The finite-volume dynamical core on the cubed-sphere

As horizontal resolutions of global climate and numerical weather prediction applications increase beyond the hydrostatic limit of 10-km, the demand for efficient scalable applications becomes essential. Over the next decade global models will require scalability beyond hundreds of thousands to millions of processors. The current implementation of the finite-volume dynamical core (fvcore), a key component of global models at NASA, NOAA and NCAR, is limited in terms of scalability by the choice of computational grid (latitude-longitude based). To break through these scalability limitations the fvcore has been implemented on the quasi-uniform cubed-sphere grid with a 2-dimensional horizontal domain decomposition.The cubed-sphere fvcore scales well beyond the pure MPI limitations of the lat-lon core displaying ideal scaling on a full node of the SGI Altix (512 CPUs). This improved scalability will allow parent models to scale in excess of 10,000s of processors as we move toward petascale computing environments.

[1]  Akio Arakawa,et al.  Integration of the Nondivergent Barotropic Vorticity Equation with AN Icosahedral-Hexagonal Grid for the SPHERE1 , 1968 .

[2]  Anthony Skjellum,et al.  Using MPI - portable parallel programming with the message-parsing interface , 1994 .

[3]  A. Hollingsworth,et al.  An internal symmetric computational instability , 1983 .

[4]  Shian-Jiann Lin,et al.  A finite‐volume integration method for computing pressure gradient force in general vertical coordinates , 1997 .

[5]  Yong Li,et al.  Numerical simulations of Rossby–Haurwitz waves , 2000 .

[6]  A. Khamayseh,et al.  Computational Conformal Mapping for Surface Grid Generation , 1996 .

[7]  S. Klein,et al.  GFDL's CM2 Global Coupled Climate Models. Part I: Formulation and Simulation Characteristics , 2006 .

[8]  Robert B. Ross,et al.  Using MPI-2: Advanced Features of the Message Passing Interface , 2003, CLUSTER.

[9]  Todd D. Ringler,et al.  The ZM Grid: An Alternative to the Z Grid , 2002 .

[10]  Chris Hill,et al.  Implementation of an Atmosphere-Ocean General Circulation Model on the Expanded Spherical Cube , 2004 .

[11]  Ionel M. Navon,et al.  A comparative study of the performance of high resolution advection schemes in the context of data assimilation , 2006 .

[12]  Norman A. Phillips,et al.  NUMERICAL INTEGRATION OF THE PRIMITIVE EQUATIONS ON THE HEMISPHERE , 1959 .

[13]  Cecelia DeLuca,et al.  Design and Implementation of Components in the Earth System Modeling Framework , 2005, Int. J. High Perform. Comput. Appl..

[14]  Joe F. Thompson,et al.  Quasiconformal Mappings and Grid Generation , 1984 .

[15]  Stephen J. Thomas,et al.  A Discontinuous Galerkin Global Shallow Water Model , 2005, Monthly Weather Review.

[16]  David L. Williamson,et al.  Integration of the barotropic vorticity equation on a spherical geodesic grid , 1968 .

[17]  Q.F. Stout,et al.  Adaptive Blocks: A High Performance Data Structure , 1997, ACM/IEEE SC 1997 Conference (SC'97).

[18]  William Gropp,et al.  Parallel Scalability of the Spectral Transform Method , 1991, PPSC.

[19]  F. Mesinger,et al.  A global shallow‐water model using an expanded spherical cube: Gnomonic versus conformal coordinates , 1996 .

[20]  W. Gates.  AMIP: The Atmospheric Model Intercomparison Project. , 1992 .

[21]  Branislav Jaramaz,et al.  Nearly orthogonal two-dimensional grid generation with aspect ratio control , 2001 .

[22]  Hirofumi Tomita,et al.  Shallow water model on a modified icosahedral geodesic grid by using spring dynamics , 2001 .

[23]  Christiane Jablonowski,et al.  Adaptive grids in weather and climate modeling. , 2004 .

[24]  J. Hack,et al.  Spectral transform solutions to the shallow water test set , 1995 .

[25]  Robert Atlas,et al.  Global weather prediction and high-end computing at NASA , 2004, Computing in Science & Engineering.

[26]  M. Suárez,et al.  A proposal for the intercomparison of the dynamical cores of atmospheric general circulation models , 1994 .

[27]  C. Wayne Mastin,et al.  Surface grid generation based on elliptic PDE models , 1994 .

[28]  Arthur A. Mirin,et al.  A Scalable Implementation of a Finite-Volume Dynamical Core in the Community Atmosphere Model , 2005, Int. J. High Perform. Comput. Appl..

[29]  Todd D. Ringler,et al.  Modeling the Atmospheric General Circulation Using a Spherical Geodesic Grid: A New Class of Dynamical Cores , 2000 .

[30]  G.E. Moore,et al.  Cramming More Components Onto Integrated Circuits , 1998, Proceedings of the IEEE.

[31]  P. Swarztrauber,et al.  A standard test set for numerical approximations to the shallow water equations in spherical geometry , 1992 .

[32]  Philip J. Rasch,et al.  Characteristics of Atmospheric Transport Using Three Numerical Formulations for Atmospheric Dynamics in a Single GCM Framework , 2006 .

[33]  D. Williamson,et al.  A baroclinic instability test case for atmospheric model dynamical cores , 2006 .

[34]  R. J. Purser,et al.  Smooth quasi‐homogeneous gridding of the sphere , 1998 .

[35]  Thomas P. Minka,et al.  Gates , 2008, NIPS.

[36]  Achi Brandt,et al.  A global shallow‐water numerical model based on the semi‐lagrangian advection of potential vorticity , 1995 .

[37]  J. G. Charney,et al.  The Use of the Primitive Equations of Motion in Numerical Prediction , 1955 .