Approximation algorithm for the temperature-aware scheduling problem

The paper addresses the problem of performance optimization for a set of periodic tasks with discrete voltage/frequency states under thermal constraints. We prove that the problem is NP-hard, and present a pseudo-polynomial optimal algorithm and a fully polynomial time approximation technique (FPTAS) for the problem. The FPTAS technique is able to generate solutions in polynomial time that are guaranteed to be within a designer specified quality bound (QB) (say within 1% of the optimal). We evaluate our techniques by experimentation with multimedia and synthetic benchmarks mapped on the 70 nm CMOS technology processor. The experimental results demonstrate our techniques are able to match optimal solutions when QB is set at 5%, can generate solutions that arc quite close to optimal (< 5%) even when QB is set at higher values (50%), and executes in few seconds (with QB > 25%) for large task sets with 120 nodes (while the optimal solution takes several hundred seconds). We also analyze the effect of different thermal parameters, such as the initial temperature, the final temperature and the thermal resistance.