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
A systematic method for functional unit power estimation in microprocessors
Proceedings of the 43rd annual Design Automation Conference
Advanced Model Order Reduction Techniques in VLSI Design
Advanced Model Order Reduction Techniques in VLSI Design
PRIMA: passive reduced-order interconnect macromodeling algorithm
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Parameterized transient thermal behavioral modeling for chip multiprocessors
Proceedings of the 2008 IEEE/ACM International Conference on Computer-Aided Design
Parameterized architecture-level dynamic thermal models for multicore microprocessors
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Architecture-level thermal characterization for multicore microprocessors
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
General behavioral thermal modeling and characterization for multi-core microprocessor design
Proceedings of the Conference on Design, Automation and Test in Europe
Power agnostic technique for efficient temperature estimation of multicore embedded systems
Proceedings of the 2012 international conference on Compilers, architectures and synthesis for embedded systems
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In this paper, we investigate a new architecture-level thermal characterization problem from behavioral modeling perspective to address the emerging thermal related analysis and optimization problems for high-performance multi-core microprocessor design. We propose a new approach, called ThermPOF, to build the thermal behavioral models from the measured architecture thermal and power information. ThermPOF first builds the behavioral thermal model using generalized pencil-of-function (GPOF) method. And then to effectively model transient temperature changes, we proposed two new schemes to improve the GPOF. First we apply logarithmic-scale sampling instead of traditional linear sampling to better capture the temperature changing characteristics. Second, we modify the extracted thermal impulse response such that the extracted poles from GPOF are guaranteed to be stable without accuracy loss. To further reduce the model size, Krylov subspace based model order reduction is performed to reduce the order of the models in the state-space form. Experimental results on a practical quad-core microprocessor show that generated thermal behavioral models match the measured data very well.