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International Journal of Reconfigurable Computing
Volume 2010 (2010), Article ID 980762, 20 pages
http://dx.doi.org/10.1155/2010/980762
Research Article

New Three-Level Resource Management Enhancing Quality of Offline Hardware Task Placement on FPGA

1University of Nice Sophia-Antipolis/LEAT-CNRS, 250 rue Albert Einstein, bât 4. 06560, Sophia Antipolis - Cedex, France
2Research Unit ReDCAD, National Engineering School of Sfax, B.P. 1173-3038 Sfax, Tunisia

Received 14 November 2009; Revised 6 March 2010; Accepted 24 April 2010

Academic Editor: Christophe Bobda

Copyright © 2010 Ikbel Belaid et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Currently, reconfigurable hardware devices feature a high density of heterogeneous resources to enable multitasking and offer flexibility in application needs. These concepts raise the need for efficient management of hardware tasks and hardware resources. The scheduling of hardware tasks is highly dependent on placement. Placement focuses on allocation of hardware resources required by the scheduled hardware tasks. In this paper, we propose novel three-level resource management that investigates enhancement of placement quality by reducing task rejection, configuration overheads, and by optimizing resource utilization. Improving placement quality will produce significant enhancement of performance for scheduling and overall execution time of the application in FPGA. Hence, the placement problem is formulated into a constrained optimization problem and resolved with powerful solvers using the Branch and Bound method. The obtained results of an application of heterogeneous hardware tasks show an average resource utilization of 36% of the available resources on the reconfigurable region and an overall overhead of 11% of total application running time, and we have eliminated the issue of task rejection. Compared to static implementation, the gain in resource utilization within the reconfigurable region achieves up to 43%.