Abstract
The heat transfer analysis coupled with fluid flow is important in many real-world application areas varying from micro-channels to spacecraft’s. Numerical prediction of thermal and fluid flow situation has become very common method using any computational fluid dynamics software or by developing in-house codes. One of the major issues pertinent to numerical analysis lies with immense computational time required for repeated analysis. In this article, technique applied for parallelization of in-house developed generic code using CUDA and OpenMP paradigm is discussed. The parallelized finite-volume method (FVM)-based code for analysis of various problems is analyzed for different boundary conditions. Two GPUs (graphical processing units) are used for parallel execution. Out of four functions in the code (U, V, P, and T), only P function is parallelized using CUDA as it consumes 91% of computational time and the rest functions are parallelized using OpenMP. Parallel performance analysis is carried out for 400, 625, and 900 threads launched from host for parallel execution. Improvement in speedup using CUDA compared with speedup using complete OpenMP parallelization on different computing machines is also provided. Parallel efficiency of the FVM code for different grid size, Reynolds number, internal flow, and external flow is also carried out. It is found that the GPU provides immense speedup and outperforms OpenMP largely. Parallel execution on GPU gives results in a quite acceptable amount of time. The parallel efficiency is found to be close to 90% in internal flow and 10% for external flow.
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References
Abdi DS, Bitsuamlak GT (2015) Asynchronous parallelization of a CFD solver. J Comput Eng. https://doi.org/10.1155/2015/295393
Abdul Razak RK, Afzal A, Mohammed Samee AD, Ramis MK (2019) Effect of cladding on thermal behavior of nuclear fuel element with non-uniform heat generation. Prog Nucl Energy 111:1–14. https://doi.org/10.1016/j.pnucene.2018.10.013
Adelaja AO, Dirker J, Meyer JP (2014) Effects of the thick walled pipes with convective boundaries on laminar flow heat transfer. Appl Energy 130:838–845. https://doi.org/10.1016/j.apenergy.2014.01.072
Afzal A, Ansari Z, Faizabadi A, Ramis M (2017) Parallelization strategies for computational fluid dynamics software: state of the art review. Arch Comput Methods Eng 24:337–363. https://doi.org/10.1007/s11831-016-9165-4
Afzal A, Mohammed Samee AD, Abdul Razak RK, Ramis MK (2019) Effect of spacing on thermal performance characteristics of Li-ion battery cells. J Therm Anal Calorim 135:1797–1811. https://doi.org/10.1007/s10973-018-7664-2
Afzal A, Samee ADM, Razak RKA, Ramis MK (2020a) Thermal management of modern electric vehicle battery systems (MEVBS). J Therm Anal Calorim. https://doi.org/10.1007/s10973-020-09606-x
Afzal A, Ansari Z, Ramis MK (2020b) Parallelization of numerical conjugate heat transfer analysis in parallel plate channel using OpenMP. Arab J Sci Eng. https://doi.org/10.1007/s13369-020-04640-1
Amritkar A, Tafti D, Liu R, Kufrin R, Chapman B (2012) OpenMP parallelism for fluid and fluid-particulate systems. Parallel Comput 38:501–517. https://doi.org/10.1016/j.parco.2012.05.005
Amritkar A, Deb S, Tafti D (2014) Efficient parallel CFD-DEM simulations using OpenMP. J Comput Phys 256:501–519. https://doi.org/10.1016/j.jcp.2013.09.007
Arici ME, Aydin O (2009) Conjugate heat transfer in thermally developing laminar flow with viscous dissipation effects. Heat Mass Transf 45:1199–1203. https://doi.org/10.1007/s00231-009-0494-9
Ate A, Darici S, Bilir E (2010) Unsteady conjugated heat transfer in thick walled pipes involving two-dimensional wall and axial fluid conduction with uniform heat flux boundary condition. Int J Heat Mass Transf 53:5058–5064. https://doi.org/10.1016/j.ijheatmasstransfer.2010.07.059
Bhatti MM, Ullah Khan S, Anwar Bég O, Kadir A (2020) Differential transform solution for Hall and ion-slip effects on radiative-convective Casson flow from a stretching sheet with convective heating. Heat Transf Res 49:872–888
Bilir Ş (2002) Transient conjugated heat transfer in pipes involving two-dimensional wall and axial fluid conduction. Int J Heat Mass Transf 45:1781–1788. https://doi.org/10.1016/S0017-9310(01)00270-8
Couder-Castaneda C, Barrios-Pina H, Gitler I, Arroyo M (2015) Performance of a code migration for the simulation of supersonic ejector flow to SMP, MIC, and GPU using OpenMP, OpenMP + LEO, and OpenACC directives. Sci Program. https://doi.org/10.1155/2015/739107
Cukurel B, Arts T, Selcan C (2012) Conjugate heat transfer characterization in cooling channels. J Therm Sci 21:286–294. https://doi.org/10.1007/s11630-012-0546-1
Darmana D, Deen NG, Kuipers JAM (2006) Parallelization of an Euler-Lagrange model using mixed domain decomposition and a mirror domain technique: application to dispersed gas-liquid two-phase flow. J Comput Phys 220:216–248. https://doi.org/10.1016/j.jcp.2006.05.011
Eyheramendy D (2003) Object-Oriented parallel CFD with JAVA. Parallel Comput Fluid Dyn Adv Numer Methods Softw Appl 2004:409–416. https://doi.org/10.1016/B978-044451612-1/50052-4
Gorobets A, Soukov S, Bogdanov P (2018) Multilevel parallelization for simulating compressible turbulent flows on most kinds of hybrid supercomputers. Comput Fluids 173:171–177. https://doi.org/10.1016/j.compfluid.2018.03.011
Gropp WD, Kaushik DK, Keyes DE, Smith BF (2001) High-performance parallel implicit CFD. Parallel Comput 27:337–362. https://doi.org/10.1016/S0167-8191(00)00075-2
Guan T, Zhang J, Shan Y, Hang J (2017) Conjugate heat transfer on leading edge of a conical wall subjected to external cold flow and internal hot jet impingement from chevron nozzle—part 1: experimental analysis. Int J Heat Mass Transf 106:329–338. https://doi.org/10.1016/j.ijheatmasstransfer.2016.06.101
Harman SA, Cole KD (2001) Conjugate heat transfer from a two-layer substrate model of a convectively cooled circuit board. J Electron Package 123:156–158. https://doi.org/10.1115/1.1348011
He J, Liu L, Jacobi AM (2011) Conjugate thermal analysis of air-cooled discrete flush-mounted heat sources in a horizontal channel. J Electron Package 133:041001. https://doi.org/10.1115/1.4005299
Jacobsen D, Senocak I (2011) Scalability of incompressible flow computations on multi-GPU clusters using dual-level and tri-level parallelism. In: 49th AIAA aerospace sciences meeting including the new horizons forum and aerospace exposition, p 947
Jia R, Sundén B (2004) Parallelization of a multi-blocked CFD code via three strategies for fluid flow and heat transfer analysis. Comput Fluids 33:57–80. https://doi.org/10.1016/S0045-7930(03)00029-X
Kafui DK, Johnson S, Thornton C, Seville JPK (2011) Parallelization of a Lagrangian–Eulerian DEM/CFD code for application to fluidized beds. Powder Technol 207:270–278
Kaladgi AR, Afzal A, AD MS, MK R (2019) Investigation of dimensionless parameters and geometry effects on heat transfer characteristics of liquid sodium flowing over a vertical flat plate. Heat Transf Asian Res 48:62–79. https://doi.org/10.1002/htj.21368
Karimi G, Li X (2012) Thermal management of lithium-ion batteries for electric vehicles. Int J Energy Res 37:13–24. https://doi.org/10.1002/er.1956
Khan SU, Shehzad SA, Nasir S (2019) Unsteady flow of chemically reactive Oldroyd-B fluid over oscillatory moving surface with thermo-diffusion and heat absorption/generation effects. J Braz Soc Mech Sci Eng 41:72
Khan N, Nabwey HA, Hashmi MS, Khan SU, Tlili I (2020) A theoretical analysis for mixed convection flow of maxwell fluid between two infinite isothermal stretching disks with heat source/sink. Symmetry (Basel) 12:62
Lai J, Li H, Tian Z (2018) CPU/GPU heterogeneous parallel CFD solver and optimizations. In: Proceedings of 2018 international conference service robotics technology. ACM, Chengdu, China, pp 88–92
Lehmkuhl O, Borrell R, Soria M, Oliva A (2007) TermoFluids: a new parallel unstructured CFD code for the simulation of turbulent industrial problems on low cost PC cluster. Parallel Comput Fluid Dyn 2009:275–282. https://doi.org/10.1007/978-3-540-92744-0
Lindstedt M, Karvinen R (2017) Conjugated heat transfer from a uniformly heated plate and a plate fin with uniform base heat flux. Int J Heat Mass Transf 107:89–95. https://doi.org/10.1016/j.ijheatmasstransfer.2016.10.079
Meng F, Dong S, Wang J, Guo D (2016) A new algorithm of global tightly-coupled transient heat transfer based on quasi-steady flow to the conjugate heat transfer problem. Theor Appl Mech Lett 6:233–235. https://doi.org/10.1016/j.taml.2016.08.005
Mininni PD, Rosenberg D, Reddy R, Pouquet A (2011) A hybrid MPI-OpenMP scheme for scalable parallel pseudospectral computations for fluid turbulence. Parallel Comput 37:316–326
Mohamme Samee AD, Afzal A, Ramis MK, Abdul Razak RK (2019) Optimal spacing in heat generating parallel plate channel: a conjugate approach. Int J Therm Sci 136:267–277. https://doi.org/10.1016/j.ijthermalsci.2018.10.025
Mudigere D, Sridharan S, Deshpande A, Park J, Heinecke A, Smelyanskiy M, Kaul B, Dubey P, Kaushik D, Keyes D (2015) Exploring shared-memory optimizations for an unstructured mesh CFD application on modern parallel systems. In: 2015 IEEE international parallel and distributed processing symposium, May 25. IEEE, pp 723–732
Niedermeier CA, Janßen CF, Indinger T (2018) Massively-parallel multi-GPU simulations for fast and accurate automotive aerodynamics. In: 7th European conference on computational fluid dynamics
Niemeyer KE, Sung C-J (2014) Recent progress and challenges in exploiting graphics processors in computational fluid dynamics. J Supercomput 67:528–564. https://doi.org/10.1007/s11227-013-1015-7
Oktay E, Akay HU, Merttopcuoglu O (2011) Parallelized structural topology optimization and CFD coupling for design of aircraft wing structures. Comput Fluids 49:141–145. https://doi.org/10.1016/j.compfluid.2011.05.005
Passoni G, Cremonesi P, Alfonsi G (2001) Analysis and implementation of a parallelization strategy on a Navier–Stokes solver for shear flow simulations. Parallel Comput 27:1665–1685. https://doi.org/10.1016/S0167-8191(01)00114-4
Peigin S, Epstein B (2004) Embedded parallelization approach for optimization in aerodynamic design. J Supercomput 29:243–263. https://doi.org/10.1023/B:SUPE.0000032780.68664.1b
Pinto RN, Afzal A, Navaneeth IM, Ramis MK (2016) Computational analysis of flow in turbines. In: IEEE invention computer technology (ICICT). International Conference Coimbatore, India: (3), pp 1–5. https://doi.org/10.1109/INVENTIVE.2016.7830174
Pinto R, Afzal A, D’Souza L, Ansari Z, Mohammed Samee AD (2017) Computational fluid dynamics in turbomachinery: a review of state of the art. Arch Comput Methods Eng 24:467–479. https://doi.org/10.1007/s1183
Poddar A, Chatterjee R, Chakravarty A, Ghosh K, Mukhopadhyay A, Sen S (2015) Thermodynamic analysis of a solid nuclear fuel element surrounded by flow of coolant through a concentric annular channel. Prog Nucl Energy 85:178–191. https://doi.org/10.1016/j.pnucene.2015.06.018
Samee AdM, Afzal A, Razak Rk A, Mk R (2018) Effect of Prandtl number on the average exit temperature of coolant in a heat-generating vertical parallel plate channel: a conjugate analysis. Heat Transf Asian Res. https://doi.org/10.1002/htj.21330
Schulz M, Krafczyk M, Tölke J, Rank E (2002) Parallelization strategies and efficiency of CFD computations in complex geometries using lattice Boltzmann methods on high-performance computers. High Perform Sci Eng Comput 21:115–122. https://doi.org/10.1007/978-3-642-55919-8
Shan P, Zhu R, Wang F, Wu J (2018) Efficient approximation of free-surface Green function and OpenMP parallelization in frequency-domain wave–body interactions. J Mar Sci Technol. https://doi.org/10.1007/s00773-018-0568-9
Shang Y (2009) A distributed memory parallel Gauss–Seidel algorithm for linear algebraic systems. Comput Math Appl 57:1369–1376. https://doi.org/10.1016/j.camwa.2009.01.034
Sheraton MV, Sloot PMA (2018) Parallel performance analysis of bacterial biofilm simulation models. Computer Science—ICCS. Lecture Notes Computer Science, vol 10862. Springer International Publishing, Berlin, pp 496–505. https://doi.org/10.1007/978-3-319-93713-7
Simmendinger C, Kügeler E (2010) Hybrid parallelization of a turbomachinery CFD code: performance enhancements on multicore architectures. In: Proceedings of the V European conference on computational fluid dynamics ECCOMAS CFD
Steijl R, Barakos GN (2018) Parallel evaluation of quantum algorithms for computational fluid dynamics. Comput Fluids 173:22–28. https://doi.org/10.1016/j.compfluid.2018.03.080
Ullah KS, Ali N, Hayat T, Abbas Z (2019) Heat transfer analysis based on Cattaneo–Christov heat flux model and convective boundary conditions for flow over an oscillatory stretching surface. Therm Sci 23:443–455
Walther JH, Sbalzarini IF (2009) Large-scale parallel discrete element simulations of granular flow. Eng Comput 26:688–697. https://doi.org/10.1108/02644400910975478
Wang X, Guo L, Ge W, Tang D, Ma J, Yang Z et al (2005) Parallel implementation of macro-scale pseudo-particle simulation for particle-fluid systems. Comput Chem Eng 29:1543–1553. https://doi.org/10.1016/j.compchemeng.2004.12.006
Wang YX, Zhang LL, Liu W, Cheng XH, Zhuang Y, Chronopoulos AT (2018) Performance optimizations for scalable CFD applications on hybrid CPU + MIC heterogeneous computing system with millions of cores. Comput Fluids 173:226–236. https://doi.org/10.1016/j.compfluid.2018.03.005
Xu XM, He R (2013) Research on the heat dissipation performance of battery pack based on forced air cooling. J Power Sour 240:33–41. https://doi.org/10.1016/j.jpowsour.2013.03.004
Xu C, Deng X, Zhang L, Fang J, Wang G, Jiang Y et al (2014) Collaborating CPU and GPU for large-scale high-order CFD simulations with complex grids on the TianHe-1A supercomputer. J Comput Phys 278:275–297. https://doi.org/10.1016/j.jcp.2014.08.024
Xu Z, Zhao H, Zheng C (2015) Accelerating population balance-Monte Carlo simulation for coagulation dynamics from the Markov jump model, stochastic algorithm and GPU parallel computing. J Comput Phys 281:844–863. https://doi.org/10.1016/j.jcp.2014.10.055
Zhang LT, Wagner GJ, Liu WK (2002) A parallelized meshfree method with boundary enrichment for large-scale CFD. J Comput Phys 176:483–506. https://doi.org/10.1006/jcph.2002.6999
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Communicated by Jorge X. Velasco.
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Afzal, A., Ansari, Z. & Ramis, M.K. Parallel performance analysis of coupled heat and fluid flow in parallel plate channel using CUDA. Comp. Appl. Math. 39, 219 (2020). https://doi.org/10.1007/s40314-020-01244-1
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DOI: https://doi.org/10.1007/s40314-020-01244-1