Reliable Implementation on SRAM-based FPGA using Evolutionary Methods

Abstract

The mitigation of Single Event Upset (SEU), in the implemented circuits on SRAM-based FPGAs is a crucial issue with increasing usage of such chips in aerospace applications. In this paper, three evolutionary methods have been developed to reduce Soft Error Rate (SER) of such circuits. The first two methods are based on Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), and the other one is a co-evolutionary method which improves the convergence rate and cost of the former methods. The efficiency of these methods has been shown by comparing SER of implemented circuits using these methods with Versatile Place and Route (VPR) counterparts. More than 35% in SER reduction has been achieved for some MCNC benchmark circuits.