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Application-aware optimization of redundant resources for the reconfigurable self-healing eDNA hardware architecture

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3 Author(s)
Boesen, M.R. ; DTU Inf., Tech. Univ. of Denmark, Lyngby, Denmark ; Madsen, J. ; Pop, P.

In this paper we are interested in the mapping of embedded applications on a dynamically reconfigurable self-healing hardware architecture known as the eDNA (electronic DNA) architecture. The architecture consists of an array of cells interconnected through a 2D-mesh topology. Each cell consists of a processor and an Arithmetic Logic Unit (ALU). Applications are modeled as task graphs. We propose a Tabu Search-based approach for the mapping of an application to the reconfigurable architecture, such that the performance is maximized. When faults occur, the self-healing moves the affected functionality to spare-cells. We optimize the number and placement of spare-cells such that the performance overhead is minimized in the fault-free scenario and the application degrades gracefully in case of faults. This has been done using three different spare-cell placement strategies. We use Monte Carlo simulation to determine the average performance overhead increase due to fault occurrences. The approach has been evaluated using a large number of benchmarks and have shown that the performance loss is reduced with 16% for the best spare-cell placement strategy.

Published in:

Adaptive Hardware and Systems (AHS), 2011 NASA/ESA Conference on

Date of Conference:

6-9 June 2011