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Paper: Deterministic and Statistical Parameter Space Sampling: an Autonomous Driver for ScientificWorkflows
Volume: 376, Astronomical Data Analysis Software and Systems XVI
Page: 417
Authors: Hovest, W.; Stojceska, G.; Saverchenko, I.; Adorf, H.-M.; Ensslin, T.; Riller, Th.
Abstract: Scientific workflows are usually controlled by many parameters, and assigning near-optimal values to these is often critical for efficiently finding solutions to goal-oriented problems. Such problems are typically solved by running sophisticated simulation or data analysis workflows. We present a novel sampling framework which is integrated into the Process Coordinator (ProC) the general purpose scientific workflow engine originally developed for the Planck Surveyor satellite mission. The framework supports the exploration of high-dimensional parameter spaces for function representation, optimization, or integration purposes. Complemented by one of several pluggable sampling algorithms, a Sampler Control Element (SCE) drives the exploration process in multiple cycles. The whole sampling framework has been tested with different sampling algorithm plug-ins, and is ready for use in astrophysical research.
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