Thermal-Aware Floorplanning for Partially-Reconfigurable FPGA-Based Systems

Abstract

Abstract-Field Programmable Gate Arrays (FPGAs) systems are being more and more frequent in high performance applications. Temperature affects both reliability and performance, therefore its optimization has become challenging for system designers. In this work we present a novel thermal aware floorplanner based on both Simulated Annealing (SA) and MixedInteger Linear Programming (MILP). The proposed method takes into account an accurate description of heterogeneous resources and partially reconfigurable constraints of recent FPGAs. Our major contribution is to provide a high level formulation for the problem, without resorting to low level consideration about FPGAs resources. Within our approach we combine the benefits of SA and MILP to handle both linear and non-linear optimization metrics while providing an effective exploration of the solution space. Experimental results show that, for several designs, it is possible to reduce the peak temperature by taking into account power consumption during the floorplanning stage.