Title :
FPGA-Based Reconfigurable Hardware for Compute Intensive Data Mining Applications
Author :
Perera, Darshika G. ; Li, Kin Fun
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Victoria, Victoria, BC, Canada
Abstract :
Advances in distributed system technology have enabled new computation paradigms such as Grid, Cloud, and Internet computing. Due to the logical and physical organization of these paradigms, portable and embedded computing devices are being developed and naturally becoming an integral part of these systems. In addition to stringent area and power requirements, design constraints such as time-to-market and competitive margin pose serious challenges to embedded hardware designers. One of the most promising avenues to overcome these challenges is reconfigurable hardware. In this work, FPGA-based reconfigurable hardware is examined. As a case study, Principal Component Analysis (PCA), the classical technique to reduce the dimensionality of data and to extract dominant features, is designed and implemented as hardware on FPGA to be reconfigured dynamically during execution. Using part of a handwriting analysis application together with a benchmark dataset, experiments are performed to evaluate the feasibility, efficiency, and flexibility of reconfigurable hardware.
Keywords :
data mining; distributed processing; embedded systems; feature extraction; field programmable gate arrays; handwriting recognition; principal component analysis; reconfigurable architectures; FPGA-based reconfigurable hardware; PCA; benchmark dataset; compute intensive data mining application; data dimensionality reduction; design constraints; distributed system technology; dominant feature extraction; embedded computing devices; embedded hardware designer; handwriting analysis application; logical organization; physical organization; portable computing devices; principal component analysis; Covariance matrix; Data mining; Field programmable gate arrays; Hardware; Nonvolatile memory; Principal component analysis; Program processors; data mining; dynamic reconfiguration; hardware algorithm; principal component analysis; reconfigurable hardware;
Conference_Titel :
P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC), 2011 International Conference on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4577-1448-1
DOI :
10.1109/3PGCIC.2011.25