Temperature and energy aware scheduling of heterogeneous processors

Modern computing requires faster and more powerful processing. Faster and more powerful processors have resulted in higher heat dissipation and power consumption. In this paper we present an offline algorithm called Temperature and Energy aware Dynamic Level Scheduling (TEDLS). It is able to schedule tasks in a heterogeneous environment with DVS enabled processors to minimize execution time, energy consumption and heat dissipation. We use a heat model to estimate the final temperature of a processor executing a task. This estimation of temperature is based on processor characteristics, which aids in choosing the cooler processors. Our simulation results have shown that the TEDLS algorithm not only results in processors having lower temperatures but also produces lower energy consumption as compared to the previous offline algorithms. The TEDLS algorithm also produces lower application execution time when the application size is small.