Peak Temperature Reduction by Physical Information Driven Behavioral Synthesis with Resource Usage Allocation

Abstract

High temperature adversely impacts on circuit's reliability, performance, and leakage power. During behavioral synthesis, both resource usage allocation and resource binding influence thermal profile. Current thermal-aware behavioral syntheses do not utilize location information of resources from floorplan and in addition only focus on binding, ignoring allocation. This paper proposes thermal-aware behavioral synthesis with resource usage allocation. Based on a hybrid metric of physical location information and temperature, we rebind operations and reallocate the number of resources under area constraint. Our approach effectively controls peak temperature and creates even power densities among resources of different types and within resources of the same type. Experimental results show an average of 8.6°C drop in peak temperature and 5.3% saving of total power consumption with little latency overhead.