Keywords

Goal and description The scenario is that there is a need to perform a complex sweep over a non-trivial parameter space in a limited period of time as part of a series of in-silico experiments: an example might be testing compositions of and configurations of turbine blades through demanding duty cycles. To realize this, there is a need for an outer engine that performs the parameter sweep and an inner part that does data management[*] and which then runs some coupled simulations on the dataset, quite probably with additional stages as well to set up things like finite element meshes and stuff like that (we're interested in doing coupled CFD and FEM codes; turbine blade design is a good example.) There's a desire to keep the amount of work done down to keep turnaround time short, and there's also a desire to manage things in such a way that if a component fails[**], it remains possible to recover and still complete the overall workflow goals. We specifically want to be able to support a workflow system that can manage multiple ways of achieving the overall goal or a subgoal; I for one want to run a test where I pull the plug on one of the servers in use (i.e. a total catastrophic failure!) and have the customer's overall SLA still met.

* Our specific scenarios have the data moved to the computation for security and legal reasons.

** There are a _lot_ of failure modes! Many of them are recoverable with the right sort of workflow manager, but maybe not all.

Actors/stakeholders

Assumptions

Preconditions

Main flow of events (Basic, alternate, exceptional)

Postconditions

Success requirements

Special Requirements

Issues

Sources/references

OGF sponsor/stakeholder/interested party