EMEWS: Extreme-scale Model Exploration with Swift

As high-performance computing resources have become increasingly available, new modes of computational processing and experimentation have become possible. The Extreme-scale Model Exploration with Swift (EMEWS) framework enables the direct integration of multi-language model exploration (ME) algorithms while scaling dynamic computational experiments to very large numbers (millions) of models on all major HPC platforms. EMEWS has been designed for any "black box" application code, such as agent-based and microsimulation models or training of machine learning models, that require multiple runs as part of heuristic model explorations. One of the main goals of EMEWS is to democratize the use of large-scale computing resources by making them accessible to more researchers in many more science domains. EMEWS is built on the Swift/T parallel scripting language.

EMEWS Tutorial

The new EMEWS tutorial is the primary resource for using EMEWS. Note that it is currently a work in progress.

The previous EMEWS tutorial, which does not include EMEWS DB, can be found here.

EMEWS Resources

For additional EMEWS resources, see the resources page.

EMEWS Papers

For EMEWS papers, see the papers page.

EMEWS Support

For support, including EMEWS mailing list information, see the support page.