Parameterized architecture-level dynamic thermal models for multicore microprocessors

Abstract

In this article, we propose a new architecture-level parameterized dynamic thermal behavioral modeling algorithm for emerging thermal-related design and optimization problems for high-performance multicore microprocessor design. We propose a new approach, called ParThermPOF , to build the parameterized thermal performance models from the given accurate architecture thermal and power information. The new method can include a number of variable parameters such as the locations of thermal sensors in a heat sink, different components (heat sink, heat spreader, core, cache, etc.), thermal conductivity of heat sink materials, etc. The method consists of two steps: first, a response surface method based on low-order polynomials is applied to build the parameterized models at each time point for all the given sampling nodes in the parameter space. Second, an improved Generalized Pencil-Of-Function (GPOF) method is employed to build the transfer-function-based behavioral models for each time-varying coefficient of the polynomials generated in the first step. Experimental results on a practical quad-core microprocessor show that the generated parameterized thermal model matches the given data very well. The compact models by ParThermPOF offer two order of magnitudes speedup over the commercial thermal analysis tool FloTHERM on the given examples. ParThermPOF is very suitable for design space exploration and optimization where both time and system parameters need to be considered.