This new paper utilizes a workflow management system (WMS) to couple Elmer/Ice to HiDEM in order to enable a high resolution, physically accurate representation of calving. Scientific computing applications involving complex simulations and data-intensive processing are often composed of multiple tasks forming a workflow of computing jobs. Scientific communities running such applications on computing resources often find it cumbersome to manage and monitor the execution of these tasks and their associated data. These workflow implementations usually add overhead by introducing unnecessary input/output (I/O) for coupling the models and can lead to sub-optimal CPU utilization. Furthermore, running these workflow implementations in different environments requires significant adaptation efforts, which can hinder the reproducibility of the underlying science. High-level scientific WMS can be used to automate and simplify complex task structures by providing tooling for the composition and execution of workflows – even across distributed and heterogeneous computing environments. The WMS approach allows users to focus on the underlying high-level workflow and avoid low-level pitfalls that would lead to non-optimal resource usage while still allowing the workflow to remain portable between different computing environments. As a case study, we apply the UNICORE workflow management system to enable the coupling of a glacier flow model and calving model which contain many tasks and dependencies, ranging from pre-processing and data management to repetitive executions in heterogeneous high-performance computing (HPC) resource environments. Using the UNICORE workflow management system, the composition, management, and execution of the glacier modelling workflow becomes easier with respect to usage, monitoring, maintenance, reusability, portability, and reproducibility in different environments and by different user groups. Last but not least, the workflow helps to speed the runs up by reducing model coupling I/O overhead and it optimizes CPU utilization by avoiding idle CPU cores and running the models in a distributed way on the HPC cluster that best fits the characteristics of each model.
Read more: Memon S., D. Vallot, T. Zwinger, J. Åström, H. Neukirchen, M. Riedel and M. Book, 2019. Scientific workflows applied to the coupling of a continuum (Elmer v8.3) and a discrete element (HiDEM v1.0) ice dynamic model, Geosci. Model Dev., 12, 3001-3015 DOI: 10.5194/gmd-12-3001-2019