MIL - The University of Tennessee
the university of tennessee machine intelligence lab
 

Hardware Acceleration Platforms for Power Systems Analysis

Background and Motivation

Power grid analysis, spanning both state (load flow) estimation and contingency analysis, is a computationally heavy process. One mainstream approach to accelerate this process is by use of supercomputing platforms. Although the latter offer substantial speed up gain when compared to desktop workstations, the price/performance ratio is somewhat high. An alternative approach, taken by our research group, is to employ Field Programmable Gate Array (FPGA) devices as custom-logic based acceleration platforms.
 

Research Approach

Our research focuses on distributed hardware architectures that exploit parallelism and concurrency to achieve substantial computation speed up gains in a cost-efficient FPGA-based framework. We utilize a hybrid software/hardware setting to optimize flexible user interface together with a highly efficient acceleration engine, to yield pragmatic solutions.