DYNAMO Content - Review and edit to improve the web content

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Short Title: DYNAMO: DYnamic Analysis and MOdeling

Project: [Dynamo: AI approaches to dynamic analysis, modeling, and information management for groundwater, rivers, and coasts]

Abstract: The DYNAMO allocation supports dynamic analysis and modeling workflows for physics-based systems with the goal of modernizing existing simulation tools and adding to the existing collection of models for the state of Texas. The DYNAMO compute allocations support testing and management of modeled information at scale for simulations data and tools. Modeling domains will include groundwater aquifers, fluvial and riverine surface water systems, and coastal systems. Additional domains of interest, such as subsidence and coastal spill conditions ,may be incorporated into DYNAMO applications and test cases.

As part of the DYNAMO effort, storage and applications are in development to support big data collections composed of modeled outputs and ancillary or complementary datasets. The DYNAMO data collections need to follow FAIR principles for findable, accessible, interoperable, and reusable tools and collections.

In addition to compute resources on Lonestar6 and Stampede3 on premise at TACC, the DYNAMO activities include the use of Microsoft Azure services for the AIM Flagship team of PT2050 . The Microsoft credits and funding have been pivotal for joint research applications with partners in the state of Texas. Over time we have developed a few approaches that leverage our on premise HPC systems with Azure. The resources complement each other and have helped us expand partnerships and research projects.

The additional credits will help us continue supporting the Water Science Program at the Texas Water Development Board (TWDB). Project DYNAMO is a joint effort between PT2050 researchers and TWDB water science to scale physics-based modeling capabilities in Texas. The agency has been running flood simulation tests on the existing Azure credits resulting in a 20 - 50% speed up in model run times. Importantly, the services are highly valued because teams can share large models (>120GB) for peer review more easily. Before using Azure teams were mailing hard drives across the state and between organizations. Azure has been key to the success of tests to date and with the latest gift credits we will continue providing access to our testbed Kubernetes on the cloud services to the agency.

[mepearson]

TASK: Review / update text of dynamo page for web purposes