Abstract
Abstract. 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 workflow management systems (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.
Highlights
The complexity of glaciological systems is increasingly reflected by the physical models used to describe the processes acting on different temporal and spatial scales
Considering this requirement, the glacier model coupling case study is automated via our standards-based workflow management system (Memon et al, 2007), which is a part of the Uniform Interface to Computing Resources (UNICORE) (Streit et al, 2010) distributed computing middleware
A shared variable is required that contains the workflow output location that is to be used across all of the tasks. This is the only variable meant to be changed for a different user: if another user wants to run the same workflow on the same set of resources, e.g. the same high-performance computing (HPC) cluster, this single value has to be adjusted to the preferred file storage location
Summary
The complexity of glaciological systems is increasingly reflected by the physical models used to describe the processes acting on different temporal and spatial scales. The main contribution of this article is to identify the workflow problems that need to be solved with respect to coupling a glacier continuum model and a discrete element model in an optimized way, in order to elicit corresponding requirements that address – among others – portability, performance improvements, and CPU utilization, and to implement an automated workflow based on the UNICORE (Streit et al, 2010) distributed computing middleware, in particular using the UNICORE workflow management system (Memon et al, 2007) We demonstrate this by combining ice flow modelling and discrete calving into a high-level easy-to-use and performance-optimized scientific workflow.
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