Abstract
In silico investigation of skin permeation is an important but also computationally demanding problem. To resolve all scales involved in full detail will not only require exascale computing capacities but also suitable parallel algorithms. This article investigates the applicability of the time-parallel Parareal algorithm to a brick and mortar setup, a precursory problem to skin permeation. The C++ library Lib4PrM implementing Parareal is combined with the UG4 simulation framework, which provides the spatial discretization and parallelization. The combination’s performance is studied with respect to convergence and speedup. It is confirmed that anisotropies in the domain and jumps in diffusion coefficients only have a minor impact on Parareal’s convergence. The influence of load imbalances in time due to differences in number of iterations required by the spatial solver as well as spatio-temporal weak scaling is discussed.
Similar content being viewed by others
Notes
The coarse method is often represented by \(\mathcal {G}\), probably because of the French word “gros” for coarse.
References
Anissimov, Y.G., Roberts, M.S.: Diffusion modeling of percutaneous absorption kinetics: 3. Variable diffusion and partition coefficients, consequences for stratum corneum depth profiles and desorption kinetics. J. Pharm. Sci. 93(2), 470–487 (2004). doi:10.1002/jps.10567
Anissimov, Y.G., Roberts, M.S.: Diffusion modelling of percutaneous absorption kinetics: 4. Effects of slow equilibration process within stratum corneum on absorbtion and desorption kinetics. J. Pharm. Sci. 98, 772–781 (2009). doi:10.1002/jps.21461
Arteaga, A., Ruprecht, D., Krause, R.: A stencil-based implementation of Parareal in the C\(++\) domain specific embedded language STELLA. Appl. Math. Comput. (2015). doi:10.1016/j.amc.2014.12.055
Aubanel, E.: Scheduling of tasks in the Parareal algorithm. Parallel Comput. 37, 172–182 (2011). doi:10.1016/j.parco.2010.10.004
Bal, G.: On the convergence and the stability of the Parareal algorithm to solve partial differential equations. In: Kornhuber, R., et al. (eds.) Domain Decomposition Methods in Science and Engineering, Lecture Notes in Computational Science and Engineering, vol. 40, pp. 426–432. Springer, Berlin (2005). doi:10.1007/3-540-26825-1_43
Bylaska, E.J., Weare, J.Q., Weare, J.H.: Extending molecular simulation time scales: parallel in time integrations for high-level quantum chemistry and complex force representations. J. Chem. Phys. 139(7), 074114 (2013). doi:10.1063/1.4818328
Celledoni, E., Kvamsdal, T.: Parallelization in time for thermo-viscoplastic problems in extrusion of aluminium. Int. J. Numer. Methods Eng. 79(5), 576–598 (2009). doi:10.1002/nme.2585
Demmel, J.W., Eisenstat, S.C., Gilbert, J.R., Li, X.S., Liu, J.W.H.: A supernodal approach to sparse partial pivoting. SIAM J. Matrix Anal. Appl. 20(3), 720–755 (1999)
Dick, B., Vogel, A., Khabi, D., Rupp, M., Küster, U., Wittum, G.: Utilization of empirically determined energy-optimal CPU-frequencies in a numerical simulation code. Comput. Vis. Sci. (2015). doi:10.1007/s00791-015-0249-8
Dongarra, J., et al.: Applied Mathematics Research for Exascale Computing. Technical Report LLNL-TR-651000, Lawrence Livermore National Laboratory (2014). http://science.energy.gov/~/media/ascr/pdf/research/am/docs/EMWGreport.pdf
Elwasif, W.R., Foley, S.S., Bernholdt, D.E., Berry, L.A., Samaddar, D., Newman, D.E., Snchez, R.S.: A dependency-driven formulation of parareal: parallel-in-time solution of PDEs as a many-task application. In: Proceedings of the 2011 ACM International Workshop on Many Task Computing on Grids and Supercomputers, p. 1524 (2011). doi:10.1145/2132876.2132883
Emmett, M., Minion, M.L.: Toward an efficient parallel in time method for partial differential equations. Commun. Appl. Math. Comput. Sci. 7, 105132 (2012). doi:10.2140/camcos.2012.7.105
Falgout, R.D., Friedhoff, S., Kolev, T.V., MacLachlan, S.P., Schroder, J.B.: Parallel time integration with multigrid. SIAM J. Sci. Comput. 36, C635C661 (2014)
Farhat, C., Chandesris, M.: Time-decomposed parallel time-integrators: theory and feasibility studies for fluid, structure, and fluid-structure applications. Int. J. Numer. Methods Eng. 58(9), 13971434 (2003). doi:10.1002/nme.860
Gander, M.J., Vandewalle, S.: On the superlinear and linear convergence of the Parareal algorithm. In: Widlund, O.B., Keyes, D.E. (eds.) Domain Decomposition Methods in Science and Engineering, Lecture Notes in Computational Science and Engineering, vol. 55, pp. 291–298. Springer, Berlin (2007). doi:10.1007/978-3-540-34469-8_34
Hansen, S., Lehr, C.M., Schaefer, U.F.: Modeling the human skin barrier—towards a better understanding of dermal absorption. Adv. Drug Deliv. Rev. (2013). doi:10.1016/j.addr.2012.12.002
Kreienbuehl, A., Benedusi, P., Ruprecht, D., Krause, R.: Time parallel gravitational collapse simulation (2015) (in preparation)
Li, X., Demmel, J., Gilbert, J., iL. Grigori, Shao, M., Yamazaki, I.: SuperLU Users’ Guide. Technical Report LBNL-44289, Lawrence Berkeley National Laboratory (1999). http://crd.lbl.gov/~xiaoye/SuperLU/. Last update: August 2011
Lions, J.L., Maday, Y., Turinici, G.: A “parareal” in time discretization of PDE’s. C. R. l’Acad. Sci. Ser. I Math. 332, 661668 (2001). doi:10.1016/S0764-4442(00)01793-6
Minion, M.L., Speck, R., Bolten, M., Emmett, M., Ruprecht, D.: Interweaving PFASST and parallel multigrid. SIAM J. Sci. Comput. (2015). arxiv:1407.6486
Minion, M.L.: A hybrid Parareal spectral deferred corrections method. Commun. Appl. Math. Comput. Sci. 5(2), 265301 (2010). doi:10.2140/camcos.2010.5.265
Mula, O.: Some contributions towards the parallel simulation of time dependent neutron transport and the integration of observed data in real time. Ph.D. Thesis, Université Pierre et Marie Curie - Paris VI (2014). https://tel.archives-ouvertes.fr/tel-01081601
Naegel, A., Heisig, M., Wittum, G.: A comparison of two- and three-dimensional models for the simulation of the permeability of human stratum corneum. Eur. J. Pharm. Biopharm. 72(2), 332–338 (2009). doi:10.1016/j.ejpb.2008.11.009. http://www.sciencedirect.com/science/article/B6T6C-4V1KMMP-1/2/b906a3a90140385ba35b48bed48fdef7
Querleux, B. (ed.): Computational Biophysics of the Skin. Pan Stanford Publishing, Singapore (2014)
Randles, A., Kaxiras, E.: Parallel in time approximation of the lattice Boltzmann method for laminar flows. J. Comput. Phys. 270, 577586 (2014). doi:10.1016/j.jcp.2014.04.006
Reiter, S., Vogel, A., Heppner, I., Rupp, M., Wittum, G.: A massively parallel geometric multigrid solver on hierarchically distributed grids. Comput. Vis. Sci. 16(4), 151–164 (2013). doi:10.1007/s00791-014-0231-x
Rim, J.E., Pinsky, P.M., van Osdol, W.W.: Using the method of homogenization to calculate the effective diffusivity of the stratum corneum with permeable corneocytes. J. Biomech. 41(4), 788–796 (2008). doi:10.1016/j.jbiomech.2007.11.011. http://www.sciencedirect.com/science/article/B6T82-4RWHXFR-2/2/bfe8e93f74d145a105071a106d6d227c
Rim, J.E., Pinsky, P.M., van Osdol, W.W.: Multiscale modeling framework of transdermal drug delivery. Ann. Biomed. Eng. 37(6), 1217–1229 (2009)
Ruprecht, D., Speck, R., Emmett, M., Bolten, M., Krause, R.: Poster: Extreme-scale space–time parallelism. In: Proceedings of the 2013 Conference on High Performance Computing Networking, Storage and Analysis Companion, SC’13 Companion (2013). http://sc13.supercomputing.org/sites/default/files/PostersArchive/tech_posters/post148s2-file3.pdf
Ruprecht, D., Speck, R., Krause, R.: Parareal for diffusion problems with space- and time-dependent coefficients. In: Domain Decomposition Methods in Science and Engineering XXII, Lecture Notes in Computational Science and Engineering, vol. 104, pp. 3–10. Springer, Switzerland (2015). doi:10.1007/978-3-319-18827-0_1
Ruprecht, D.: Convergence of Parareal with spatial coarsening. PAMM 14(1), 1031–1034 (2014). doi:10.1002/pamm.201410490
Samaddar, D., Newman, D.E., Snchez, R.S.: Parallelization in time of numerical simulations of fully-developed plasma turbulence using the Parareal algorithm. J. Comput. Phys. 229, 65586573 (2010). doi:10.1016/j.jcp.2010.05.012
Speck, R., Ruprecht, D., Krause, R., Emmett, M., Minion, M.L., Winkel, M., Gibbon, P.: A massively space–time parallel N-body solver. In: Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis, SC’12, p. 92:1–92:11. IEEE Computer Society Press, Los Alamitos, CA, USA (2012). doi:10.1109/SC.2012.6
Vogel, A., Calotoiu, A., Strube, A., Reiter, S., Nägel, A., Wolf, F., Wittum, G.: 10,000 performance models per minute-scalability of the UG4 simulation framework. In: Träff, J.L., Hunold, S., Versaci, F. (eds.) Euro-Par 2015: parallel processing, pp. 519–531. Springer, Berlin (2015)
Vogel, A., Reiter, S., Rupp, M., Nägel, A., Wittum, G.: UG4: A novel flexible software system for simulating pde based models on high performance computers. Comput. Vis. Sci. 16(4), 165–179 (2013). doi:10.1007/s00791-014-0232-9
Wang, T.F., Kasting, G.B., Nitsche, J.M.: A multiphase microscopic diffusion model for stratum corneum permeability. I. Formulation, solution, and illustrative results for representative compounds. J. Pharm. Sci. 95(3), 620–648 (2006). doi:10.1002/jps.20509
Wang, T.F., Kasting, G.B., Nitsche, J.M.: A multiphase microscopic diffusion model for stratum corneum permeability. II. Estimation of physicochemical parameters, and application to a large permeability database. J. Pharm. Sci. 96(11), 3024–3051 (2007). doi:10.1002/jps.20883
Author information
Authors and Affiliations
Corresponding author
Additional information
Communicated by Volker Schulz.
This research is funded by the Deutsche Forschungsgemeinschaft (DFG) as part of the “Exasolvers” project in the Priority Programme 1648 ”Software for Exascale Computing” (SPPEXA) and by the Swiss National Science Foundation (SNSF) under the lead agency agreement as grant SNF-145271. The research of A.K., D.R., and R.K. is also funded through the FUtuRe SwIss Electrical InfraStructure (FURIES) project of the Swiss Competence Centers for Energy Research (SCCER).
Rights and permissions
About this article
Cite this article
Kreienbuehl, A., Naegel, A., Ruprecht, D. et al. Numerical simulation of skin transport using Parareal. Comput. Visual Sci. 17, 99–108 (2015). https://doi.org/10.1007/s00791-015-0246-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00791-015-0246-y