Efficient power modeling and software thermal sensing for runtime temperature monitoring

The evolution of microprocessors has been hindered by increasing power consumption and heat dissipation on die. An excessive amount of heat creates reliability problems, reduces the lifetime of a processor, and elevates the cost of cooling and packaging considerably. It is therefore imperative to be able to monitor the temperature variations across the die in a timely and accurate manner. Most current techniques rely on on-chip thermal sensors to report the temperature of the processor. Unfortunately, significant variation in chip temperature both spatially and temporally exposes the limitation of the sensors. We present a compensating approach to tracking chip temperature through an OS resident software module that generates live power and thermal profiles of the processor. We developed such a software thermal sensor (STS) in a Linux system with a Pentium 4 Northwood core. We employed highly efficient numerical methods in our model to minimize the overhead of temperature calculation. We also developed an efficient algorithm for functional unit power modeling. Our power and thermal models are calibrated and validated against on-chip sensor readings, thermal images of the Northwood heat spreader, and the thermometer measurements on the package. The resulting STS offers detailed power and temperature breakdowns of each functional unit at runtime, enabling more efficient online power and thermal monitoring and management at a higher level, such as the operating system.