Abstract
In this paper, we developed a computational hydrodynamics (CHD) numerical model based on the Unified Parallel C (UPC) computing architecture. UPC is the extension of ISO C following the Partitioned Global Address Space (PGAS) architecture which harnesses the ease of programming of the shared memory paradigm while enabling the exploitation of data locality. UPC computing stores the data having the affinity with the corresponding computing thread in the local memory section which significantly improves the computational speedup. UPC requires a unique arrangement to achieve the optimal combination of programmability, portability, and performance scalability. The UPC-CHD model is currently governed by the unsteady, laminar, and incompressible Navier–Stokes (NS) equations with domain decomposition. The temporal term is discretized with the two-step explicit scheme from the Lax-Wendroff family of predictor–correctors. The convective fluxes are computed by the ROE scheme with the third-order upwind-biased algorithm, and the viscous terms are discretized with the second-order central differencing scheme. The calculations of the flux predictor and corrector are then distributed using a UPC work-sharing function, which is based on the single-program multiple-data approach (SPMD). The data structure together with the discretization is uniquely arranged for UPC architecture using blocked-cyclic techniques and affinity calculation algorithms. Three reference cases of laminar Blasius boundary layer, Poiseuille’s flow and Couette’s flow were simulated with UPC-CHD. The accuracy of these reference cases was first validated using the respective analytical solution, which was followed by evaluating the model’s computational performance with an SGI UV-2000 server of 100 cores. The speedup results confirm the high efficiency of the proposed computer architecture as compared to other existing ones. With proper optimization, the speed up of the UPC-CHD model is almost 56 times and 5 times faster than the sequential version and sole-UPC version without optimization, respectively.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Li, Y. -L., Lin, P. -J., & Tung, K. -L. (2011). CFD analysis of fluid flow through a spacer-filled disk-type membrane module. Desalination, 283, 140–147.
Sousa, P., Soares, A., Monteiro, E., & Rouboa, A. (2014). A CFD study of the hydrodynamics in a desalination membrane filled with spacers. Desalination, 349, 22–30.
Bucs, S. S., Radu, A. I., Lavric, V., Vrouwenvelder, J. S., & Picioreanu, C. (2014). Effect of different commercial feed spacers on biofouling of reverse osmosis membrane systems: A numerical study. Desalination, 343, 26–37.
Sobieski, W., & Zhang, Q. (2017). Multi-scale modeling of flow resistance in granular porous media. Mathematics and Computers in Simulation, 132, 159–171.
Jajcevic, D., Siegmann, E., Radeke, C., & Khinast, J. G. (2013). Large-scale CFD–DEM simulations of fluidized granular systems. Chemical Engineering Science, 98, 298–310.
Jamshed, S. (2015). The way the HPC works in CFD. In Using HPC for computational fluid dynamics (pp. 41–79). Oxford: Academic Press.
Gourdain, N., Gicquel, L., Montagnac, M., Vermorel, O., Gazaix, M., & Staffelbach, G. (2009). High performance parallel computing of flows in complex geometries: I. methods. Computational Science & Discovery, 2, 015003.
Toro, E. F. (2009). The Riemann Solver of Roe. In Riemann solvers and numerical methods for fluid dynamics: A practical introduction (pp. 345–376). Berlin, Heidelberg: Springer.
Kermani, M., & Plett, E. (2001). Roe scheme in generalized coordinates. I—formulations. In 39th Aerospace Sciences Meeting and Exhibit. American Institute of Aeronautics and Astronautics.
Kermani, M., & Plett, E. (2001). Roe scheme in generalized coordinates. II—application to inviscid and viscous flows. In 39th Aerospace Sciences Meeting and Exhibit. American Institute of Aeronautics and Astronautics.
White, F. M. (1991). Ch. 7. Viscous fluid flow (2nd ed., pp. 457–528). New York: McGraw-Hill.
Munson, B. R., Young, D. F., & Okiishi, T. H. (2006). Ch. 6. Fundamentals of fluid mechanics (6th ed., pp. 263–331). Hoboken, NJ: Wiley.
Acknowledgements
This research study is funded by the internal core funding from the Nanyang Environment and Water Research Institute (NEWRI), Nanyang Technological University (NTU), Singapore. The first author is grateful to NTU’s Interdisciplinary Graduate School (IGS) for the 4-year Ph.D. scholarship for his study. The second author is grateful to NTU for the 4-year Nanyang President Graduate Scholarship (NPGS) for his Ph.D. study.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Vu, T.T., Chew, A.W.Z., Law, A.WK. (2018). UPC Architecture for High-Performance Computational Hydrodynamics. In: Gourbesville, P., Cunge, J., Caignaert, G. (eds) Advances in Hydroinformatics . Springer Water. Springer, Singapore. https://doi.org/10.1007/978-981-10-7218-5_3
Download citation
DOI: https://doi.org/10.1007/978-981-10-7218-5_3
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-7217-8
Online ISBN: 978-981-10-7218-5
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)