JlBox v1.0: A Julia based mixed-phase atmospheric chemistry box-model

As our knowledge and understanding of atmospheric aerosol particle evolution and impact grows, designing community mechanistic models requires an ability to capture increasing chemical, physical and therefore numerical complexity. As the landscape of computing software and hardware evolves, it is important to profile the usefulness of emerging platforms in tackling this complexity. Julia is a relatively new programming language that promises computational performance close to that of Fortran, for example, without sacrificing flexibility offered by languages such as Python. With this in mind, in this paper we present and demonstrate the initial development of a high-performance community mixed phase atmospheric 0D box-model, JlBox, written in Julia. In JlBox v1.0 we provide the option to simulate the chemical kinetics of a gas phase whilst also providing a fully coupled gasparticle model with dynamic partitioning to a fully moving sectional size distribution, in the first instance. JlBox is built around chemical mechanism files, using existing informatics software to provide parameters required for mixed phase simulations. In this study we use mechanisms from a subset and the complete Master Chemical Mechanism (MCM). Exploiting the ability to perform automatic differentiation of Jacobian matrices within Julia, we profile the use of sparse linear solvers and preconditioners, whilst also using a range of stiff solvers included within the expanding ODE solver suite the Julia environment provides, including the development of an adjoint model. Case studies range from a single volatile organic compound [VOC] with 305 equations to a full complexity MCM mixed phase simulation with 47544 variables. Comparison with an existing mixed phase model shows significant improvements in performance and potential for developments in a number of areas.

Exploring Capabilities within ForTrilinos by Solving the 3D Burgers Equation

We present the first three-dimensional, partial differential equation solver to be built atop the recently released, open-source ForTrilinos package (http://trilinos.sandia.gov/packages/fortrilinos). ForTrilinos currently provides portable, object-oriented Fortran 2003 interfaces to the C++ packages Epetra, AztecOO and Pliris in the Trilinos library and framework [ACM Trans. Math. Softw.31(3) (2005), 397–423]. Epetra provides distributed matrix and vector storage and basic linear algebra calculations. Pliris provides direct solvers for dense linear systems. AztecOO provides iterative sparse linear solvers. We demonstrate how to build a parallel application that encapsulates the Message Passing Interface (MPI) without requiring the user to make direct calls to MPI except for startup and shutdown. The presented example demonstrates the level of effort required to set up a high-order, finite-difference solution on a Cartesian grid. The example employs an abstract data type (ADT) calculus [Sci. Program.16(4) (2008), 329–339] that empowers programmers to write serial code that lower-level abstractions resolve into distributed-memory, parallel implementations. The ADT calculus uses compilable Fortran constructs that resemble the mathematical formulation of the partial differential equation of interest.