Optimized FPGA Routing using Soft Computing

FPGAs are used for a wide range of applications, e.g. network communication, video communication and processing and cryptographic applications. It has been shown that FPGAs are suitable for the implementation of soft computing techniques like Neural Networks and Genetic Algorithms. In this work we have shown that Ant Colony Optimizations can also be implemented on FPGAs, leading to significant speedups in runtime compared to implementations in software on sequential machines. This paper presents an ant colony optimization algorithm for geometric FPGA routing for a route based routing constraint model in FPGA design architecture.