OBLIMAP ice sheet model coupler parallelization and optimization
A Use Case by
Short description
Within the ESiWACE2 project, we have parallelized and optimized OBLIMAP. OBLIMAP is a climate model - ice sheet model coupler that can be used for offline and online coupling with embeddable mapping routines. In order to anticipate future demand concerning higher resolution and/or adaptive mesh applications, a parallel implementation of OBLIMAP's fortran code with MPI has been developed. The data-intense nature of this mapping task required a shared memory approach across the processors per compute node in order to prevent the node memory from being the limiting bottleneck. Moreover, the current parallel implementation allows multi-node scaling and includes parallel NetCDF IO in addition to loop optimizations.
Results & Achievements
Results show that the new parallel implementation offers better performance and scales well. On a single node, the shared memory approach allows now to use all the available cores, up to 128 cores in our experiments of the Antarctica 20x20km test case where the original code was limited to 64 cores on this high-end node, and was even limited to 8 cores on moderate platforms. The multi-node parallelization yields for the Greenland 2x2km test case a speedup of 4.4 on 4 high-end compute nodes equipped with 128 cores each when compared to the original code, which was able to run only on 1 node. This paves the way to establishing OBLIMAP as a candidate ice sheet coupling library for large-scale, high-resolution climate modeling.
Objectives
The goal of the project is firstly to reduce the memory footprint of the code by improving its distribution over parallel tasks, and secondly to resolve the I/O bottleneck by implementing parallel reading and writing. This will improve the intra-node scaling of OBLIMAP-2.0 by using all the cores of a node. A second step will be the extension of the parallelization scheme to support inter-node execution. This work will establish OBLIMAP-2.0 as a candidate ice coupling library for large-scale, high-resolution climate models.
Collaborating Institutions
KNMI
Atos
