CENG STUDENT SEMINAR SERIES

"FPGA-BASED DATA-MINING ARCHITECTURES"Zachary BakerElectrical Engineering-SystemsAbstract:Recent advances in storage and data sensing have revolutionized our technological capability for collecting and storing data. The Apriori algorithm is a popular correlation-based data-mining kernel. However, it is a computationally expensive algorithm and the running times can stretch up to days for large databases, as database sizes can extend to Gigabytes. Through the use of a new extension to the systolic array architecture, time required for processing can be significantly reduced. Our array architecture implementation on a Xilinx Virtex-II Pro 100 provides a performance improvement that can be orders of magnitude faster than the state-of-the-art software implementations. The system is easily scalable and introduces an efficient ``systolic injection'' method for intelligently reporting unpredictably generated mid-array results to a controller without any chance of collision or excessive stalling.Bio:Zachary K. Baker (zbaker@usc.edu) is a PhD Candidate studying architectures and algorithms for string matching, data mining, and network classification under Professor Viktor K. Prasanna.Host: Dr. Won Namgoong, Ext. 02246

Location: Hughes Aircraft Electrical Engineering Center (EEB) - -248

Audiences: Everyone Is Invited

Contact: Rosine Sarafian