Fine-grain dynamic energy tracking for system-on-chip
Abstract
In this paper, we model system-on-chip (SoC) con- sumption as a dynamic process that can be easily tracked over time through a set of power modes. The proposed method provides precise information on each block dissipation inside the system. Each generated mode defines a specific model that links power to block activity reported by a set of critical signals. The modeling approach is illustrated by real experiments. When ap- plied to memory blocks, the model showed 10% maximum error, considering power at very fine granularity (quasi-instantaneous power). For long simulations, average and maximum energy are estimated with an error of 5.3% and 4.8%, respectively. For a memory controller and a MAC unit, only one probe is used leading to a very limited area overhead.