  A common workflow in science and engineering is to (i) setup and deploy large
experiments with tasks comprising an application and multiple parameter values;
(ii) generate intermediate results; (iii) analyze them; and (iv) reprioritize
the tasks. These steps are repeated until the desired goal is achieved, which
can be the evaluation/simulation of complex systems or model calibration. Due
to time and cost constraints, sweeping all possible parameter values of the
user application is not always feasible. Experimental Design techniques can
help users reorganize submission-execution-analysis workflows to bring a
solution in a more timely manner. This paper introduces a novel tool that
leverages users' feedback on analyzing intermediate results of parameter
sweeping experiments to advise them about their strategies on parameter
selections tied to their SLA constraints. We evaluated our tool with three
applications of distinct domains and search space shapes. Our main finding is
that users with submission-execution-analysis workflows can benefit from their
interaction with intermediate results and adapt themselves according to their
domain expertise and SLA constraints.
