Current Funded Projects

DOE,NNSA: Center for Compressible Multiphase Turbulence

The intellectual objectives of the proposed work are threefold: 1) To radically advance the field of compressible multiphase turbulence (CMT) through rigorous physics-based understanding; 2) To advance very large-scale predictive simulation science on present and near-future platforms; and 3) To advance a co-design strategy that combines exascale emulation with a novel energy-efficient numerical approach. The center will perform petascale, and work towards exascale simulations of instabilities, turbulence and mixing in particulate-laden flows under conditions of extreme pressure and temperature

AFOSR: Energy Aware Time Change Detection using Synthetic Aperture Radar on High-Performance Heterogeneous Architectures: A DDDAS Approach

Detecting areas of change in multiple snapshot images of a ground area is important in a variety of surveillance applications used by the Air Force and Department of Defense. For many such applications, images are constructed using Synthetic Aperture Radar (SAR). SAR collects information about a scene by repeatedly collecting the response from pulses transmitted toward an area of interest. A The focus of this proposal is to develop novel sequential and parallel algorithms for change detection using SAR that utilize modern architectures and minimize energy. This will enable real time change detection on an airborne device.

NSF: SparseKaffe: high-performance, auto-tuned energy-aware algorithms for sparse direct methods on modern heterogeneous architectures

The use of sparse direct methods in computational science is ubiquitous. Direct methods can be used to find solutions to many numerical algebra applications, including sparse linear systems, sparse linear least squares, and eigenvalue problems; consequently they form the backbone of a broad spectrum of large scale applications. The SparseKaffe project team will develop algorithms and software for high-performance parallel sparse direct methods with irregular and hierarchical structure that can exploit clusters of Hybrid Multicore Processors to achieve orders of magnitude gains in computational performance, while also paying careful attention to the energy requirements. This requires the development of novel and innovative algorithms for scheduling, energy minimization, and memory management; development of novel user-guided autotuning algorithms that exploit different hardware characteristics; and designing a common infrastructure for creating auto-tuned software.

NSF: Traffic Signal Control with Connected and Autonomous Vehicles in the Traffic Stream

This project will develop signalized intersection control strategies and other enabling sensor mechanisms for jointly optimizing vehicle trajectories and signal control by taking advantage of existing advanced technologies (connected vehicles and vehicle to infrastructure communications, sensors, autonomous vehicle technologies, etc.) Traffic signal control is a critical component of the existing transportation infrastructure and it has a significant impact on transportation system efficiency, as well as energy consumption and environmental impacts. 

  State of Texas: Texas External Quality Review Organization

This project will model and analyze health care data that to use data analytics to determine beneficiaries with complex needs and high costs (BCN). This population is more generally known as “super-utilizers”.

  Institute of Aging (Claude Pepper Center) at University of Florida: Data Science Core

This project conducts data driven research on “mobility and prevention of disability.” The approach uses content knowledge of age-related mobility phenotypes.  One novel aspect of our work was the development of novel algorithms for monitoring and processing information on mobile (smart-watch) devices for which battery life is an important objective. 

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