Representation of Evolutionary Algorithms in FPGA Cluster for Large-Scale Network Project

Abstract

Many problems in world are related to network projects, such as electric distribution project, highways systems, telecommunication networks, and others. Most of them can be represented by graphs, which manipulates thousands, or millions of nodes (input variables), becoming almost an impossible task to obtain solutions in real-time. Those cenarios are classified as Network Projects Problems (NPP), which involves combinatory problems whose goal is to find the most suitable graph network (reduced cost, time, route). The solution to these problems are, in general, computationally complex. However, Evolutionary Algorithms (EA) have been widely investigated. Many researches shows that the performance related to EAs for NPPs can be substantially raised by using a more appropriated representation. The objective of this project is to expand an implementation made on FPGA (Field-Programmable Gate Array), using a representation called Node-Depth (NDR) to resolve problems that are composed by more than 100 thousand nodes. The implementation will be realized on a platform composed by a Cluster of FPGA.