Response Surface Methodology: Process and Product in Optimization Using Designed Experiments
Response Surface Methodology: Process and Product in Optimization Using Designed Experiments
Temperature-aware microarchitecture
Proceedings of the 30th annual international symposium on Computer architecture
Dynamic Thermal Management for High-Performance Microprocessors
HPCA '01 Proceedings of the 7th International Symposium on High-Performance Computer Architecture
Compact thermal modeling for temperature-aware design
Proceedings of the 41st annual Design Automation Conference
The need for a full-chip and package thermal model for thermally optimized IC designs
ISLPED '05 Proceedings of the 2005 international symposium on Low power electronics and design
ICCAD '05 Proceedings of the 2005 IEEE/ACM International conference on Computer-aided design
A systematic method for functional unit power estimation in microprocessors
Proceedings of the 43rd annual Design Automation Conference
Architecture-level thermal behavioral characterization for multi-core microprocessors
Proceedings of the 2008 Asia and South Pacific Design Automation Conference
Parameterized transient thermal behavioral modeling for chip multiprocessors
Proceedings of the 2008 IEEE/ACM International Conference on Computer-Aided Design
Electronic Circuit & System Simulation Methods (SRE)
Electronic Circuit & System Simulation Methods (SRE)
Architecture-level thermal characterization for multicore microprocessors
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Compact thermal modeling for packaged microprocessor design with practical power maps
Integration, the VLSI Journal
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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.