Parallelizing a serial code: open–source module, EZ Parallel 1.0, and geophysics examples

Abstract

Abstract. Parallel computing can offer substantial speedup of numerical simulations in comparison to serial computing, as parallel computing uses many processors simultaneously rather than a single processor. However, it typically also requires substantial time and effort to convert a serial code into a parallel code. Here, a new module is developed to reduce the time and effort required to parallelize a serial code. The tested version of the module is written in the Fortran programming language,while the framework could also be extended to other languages (C++, Python, Julia, etc.). The Message Passing Interface is used to allow for either shared-memory or distributed-memory computer architectures. The software is designed for solving partial differential equations on a rectangular two-dimensional or three-dimensional domain, using finite difference, finite volume, pseudo-spectral, or other similar numerical methods. Examples are provided for two idealized models of atmospheric and oceanic fluid dynamics: the two-level quasi-geostrophic equations, and the stochastic heat equation as a model for turbulent advection–diffusion of either water vapor and clouds or sea surface height variability. In tests of the parallelized code, the strong scaling efficiency for the finite difference code is seen to be roughly 80 % to 90 %, which is achieved by adding roughly only 10 new lines to the serial code. Therefore, EZ Parallel provides great benefits with minimal additional effort.