Using multiple graphics accelerators to solve the two-dimensional inverse heat conduction problem

In this paper, we present a novel parallel algorithm implemented on graphics accelerators to solve the two-dimensional inverse heat conduction problem (estimation of the temporo-spatial heat transfer coefficients without any prior knowledge of the thermal boundary conditions) based on Particle Swarm...

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Veröffentlicht in:	Computer methods in applied mechanics and engineering Jg. 336; S. 286 - 303
Hauptverfasser:	Szénási, Sándor, Felde, Imre
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier B.V 01.07.2018 Elsevier BV
Schlagworte:	Algorithms Conduction heating Conductive heat transfer Data parallel algorithm Divergence Genetic algorithm Genetic algorithms Graphics accelerators Graphics processing units Heat conductivity Heat transfer coefficients Heuristic Heuristic methods Inverse heat conduction problem Inverse problems Launching Mathematical analysis Particle accelerators Particle Swarm Optimisation Warp Inverse heat conduction problem Particle Swarm Optimisation Data parallel algorithm Genetic algorithm Graphics accelerators
ISSN:	0045-7825, 1879-2138
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Abstract	In this paper, we present a novel parallel algorithm implemented on graphics accelerators to solve the two-dimensional inverse heat conduction problem (estimation of the temporo-spatial heat transfer coefficients without any prior knowledge of the thermal boundary conditions) based on Particle Swarm Optimisation method. In the absence of analytical solutions, there are several heuristic methods to solve the problem, but the unacceptable high runtime (several days) makes these unsuitable for practical use. This paper presents the methods on how to adapt the original sequential algorithm to an efficient data-parallel one, keeping in mind the main features of graphics processing units (launching multiple threads on all multiprocessors, storing data in fast on-chip memory, eliminating warp divergence and memory transfer latency, using the host and device together, etc.). The achieved ∼45× speed-up (without any accuracy degradation) makes the heuristic methods suitable for practical use. Some of the proposed ideas are generally useable; therefore, this paper can be considered a step-by-step guide for researchers of other fields to speed-up general purpose calculations and evaluate the results. •Our goal is to solve the two-dimensional IHCP using heuristic optimisation methods.•A multi-level parallel algorithm implemented on GPU and CPU cores is presented.•It is 100x faster than the original sequential one (the accuracy is the same).•Details of optimisation (memory transfers, warp divergence, etc.) are discussed.
AbstractList	In this paper, we present a novel parallel algorithm implemented on graphics accelerators to solve the two-dimensional inverse heat conduction problem (estimation of the temporo-spatial heat transfer coefficients without any prior knowledge of the thermal boundary conditions) based on Particle Swarm Optimisation method. In the absence of analytical solutions, there are several heuristic methods to solve the problem, but the unacceptable high runtime (several days) makes these unsuitable for practical use. This paper presents the methods on how to adapt the original sequential algorithm to an efficient data-parallel one, keeping in mind the main features of graphics processing units (launching multiple threads on all multiprocessors, storing data in fast on-chip memory, eliminating warp divergence and memory transfer latency, using the host and device together, etc.). The achieved ∼45× speed-up (without any accuracy degradation) makes the heuristic methods suitable for practical use. Some of the proposed ideas are generally useable; therefore, this paper can be considered a step-by-step guide for researchers of other fields to speed-up general purpose calculations and evaluate the results. In this paper, we present a novel parallel algorithm implemented on graphics accelerators to solve the two-dimensional inverse heat conduction problem (estimation of the temporo-spatial heat transfer coefficients without any prior knowledge of the thermal boundary conditions) based on Particle Swarm Optimisation method. In the absence of analytical solutions, there are several heuristic methods to solve the problem, but the unacceptable high runtime (several days) makes these unsuitable for practical use. This paper presents the methods on how to adapt the original sequential algorithm to an efficient data-parallel one, keeping in mind the main features of graphics processing units (launching multiple threads on all multiprocessors, storing data in fast on-chip memory, eliminating warp divergence and memory transfer latency, using the host and device together, etc.). The achieved ∼45× speed-up (without any accuracy degradation) makes the heuristic methods suitable for practical use. Some of the proposed ideas are generally useable; therefore, this paper can be considered a step-by-step guide for researchers of other fields to speed-up general purpose calculations and evaluate the results. •Our goal is to solve the two-dimensional IHCP using heuristic optimisation methods.•A multi-level parallel algorithm implemented on GPU and CPU cores is presented.•It is 100x faster than the original sequential one (the accuracy is the same).•Details of optimisation (memory transfers, warp divergence, etc.) are discussed.
Author	Szénási, Sándor Felde, Imre
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Cites_doi	10.12700/APH.11.09.2014.09.1 10.1590/S1678-58782006000100001 10.1016/j.jmatprotec.2015.06.016 10.1016/j.ijheatmasstransfer.2006.10.045 10.1016/S1665-6423(14)71676-1 10.1016/j.cma.2016.03.038 10.1016/j.parco.2014.02.002 10.1080/10407790903116469 10.1080/10407780490478533 10.1016/j.ijheatmasstransfer.2016.04.073 10.1016/j.cma.2016.08.016 10.1016/j.jpdc.2016.04.014 10.1109/IPDPS.2010.5470413 10.1016/j.ijheatmasstransfer.2013.11.028 10.1109/ICNN.1995.488968 10.1016/j.jpdc.2007.09.004 10.1016/j.parco.2012.10.002 10.1016/j.cpc.2012.06.005 10.1016/j.jqsrt.2007.07.013 10.1016/j.jpdc.2012.04.003 10.1016/j.ijheatmasstransfer.2016.06.103
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References	Skinderowicz (b26) 2016; 98 L. Chen, O. Villa, S. Krishnamoorthy, G.R. Gao, Dynamic load balancing on single- and multi-GPU systems, in: Proceedings of the 2010 IEEE International Symposium on Parallel and Distributed Processing, IPDPS 2010, 2010 Martínez-Frutos, Herrero-Pérez (b32) 2016; 311 Felde, Szénási (b23) 2016; 11 Cook (b30) 2012 Gur, Pan (b2) 2009 Szénási, Felde, Kovács (b21) 2015 Klimeš, Štětina (b11) 2015; 226 URL Beck, Blackwell, Clair (b3) 1985 Sanders, Kandrot (b29) 2010 Alifanov (b4) 1994 Xu (b6) 2016; 103 Oksman, Yu, Kytönen, Louhenkilpi (b1) 2014; 11 Colaço, Orlande, Dulikravich (b14) 2006; 28 Cotronis, Konstantinidis, Louka, Missirlis (b9) 2014; 40 I. Felde, S. Szénási, A. Kenéz, S. Wei, R. Colas, Determination of complex thermal boundary conditions using a particle swarm optimization method in: 5th International Conference on Distortion Engineering, Bremen, 2015, pp. 227–236. (b27) 2014 Vakili, Gadala (b19) 2009; 56 Kim, Baek (b5) 2004; 46 A.L. Fazenda, C.L. Mendes, L.V. Kale, J. Panetta, E.R. Rodrigues, Dynamic load balancing in GPU-based systems - early experiments Jacobsen, Senocak (b10) 2013; 39 Rong, Zhang, Shi, Guo (b12) 2014; 70 Özisik, Orlande (b15) 2000 Satake, Yoshimori, Suzuki (b13) 2012; 183 Lin, Hsieh, Chang, Hsiung (b35) 2014; 12 Verma, Balaji (b16) 2007; 50 Kareem, Gao, Ahmed (b7) 2016; 100 . Qi, Ruan, Shi, An, Tan (b18) 2008; 109 Bana, Kruzel, Bielaski (b25) 2016; 305 Cheng, Grossman, Ty McKercher (b31) 2013 Szénási, Felde (b20) 2016 J. Kennedy, R. Eberhart, Particle swarm optimization, in: Neural Networks, 1995. Proceedings., IEEE International Conference on, Vol. 4, 1995, pp. 1942–1948 Ltaief, Gabriel, Garbey (b8) 2008; 68 Brodtkorb, Hagen, Sætra (b24) 2013; 73 Kirk, Hwu (b28) 2010 10.1016/j.cma.2018.03.024_b34 10.1016/j.cma.2018.03.024_b33 Felde (10.1016/j.cma.2018.03.024_b23) 2016; 11 Lin (10.1016/j.cma.2018.03.024_b35) 2014; 12 Beck (10.1016/j.cma.2018.03.024_b3) 1985 Brodtkorb (10.1016/j.cma.2018.03.024_b24) 2013; 73 Özisik (10.1016/j.cma.2018.03.024_b15) 2000 Cook (10.1016/j.cma.2018.03.024_b30) 2012 Xu (10.1016/j.cma.2018.03.024_b6) 2016; 103 Klimeš (10.1016/j.cma.2018.03.024_b11) 2015; 226 Skinderowicz (10.1016/j.cma.2018.03.024_b26) 2016; 98 Colaço (10.1016/j.cma.2018.03.024_b14) 2006; 28 Qi (10.1016/j.cma.2018.03.024_b18) 2008; 109 Szénási (10.1016/j.cma.2018.03.024_b21) 2015 10.1016/j.cma.2018.03.024_b22 Oksman (10.1016/j.cma.2018.03.024_b1) 2014; 11 Sanders (10.1016/j.cma.2018.03.024_b29) 2010 Verma (10.1016/j.cma.2018.03.024_b16) 2007; 50 Cheng (10.1016/j.cma.2018.03.024_b31) 2013 Kareem (10.1016/j.cma.2018.03.024_b7) 2016; 100 Martínez-Frutos (10.1016/j.cma.2018.03.024_b32) 2016; 311 Ltaief (10.1016/j.cma.2018.03.024_b8) 2008; 68 Cotronis (10.1016/j.cma.2018.03.024_b9) 2014; 40 Alifanov (10.1016/j.cma.2018.03.024_b4) 1994 Kim (10.1016/j.cma.2018.03.024_b5) 2004; 46 (10.1016/j.cma.2018.03.024_b27) 2014 Jacobsen (10.1016/j.cma.2018.03.024_b10) 2013; 39 Gur (10.1016/j.cma.2018.03.024_b2) 2009 Satake (10.1016/j.cma.2018.03.024_b13) 2012; 183 Rong (10.1016/j.cma.2018.03.024_b12) 2014; 70 Szénási (10.1016/j.cma.2018.03.024_b20) 2016 Kirk (10.1016/j.cma.2018.03.024_b28) 2010 10.1016/j.cma.2018.03.024_b17 Vakili (10.1016/j.cma.2018.03.024_b19) 2009; 56 Bana (10.1016/j.cma.2018.03.024_b25) 2016; 305
References_xml	– volume: 50 start-page: 1706 year: 2007 end-page: 1714 ident: b16 article-title: Multi-parameter estimation in combined conduction-radiation from a plane parallel participating medium using genetic algorithms publication-title: Int. J. Heat Mass Transfer – year: 2013 ident: b31 article-title: Professional CUDA C Programming – year: 1994 ident: b4 article-title: Inverse Heat Transfer Problems – reference: I. Felde, S. Szénási, A. Kenéz, S. Wei, R. Colas, Determination of complex thermal boundary conditions using a particle swarm optimization method in: 5th International Conference on Distortion Engineering, Bremen, 2015, pp. 227–236. – year: 2010 ident: b28 article-title: Programming massively parallel processors: A hands-on approach – volume: 56 start-page: 119 year: 2009 end-page: 141 ident: b19 article-title: Effectiveness and efficiency of particle swarm optimization technique in inverse heat conduction analysis publication-title: Numer. Heat Transf. Part A Fundam. – volume: 73 start-page: 4 year: 2013 end-page: 13 ident: b24 article-title: Graphics processing unit (GPU) programming strategies and trends in GPU computing publication-title: J. Parallel Distrib. Comput. – year: 2009 ident: b2 article-title: Handbook of Thermal Process Modeling of Steels – volume: 305 start-page: 827 year: 2016 end-page: 848 ident: b25 article-title: Finite element numerical integration for first order approximations on multi-and many-core architectures publication-title: Comput. Methods Appl. Mech. Engrg. – reference: A.L. Fazenda, C.L. Mendes, L.V. Kale, J. Panetta, E.R. Rodrigues, Dynamic load balancing in GPU-based systems - early experiments, – volume: 100 start-page: 121 year: 2016 end-page: 130 ident: b7 article-title: Unsteady simulations of mixed convection heat transfer in a 3D closed lid-driven cavity publication-title: Int. J. Heat Mass Transfer – start-page: 365 year: 2015 end-page: 369 ident: b21 article-title: Solving one-dimensional IHCP with particle swarm optimization using graphics accelerators publication-title: 10th Jubilee IEEE International Symposium on Applied Computational Intelligence and Informatics – reference: J. Kennedy, R. Eberhart, Particle swarm optimization, in: Neural Networks, 1995. Proceedings., IEEE International Conference on, Vol. 4, 1995, pp. 1942–1948, – volume: 70 start-page: 1040 year: 2014 end-page: 1049 ident: b12 article-title: Numerical study of heat transfer enhancement in a pipe filled with porous media by axisymmetric TLB model based on GPU publication-title: Int. J. Heat Mass Transfer – volume: 103 start-page: 285 year: 2016 end-page: 290 ident: b6 article-title: A novel numerical method for solving heat conduction problems publication-title: Int. J. Heat Mass Transfer – year: 1985 ident: b3 article-title: Inverse Heat Conduction – volume: 46 start-page: 367 year: 2004 end-page: 381 ident: b5 article-title: Inverse surface radiation analysis in an axisymmetric cylindrical enclosure using a hybrid genetic algorithm publication-title: Numer. Heat Transfer, Part A-Appl. – volume: 28 start-page: 1 year: 2006 end-page: 24 ident: b14 article-title: Inverse and optimization problems in heat transfer publication-title: J. Braz. Soc. Mech. Sci. Eng. – volume: 98 start-page: 48 year: 2016 end-page: 60 ident: b26 article-title: The GPU-based parallel ant colony system publication-title: J. Parallel Distrib. Comput. – volume: 11 start-page: 288 year: 2016 end-page: 300 ident: b23 article-title: Estimation of temporospatial boundary conditions using a particle swarm optimisation technique publication-title: Int. J. Microstruct. Mater. Prop. – year: 2014 ident: b27 article-title: CUDA C Programming Guide – reference: , URL – volume: 183 start-page: 2376 year: 2012 end-page: 2385 ident: b13 article-title: Optimizations of a GPU accelerated heat conduction equation by a programming of CUDA Fortran from an analysis of a PTX file publication-title: Comput. Phys. Comm. – volume: 11 year: 2014 ident: b1 article-title: The effective thermal conductivity method in continuous casting of steel publication-title: Acta Polytech. Hung. – volume: 226 start-page: 1 year: 2015 end-page: 14 ident: b11 article-title: A rapid GPU-based heat transfer and solidification model for dynamic computer simulations of continuous steel casting publication-title: J. Mater Process. Technol. – volume: 311 start-page: 393 year: 2016 end-page: 414 ident: b32 article-title: Large-scale robust topology optimization using multi-GPU systems publication-title: Comput. Methods Appl. Mech. Engrg. – volume: 39 start-page: 1 year: 2013 end-page: 20 ident: b10 article-title: Multi-level parallelism for incompressible flow computations on GPU clusters publication-title: Parallel Comput. – year: 2000 ident: b15 article-title: Inverse Heat Transfer: Fundamentals and Applications – volume: 68 start-page: 663 year: 2008 end-page: 677 ident: b8 article-title: Fault tolerant algorithms for heat transfer problems publication-title: J. Parallel Distrib. Comput. – reference: . – reference: L. Chen, O. Villa, S. Krishnamoorthy, G.R. Gao, Dynamic load balancing on single- and multi-GPU systems, in: Proceedings of the 2010 IEEE International Symposium on Parallel and Distributed Processing, IPDPS 2010, 2010, – volume: 40 start-page: 173 year: 2014 end-page: 185 ident: b9 article-title: A comparison of CPU and GPU implementations for solving the Convection Diffusion equation using the local Modified SOR method publication-title: Parallel Comput. – year: 2012 ident: b30 article-title: CUDA Programming – volume: 12 start-page: 1176 year: 2014 end-page: 1186 ident: b35 article-title: Efficient workload balancing on heterogeneous gpus using mixedinteger non-linear programming publication-title: J. Appl. Res. Technol. – start-page: 279 year: 2010 ident: b29 article-title: CUDA by example publication-title: Review Literature and Arts of the Americas – start-page: 263 year: 2016 end-page: 267 ident: b20 article-title: Heat transfer simulation using GPUs publication-title: 20th IEEE Jubilee International Conference on Intelligent Engineering Systems – volume: 109 start-page: 476 year: 2008 end-page: 493 ident: b18 article-title: Application of multi-phase particle swarm optimization technique to inverse radiation problem publication-title: J. Quant. Spectrosc. Radiat. Transfer – volume: 11 issue: 9 year: 2014 ident: 10.1016/j.cma.2018.03.024_b1 article-title: The effective thermal conductivity method in continuous casting of steel publication-title: Acta Polytech. Hung. doi: 10.12700/APH.11.09.2014.09.1 – start-page: 365 year: 2015 ident: 10.1016/j.cma.2018.03.024_b21 article-title: Solving one-dimensional IHCP with particle swarm optimization using graphics accelerators – volume: 11 start-page: 288 issue: 3/4 year: 2016 ident: 10.1016/j.cma.2018.03.024_b23 article-title: Estimation of temporospatial boundary conditions using a particle swarm optimisation technique publication-title: Int. J. Microstruct. Mater. Prop. – volume: 28 start-page: 1 issue: 1 year: 2006 ident: 10.1016/j.cma.2018.03.024_b14 article-title: Inverse and optimization problems in heat transfer publication-title: J. Braz. Soc. Mech. Sci. Eng. doi: 10.1590/S1678-58782006000100001 – volume: 226 start-page: 1 year: 2015 ident: 10.1016/j.cma.2018.03.024_b11 article-title: A rapid GPU-based heat transfer and solidification model for dynamic computer simulations of continuous steel casting publication-title: J. Mater Process. Technol. doi: 10.1016/j.jmatprotec.2015.06.016 – volume: 50 start-page: 1706 issue: 9–10 year: 2007 ident: 10.1016/j.cma.2018.03.024_b16 article-title: Multi-parameter estimation in combined conduction-radiation from a plane parallel participating medium using genetic algorithms publication-title: Int. J. Heat Mass Transfer doi: 10.1016/j.ijheatmasstransfer.2006.10.045 – year: 2012 ident: 10.1016/j.cma.2018.03.024_b30 – volume: 12 start-page: 1176 issue: 6 year: 2014 ident: 10.1016/j.cma.2018.03.024_b35 article-title: Efficient workload balancing on heterogeneous gpus using mixedinteger non-linear programming publication-title: J. Appl. Res. Technol. doi: 10.1016/S1665-6423(14)71676-1 – year: 2009 ident: 10.1016/j.cma.2018.03.024_b2 – year: 2000 ident: 10.1016/j.cma.2018.03.024_b15 – volume: 305 start-page: 827 year: 2016 ident: 10.1016/j.cma.2018.03.024_b25 article-title: Finite element numerical integration for first order approximations on multi-and many-core architectures publication-title: Comput. Methods Appl. Mech. Engrg. doi: 10.1016/j.cma.2016.03.038 – volume: 40 start-page: 173 issue: 7 year: 2014 ident: 10.1016/j.cma.2018.03.024_b9 article-title: A comparison of CPU and GPU implementations for solving the Convection Diffusion equation using the local Modified SOR method publication-title: Parallel Comput. doi: 10.1016/j.parco.2014.02.002 – volume: 56 start-page: 119 issue: 2 year: 2009 ident: 10.1016/j.cma.2018.03.024_b19 article-title: Effectiveness and efficiency of particle swarm optimization technique in inverse heat conduction analysis publication-title: Numer. Heat Transf. Part A Fundam. doi: 10.1080/10407790903116469 – year: 1994 ident: 10.1016/j.cma.2018.03.024_b4 – volume: 46 start-page: 367 issue: 4 year: 2004 ident: 10.1016/j.cma.2018.03.024_b5 article-title: Inverse surface radiation analysis in an axisymmetric cylindrical enclosure using a hybrid genetic algorithm publication-title: Numer. Heat Transfer, Part A-Appl. doi: 10.1080/10407780490478533 – volume: 100 start-page: 121 year: 2016 ident: 10.1016/j.cma.2018.03.024_b7 article-title: Unsteady simulations of mixed convection heat transfer in a 3D closed lid-driven cavity publication-title: Int. J. Heat Mass Transfer doi: 10.1016/j.ijheatmasstransfer.2016.04.073 – volume: 311 start-page: 393 year: 2016 ident: 10.1016/j.cma.2018.03.024_b32 article-title: Large-scale robust topology optimization using multi-GPU systems publication-title: Comput. Methods Appl. Mech. Engrg. doi: 10.1016/j.cma.2016.08.016 – volume: 98 start-page: 48 year: 2016 ident: 10.1016/j.cma.2018.03.024_b26 article-title: The GPU-based parallel ant colony system publication-title: J. Parallel Distrib. Comput. doi: 10.1016/j.jpdc.2016.04.014 – ident: 10.1016/j.cma.2018.03.024_b22 – ident: 10.1016/j.cma.2018.03.024_b34 doi: 10.1109/IPDPS.2010.5470413 – start-page: 279 year: 2010 ident: 10.1016/j.cma.2018.03.024_b29 article-title: CUDA by example – volume: 70 start-page: 1040 year: 2014 ident: 10.1016/j.cma.2018.03.024_b12 article-title: Numerical study of heat transfer enhancement in a pipe filled with porous media by axisymmetric TLB model based on GPU publication-title: Int. J. Heat Mass Transfer doi: 10.1016/j.ijheatmasstransfer.2013.11.028 – start-page: 263 year: 2016 ident: 10.1016/j.cma.2018.03.024_b20 article-title: Heat transfer simulation using GPUs – year: 2010 ident: 10.1016/j.cma.2018.03.024_b28 – ident: 10.1016/j.cma.2018.03.024_b17 doi: 10.1109/ICNN.1995.488968 – volume: 68 start-page: 663 issue: 5 year: 2008 ident: 10.1016/j.cma.2018.03.024_b8 article-title: Fault tolerant algorithms for heat transfer problems publication-title: J. Parallel Distrib. Comput. doi: 10.1016/j.jpdc.2007.09.004 – ident: 10.1016/j.cma.2018.03.024_b33 – volume: 39 start-page: 1 issue: 1 year: 2013 ident: 10.1016/j.cma.2018.03.024_b10 article-title: Multi-level parallelism for incompressible flow computations on GPU clusters publication-title: Parallel Comput. doi: 10.1016/j.parco.2012.10.002 – volume: 183 start-page: 2376 issue: 11 year: 2012 ident: 10.1016/j.cma.2018.03.024_b13 article-title: Optimizations of a GPU accelerated heat conduction equation by a programming of CUDA Fortran from an analysis of a PTX file publication-title: Comput. Phys. Comm. doi: 10.1016/j.cpc.2012.06.005 – volume: 109 start-page: 476 issue: 3 year: 2008 ident: 10.1016/j.cma.2018.03.024_b18 article-title: Application of multi-phase particle swarm optimization technique to inverse radiation problem publication-title: J. Quant. Spectrosc. Radiat. Transfer doi: 10.1016/j.jqsrt.2007.07.013 – year: 2014 ident: 10.1016/j.cma.2018.03.024_b27 – volume: 73 start-page: 4 issue: 1 year: 2013 ident: 10.1016/j.cma.2018.03.024_b24 article-title: Graphics processing unit (GPU) programming strategies and trends in GPU computing publication-title: J. Parallel Distrib. Comput. doi: 10.1016/j.jpdc.2012.04.003 – year: 1985 ident: 10.1016/j.cma.2018.03.024_b3 – volume: 103 start-page: 285 year: 2016 ident: 10.1016/j.cma.2018.03.024_b6 article-title: A novel numerical method for solving heat conduction problems publication-title: Int. J. Heat Mass Transfer doi: 10.1016/j.ijheatmasstransfer.2016.06.103 – year: 2013 ident: 10.1016/j.cma.2018.03.024_b31
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Snippet	In this paper, we present a novel parallel algorithm implemented on graphics accelerators to solve the two-dimensional inverse heat conduction problem...
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SubjectTerms	Algorithms Conduction heating Conductive heat transfer Data parallel algorithm Divergence Genetic algorithm Genetic algorithms Graphics accelerators Graphics processing units Heat conductivity Heat transfer coefficients Heuristic Heuristic methods Inverse heat conduction problem Inverse problems Launching Mathematical analysis Particle accelerators Particle Swarm Optimisation Warp
Title	Using multiple graphics accelerators to solve the two-dimensional inverse heat conduction problem
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