Self-healing Evolvable Hardware Architectures for Image Processing Applications

1. Self-healing Evolvable Hardware Architecturesfor Image Processing Applications J. Mora The proposed system implements a platform for evolvable hardware which takes advantage of the possibility of performing partial dynamic reconfiguration of hardware on a RAM-based FPGA. Online performance measurements and self-reconfiguration let the system recover from faults automatically. Median filter ARCHITECTURE FEATURES Median filter Project sponsored by Fitness • High processing speed • Autonomous • Adaptive • Fault tolerant, self-healing Generations Fitness (log) Number of filters Pre-synthed function library RESULTS CONTROL INTERFACE MICRO PROCESSOR Fitness JTAG Effect of cascading filters Ref Evol. algorithm COMPACT FLASH Result Reconfig control Image All functions are simple (add, subtract, max, double…) There are no complex functions such as multiplications RAM HARDWARE ICAP SYSTOLIC ARRAY FAULT TOLERANCE 3x3 Errors Evolution creates filters that avoid errors Errors CONCLUSIONS Up to 5700 evaluations per second (1 evaluation = mutation + reconfiguration + processing and fitness calculation) Different input conditions result in different, specialized filters System is still able to generate filters even after inserting errors