Power Agnostic Technique for Efficient Temperature Estimation of Multicore Embedded Systems

Temperature plays an increasingly important role in the over-all performance and reliability of a computing system. Multi-andmany-core systems provide an opportunity tomanage the overall temperature profile by cleverly designing the application-to-core mapping and the associated scheduling policies. An uncontrolled temperature profile may lead to an unplanned performance loss, since the system activates protective mech-anisms such as voltage and/or frequency scaling to cool it-self. Similarly, deep thermal cycles with high frequency lead to severe deterioration in the overall reliability of the system. Design space exploration tools are often used to optimize bind-ing and scheduling choices based on a given set of constraints and objectives, thus motivating the need for fast and accu-rate temperature estimation techniques. We argue that the currently available techniques are not an ideal fit to design space exploration tools, and suggest a system level technique which is based on application fingerprinting. It does not need any information about the processor floorplan, the physical and thermal structure, or about power consumption. Instead, its temperature estimation is based on a set of application-specific calibration runs and associated temperature measure-ments using available built-in sensors. We show that a given application possesses a unique thermal signature on the sys-tem it executes on, which provides a computationally fast method to calculate accurate temperature traces. Extensive experimental studies show that our technique can estimate temperature on all cores of a system to within 5oC, and is three orders of magnitude faster than state of the art numer-ical simulators like Hotspot