On the parallelization of a global climate-chemistry modeling system

Coupled climate-chemistry simulations are computationally intensive owing to the spatial and temporal scope of the problem. In global chemistry models, the time integrations encountered in the chemistry and aerosol modules usually comprise the major CPU consumption. Parallelization of these segments of the code can contribute to multifold CPU speed-ups with minimal modification of the original serial code. This technical note presents a single program-multiple data (SPMD) strategy applied to the time-split chemistry modules of a coupled climate – global tropospheric chemistry model. Latitudinal domain decomposition is adopted along with a dynamic load-balancing technique that uses the previous time-step’s load/latitude estimates for distributing the latitude bands amongst the processors. The coupled model is manually parallelized using the Message Passing Interface standard (MPI) on a distributed memory platform (IBM-SP2). Load-balancing efficiencies and the associated MPI overheads are discussed. Overall speed-ups and efficiencies are also calculated for a series of runs employing up to eight processors.