Embedded Systems Applications
The AAA research group (formerly (BIC) at K-State is involved in theoretical and applied research in machine learning, algorithm analysis, multiagent systems, game theory, multi-objective optimization, and soft computing techniques for prediction, structure discovery, and other applications in terrestrial and shipboard power systems, smart grid and computational genomics. The group has received external funding from the National Science Foundation, Department of Defense and the U.S. Department of Agriculture in the areas of gene network modeling, shipboard systems and power distribution systems.
Embedded Systems Group
The current research in High Performance Computing (HPC) in the Mike Wiegers Department of Electrical and Computer Engineering has explored the effects of cache memory and hardware accelerators on a computers performance. To measure performance, special programs called bench-marks are run on the computer and the time required to run the program is a measure of the systems performance. This research has primarily used a program that solves a realistic finite element model, and has been formalized as part of the Mantevo benchmarks. By implementing the computer system on an FPGA, the researchers at K-State ECE were able to compare the amount of time and electrical power required to complete the benchmarks. The current research has shown that although hardware accelerators and cache memories tend to improve performance, their cost both financially and in power consumption can outweigh these gains.
The embedded systems group is also playing an active role in the Biosensors Network Project sponsored by NASA.