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.
|Title of host publication||2011 NASA/ESA Conference on Adaptive Hardware and Systems (AHS)|
|Publication status||Published - 2011|
|Event||2011 NASA/ESA Conference on Adaptive Hardware and Systems - San Diego, CA, United States|
Duration: 6 Jun 2011 → 9 Jun 2011
|Conference||2011 NASA/ESA Conference on Adaptive Hardware and Systems|
|City||San Diego, CA|
|Period||06/06/2011 → 09/06/2011|