetic Intensity in Multigrid Methods on GPUs Using Block Smoothers." In Parallel Processing and Applied Mathematics, 515–25. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32149-3_48.
Повний текст джерелаDouglas, Craig C., Sachit Malhotra, and Martin H. Schultz. "“Transpose Free” Alternating Direction Smoothers for Serial and Parallel Multigrid Methods." In Advances in Computational Mathematics, 39–52. Boca Raton: CRC Press, 2023. http://dx.doi.org/10.1201/9781003419839-3.
Повний текст джерелаKrzyżanowski, Piotr. "A Class of Block Smoothers for Multigrid Solution of Saddle Point Problems with Application to Fluid Flow." In Parallel Processing and Applied Mathematics, 1006–13. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24669-5_130.
Повний текст джерелаReiter, Sebastian, Andreas Vogel, Arne Nägel, and Gabriel Wittum. "A Massively Parallel Multigrid Method with Level Dependent Smoothers for Problems with High Anisotropies." In High Performance Computing in Science and Engineering ´16, 667–75. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47066-5_45.
Повний текст джерелаHeuveline, Vincent, Dimitar Lukarski, Nico Trost, and Jan-Philipp Weiss. "Parallel Smoothers for Matrix-Based Geometric Multigrid Methods on Locally Refined Meshes Using Multicore CPUs and GPUs." In Facing the Multicore - Challenge II, 158–71. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30397-5_14.
Повний текст джерелаNakasato, N., M. Mori, and K. Nomoto. "Smoothed Particle Hydrodynamics with Parallel Virtual Machine." In Astrophysics and Space Science Library, 269–72. Dordrecht: Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-010-0864-8_34.
Повний текст джерелаEmans, Maximilian. "Combining Smoother and Residual Calculation in v-cycle AMG for Symmetric Problems." In Parallel Processing and Applied Mathematics, 651–60. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31464-3_66.
Повний текст джерелаMoon, Sung-Whan, Padmanabhan Pillai, and Kang G. Shin. "STREAMER: Hardware Support for Smoothed Transmission of Stored Video over ATM." In Parallel Computer Routing and Communication, 75–88. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/3-540-69352-1_7.
Повний текст джерелаDomínguez, J. M., A. Barreiro, A. J. C. Crespo, O. García-Feal, and M. Gómez-Gesteira. "Parallel CPU/GPU Computing for Smoothed Particle Hydrodynamics Models." In Recent Advances in Fluid Dynamics with Environmental Applications, 477–91. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-27965-7_34.
Повний текст джерелаTitov, Alexander, Sergey Khrapov, Victor Radchenko, and Alexander Khoperskov. "Aerodynamic Models of Complicated Constructions Using Parallel Smoothed Particle Hydrodynamics." In Communications in Computer and Information Science, 173–84. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-05807-4_15.
Повний текст джерелаТези доповідей конференцій з теми "Parallel Smoothers"
Douglas, Craig C., and Gundolf Haase. "Parallel ADI Smoothers for Multigrid." In 2013 12th International Symposium on Distributed Computing and Applications to Business, Engineering & Science (DCABES). IEEE, 2013. http://dx.doi.org/10.1109/dcabes.2013.25.
Повний текст джерелаYaghoobi, Fatemeh, Adrien Corenflos, Sakira Hassan, and Simo Sarkka. "Parallel Iterated Extended and Sigma-Point Kalman Smoothers." In ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2021. http://dx.doi.org/10.1109/icassp39728.2021.9413364.
Повний текст джерелаKashi, Aditya, Syam Vangara, and Sivakumaran Nadarajah. "Asynchronous fine-grain parallel smoothers for computational fluid dynamics." In 2018 Fluid Dynamics Conference. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2018. http://dx.doi.org/10.2514/6.2018-3558.
Повний текст джерелаKashi, Aditya, Syam Vangara, and Sivakumaran Nadarajah. "Correction: Asynchronous fine-grain parallel smoothers for computational fluid dynamics." In 2018 Fluid Dynamics Conference. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2018. http://dx.doi.org/10.2514/6.2018-3558.c1.
Повний текст джерелаTuminaro, R. S., and C. Tong. "Parallel Smoothed Aggregation Multigrid : Aggregation Strategies on Massively Parallel Machines." In ACM/IEEE SC 2000 Conference. IEEE, 2000. http://dx.doi.org/10.1109/sc.2000.10008.
Повний текст джерелаManea, A. M. "A Massively Parallel Restriction-Smoothed Basis Multiscale Solver on Multicore and GPU Architectures." In SPE Reservoir Simulation Conference. SPE, 2021. http://dx.doi.org/10.2118/203939-ms.
Повний текст джерелаManea, Abdulrahman. "GPU-Enabled Scalable Multiscale Solver for Reservoir Simulation." In International Petroleum Technology Conference. IPTC, 2022. http://dx.doi.org/10.2523/iptc-22024-ms.
Повний текст джерелаWu, Shikang, Hanyu Hong, Yu Shi, and Xia Hua. "Blind deblurring with image layer separation using relative smoothness." In Parallel Processing of Images and Optimization Techniques, edited by Bruce Hirsch, Hong Sun, and Chao Cai. SPIE, 2020. http://dx.doi.org/10.1117/12.2538072.
Повний текст джерелаLi, Jian, Zhenhua Li, Yao Liu, and Zhi-Li Zhang. "Do Twin Clouds Make Smoothness for Transoceanic Video Telephony?" In 2015 44th International Conference on Parallel Processing (ICPP). IEEE, 2015. http://dx.doi.org/10.1109/icpp.2015.35.
Повний текст джерелаLukyanov, A., and C. Vuik. "Parallel Fully Implicit Smoothed Particle Hydrodynamics Based Multiscale Method." In ECMOR XV - 15th European Conference on the Mathematics of Oil Recovery. Netherlands: EAGE Publications BV, 2016. http://dx.doi.org/10.3997/2214-4609.201601748.
Повний текст джерелаЗвіти організацій з теми "Parallel Smoothers"
Baker, A. H., R. D. Falgout, T. V. Kolev, and U. M. Yang. Multigrid Smoothers for Ultra-Parallel Computing: Additional Theory and Discussion. Office of Scientific and Technical Information (OSTI), June 2011. http://dx.doi.org/10.2172/1122232.
Повний текст джерела