A framework for predictive dynamic temperature management of microprocessor systems

The sustained push for performance, transistor count and instruction level parallelism has reached a point where IC thermal issues are at the forefront of design constraints. Many of the current systems deploy dynamic voltage and frequency scaling (DVFS) to address thermal emergencies. DVFS has certain limitations in terms of response lag, scalability and being reactive. On the other hand, several hardware based control theoretic schemes have been proposed to deliver optimal performance, but such schemes come at high cost and lack flexibility and scalability. In this paper, we present an alternative thermal monitoring and management system that utilizes software and hardware components, based on virtual machine concept. The proposed scheme delivers targeted, localized, and preemptive thermal management at low cost, adapts well to a multitasking environment, while delivering maximum performance under thermal stress.