Abstract
In various applications including atmospheric and ocean simulation programs, stencil computations occur on grids where sub-domains of the grid are regular (e.g., can be stored in an array) but boundaries between sub-domains connect in an irregular fashion. We call this class of grids semi-regular. Implementations of stencils on semi-regular grids often have grid-structure details tangled with the stencil computation code. This tangling of details requires programmers to have full knowledge of the current grid structure to make changes to the stencil computations and makes changing the grid structure extremely expensive. Existing libraries and tools [1-7] for stencil computations have not focused on this class of grid, focusing instead on purely regular or irregular grids. In this poster we introduce abstractions for the class of semi-regular grids and describe the GridLib library where we have implemented these abstractions. These abstractions enable a separation of grid, algorithm, and parallelization for semi-regular grids.
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
References
Colella, P., Graves, D.T., Keen, N.D., Ligocki, T.J., Martin, D.F., Mccorquodale, P.W., Modiano, D., Schwartz, P.O., Sternberg, T.D., Straalen, B.V.: Chombo Software Package for AMR Applications: Design Document. Technical report, Lawrence Berkeley National Laboratory (2009)
Kamil, S., Chan, C., Williams, S., Oliker, L., Shalf, J., Howison, M., Bethel, E.W.: A generalized framework for auto-tuning stencil computations. In: Proceedings of the Cray User Group Conference (2009)
Unat, D., Cai, X., Baden, S.B.: Mint: realizing cuda performance in 3d stencil methods with annotated c. In: Proceedings of the International Conference on Supercomputing, ICS 2011, pp. 214–224. ACM, New York (2011)
Christen, M., Schenk, O., Burkhart, H.: Automatic code generation and tuning for stencil kernels on modern shared memory architectures. Comput. Sci. 26, 205–210 (2011)
Maruyama, N., Nomura, T., Sato, K., Matsuoka, S.: Physis: an implicitly parallel programming model for stencil computations on large-scale gpu-accelerated supercomputers. In: Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2011, pp. 11:1–11:12. ACM, New York (2011)
Giles, M.B., Mudalige, G.R., Sharif, Z., Markall, G., Kelly, P.H.J.: Performance Analysis and Optimization of the OP2 Framework on Many-Core Architectures. The Computer Journal 55(2), 168–180 (2011)
DeVito, Z., Joubert, N., Palacios, F., Oakley, S., Medina, M., Barrientos, M., Elsen, E., Ham, F., Aiken, A., Duraisamy, K., Darve, E., Alonso, J., Hanrahan, P.: Liszt: a domain specific language for building portable mesh-based pde solvers. In: Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2011, pp. 9:1–9:12. ACM, New York (2011)
Smith, R.D., Kortas, S.: Curvilinear coordinates for global ocean models. Technical report, Los Alamos National Laboratory, LA-UR-95-1146 (1995)
Murray, R.J.: Explicit Generation of Orthogonal Grids for Ocean Models. Journal of Computational Physics 126(2), 251–273 (1996)
Tomita, H., Tsugawa, M., Satoh, M., Goto, K.: Shallow Water Model on a Modified Icosahedral Geodesic Grid by Using Spring Dynamics. Journal of Computational Physics 174(2), 579–613 (2001)
Sadourny, R.: Conservative Finite-Difference Approximations of the Primitive Equations on Quasi-Uniform Spherical Grids. Monthly Weather Review 100(2), 136–144 (1972)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Stone, A., Strout, M.M. (2013). Abstractions for Defining Semi-Regular Grids Orthogonally from Stencils. In: Kasahara, H., Kimura, K. (eds) Languages and Compilers for Parallel Computing. LCPC 2012. Lecture Notes in Computer Science, vol 7760. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37658-0_22
Download citation
DOI: https://doi.org/10.1007/978-3-642-37658-0_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-37657-3
Online ISBN: 978-3-642-37658-0
eBook Packages: Computer ScienceComputer Science (R0)