| Name | Description | Keywords | Funding Agency | Award Number |
|---|---|---|---|---|
| SPEX: SParse EXact linear algebra and optimization solvers | The primary goal of this project is to design, create, and deploy computational tools to solve large-scale, sparse systems of linear equations and optimization problems without any error at all. Because of the ubiquity of solving systems of linear equations and optimization problems, the outcomes of this project will directly translate in software that is more reliable for applications across academia, industry, and government. | Optimization problem, Algorithms as Software - solve large-scale, sparse LPs | NSF | 1835499 |
| MetPy | This project advances MetPy to address some current limitations in supported data formats, scalability, and run-time performance; it makes MetPy more suitable for working on much larger datasets, frequently encountered in climate science and ensemble-based modeling studies. | software package: enhancement of MetPy package | NSF | 2103682 |
| SAGE3 | SAGE3 - the Smart Amplified Group Environment is software to enable collaborators to come to decisions with greater speed, accuracy, confidence and comprehensiveness by working in front of large display walls and/or remotely on laptops, to interpret large amounts of information in the form of visualizations and documents, with the assistance of Artificial Intelligence, | collaboration tiled display visualization decision support decision theater | NSF | 2004014 , 2003800, 2003387 |
| Foundry | Foundry is a Python package that simplifies the discovery and usage of machine-learning ready datasets in materials science and chemistry. Foundry provides software tools that make it easy to load these datasets and work with them in local or cloud environments. Further, Foundry provides a dataset specification, and defined curation flows, that allow users to create new datasets for the community to use through this same interface. | materials data, FAIR, datasets, models, machine learning | NSF | 1931306 |
| GMTSAR | GMTSAR is an open source InSAR processing system for generating wide-area mapping of the deformation of the surface of the Earth using repeated synthetic aperture radar (SAR) images collected by spacecraft ( https://topex.ucsd.edu/gmtsar/ ). The major deformation signals of interest are associated with earthquakes, volcanoes, glacier flow, and subsidence due to withdrawal of crustal fluids (e.g., water and hydrocarbons). The major goals of the GMTSAR project are to: 1) improve the software distribution with a wider range of package managers as well as the deployment of virtual machines ready for cloud computing; 2) harden the code through more robust batch/production algorithms combined with regular end-to-end testing; 3) develop tools to improve geodetic accuracy (e.g., split-spectrum ionosphere correction, solid earth tide corrections, resolution of integer phase ambiguity); 4) provide education in the theory and application of InSAR technology through UNAVCO short courses and refined documentation; and 5) move the software development from the aging team of original science developers to an engaged pool of younger research/production programmers. | Data Processing,Software Tool:GMTSAR | NSF | 1834807 |