| Name | Description | Keywords | Funding Agency | Award Number |
|---|---|---|---|---|
| SVD_Software_Package | This project proposes to develop a software package that unifies randomized and iterative methods with a particular focus on the specific requirements of various ML applications and with high performance optimizations for modern computing platforms. This will allow scientists to analyze significantly larger datasets, ML researchers to study large models that could not be tackled before, and ML service providers to use the new solvers to reduce their operational cost. | HPC, ML, Software Package: A high performance suite of SVD related solvers for machine learning | NSF | 1835821 |
| BLIS | BLIS is a portable software framework for instantiating high-performance BLAS-like dense linear algebra libraries. The framework was designed to isolate essential kernels of computation that, when optimized, immediately enable optimized implementations of most of its commonly used and computationally intensive operations. BLIS is written in ISO C99 and available under a new/modified/3-clause BSD license. While BLIS exports a new BLAS-like API, it also includes a BLAS compatibility layer which gives application developers access to BLIS implementations via traditional BLAS routine calls. An object-based API unique to BLIS is also available. | HPC, ML, BLAS, software framework | NSF | 2003931, 2003921 |
| P3DFFT++ | P3DFFT++ is an open source library, providing solution for an important class of problems in computational science, namely the multidimensional Fast Fourier transforms (FFTs). This library is designed to be portable, easy to use and scalable on large HPC platforms. | HPC, Supercomputers, Software for Multidimensional Fast Fourier transforms (FFTs), Fast Fourier Transforms (FFT) is a ubiquitous tool in scientific simulations, from Computational Fluid Dynamics to plasma physics, astrophysics, ocean modeling, materials research, medical imaging, molecular dynamics and many others | NSF | 1835885 |
| GeoSCIFramework | This project uses a collaboration between computer scientists and geoscientists to develop a data framework for generalized real-time streaming analytics and machine learning for geoscience and hazards research. It focuses on the aggregation and integration of a large number of data streams into a coherent system that supports analysis of the data streams in real-time. | Data Pipelines, ML, real-time streaming analytics, Geoscience and Hazards Research, Docker environment, local cluster, cloud, Data Framework - ML Based Tools | NSF | 1835661, 1835791, 1835692, 1835566 |
| InGeO | This award will support the development of the Integrated Geoscience Observatory (InGeO). InGeO is an online platform that integrates data and associated software tools contributed by researchers into a unified toolset to enable studying the convergent, systems science. | data linking, data processing,container,web based software tool:InGeo | NSF | 1835573 |