Abstract
The implementation of multiscale numerical simulations on heterogeneous hardware architectures is presented in the paper. The simulations are composed of coupled micro and macro scale approaches, which are implemented by using cellular automata and finite element method respectively. Details of both of these methods are described in the papers as well. The simulations were performed for the problem of material heat treatment (macro scale) with simultaneous application of grain growth calculation (micro scale). Comparison of quantitative results obtained by using separated and coupled computing methods are presented in form of speedup and efficiency coefficients.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Grosman, F.: Application of the flow stress function in programmes for computer simulation of plastic working processes. Journal of Materials Processing Technology 64, 169–180 (1997)
Estrin, Y., Mecking, H.A.: Unified phenomenological description of work hardening and creep based on one-parameter models. Acta Metallurgica 32, 57–70 (1984)
Madej, L., Rauch, L., Yang, C.: Strain distribution analysis based on the digital material representation. Archives of Metallurgy and Materials 54, 499–507 (2009)
Goetz, R.L., Seetharaman, V.: Modeling dynamic recrystalization using cellular automata. Scripta Materialia 38, 405–413 (1998)
Pietrzyk, M., Madej, L., Rauch, L., Golab, R.: Multiscale modeling of microstructure evolution during laminar cooling of hot rolled DP steels. Archives of Civil and Mechanical Engineering 10, 57–67 (2010)
Gawad, J., Pietrzyk, M.: Application of CAFE coupled model to description of microstructure development during dynamic recrystallization. Archives of Metallurgy and Materials 52, 257–266 (2007)
Cannataro, M., Di Gregorio, S., Rongo, R., Spataro, W., Spezzano, G., Talia, D.: A parallel cellular automata environment on multicomputers for computational science. Parallel Computing 21, 803–823 (1995)
Patra, A.K., Laszloffy, A., Long, J.: Data structures and load balancing for parallel adaptive hp finite-element methods. Computers & Mathematics with Applications 46(1), 105–123 (2003)
Čiegis, R., Čiegis, R., Meilūnas, M., Jankevičiūtė, G., Starikovičius, V.: Parallel mumerical algorithm for optimization of electrical cables. Mathematical Modelling and Analysis 13(4), 471–482 (2008)
Murugesan, S.: Harnessing Green IT: Principle and Practices. IT Professional 10(1), 24–33 (2008)
Brodtkorb, A.R., Dyken, C., Hagen, T.R., Hjelmervik, J.M., Storaasli, O.O.: State-of-the-art in heterogeneous computing. Scientific Programming 18, 1–33 (2010)
Maciol, P., Plaszewski, P., Banas, K.: 3D finite element numerical integration on GPUs. Procedia Computer Science 1, 1093–1100 (2010)
Spytkowski, P., Klimek, T., Rauch, L., Madej, L.: Implementation of cellular automata framework dedicated to digital material representation. Computer Methods in Materials Science 9(2), 283–288 (2009)
Chen, F., Cui, Z., Liu, J., Chen, W., Chen, S.: Mesoscale simulation of the high-temperature austenizing and dynamic recrystallization by coupling a cellular automaton with a topology deformation technique. Materials Science and Engineering A 527, 5539–5549 (2010)
Thomas, D.B., Howes, L., Luk, W.: A comparison of CPUs, GPUs, FPGAs, and massively parallel processor arrays for random number generation. In: Proceeding of the ACM/SIGDA International Symposium on Field Programmable Gate Arrays, FPGA 2009, pp. 63–72 (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Rauch, L., Bzowski, K., Rodzaj, A. (2012). OpenCL Implementation of Cellular Automata Finite Element (CAFE) Method. In: Wyrzykowski, R., Dongarra, J., Karczewski, K., Waśniewski, J. (eds) Parallel Processing and Applied Mathematics. PPAM 2011. Lecture Notes in Computer Science, vol 7204. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31500-8_39
Download citation
DOI: https://doi.org/10.1007/978-3-642-31500-8_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31499-5
Online ISBN: 978-3-642-31500-8
eBook Packages: Computer ScienceComputer Science (R0)