| Abstract: | The paper describes a parallel implementation of a grand challenge problem: global atmospheric modeling. The novel contributions of our work include (1) a detailed investigation of opportunities for parallelism in atmospheric global modeling based on spectral solution methods, (2) the experimental evaluation of overheads arising from load imbalances and data movement for alternative parallelization methods, and (3) the development of a parallel code that can be monitored and steered interactively based on output data visualizations and animations of program functionality or performance. Code parallelization takes advantage of the relative independence of computations at different levels in the earth's atmosphere, resulting in parallelism of up to 40 processors, each independently performing computations for different atmospheric levels and requiring few communications between different levels across model time steps. Next, additional parallelism is attained within each level by taking advantage of the natural parallelism offered by the spectral computations being performed (e.g. taking advantage of independently computable terms in equations). Performance measurements are performed on a 64-node KSR2 supercomputer. However, the parallel code has been ported to several shared memory parallel machines, including SGI multiprocessors, and has also been ported to distributed memory platforms like the IBM SP-2. |
