Fundamentals of digital image processing
Fundamentals of digital image processing
Discrete-time signal processing
Discrete-time signal processing
Architectural power analysis: the dual bit type method
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Register-transfer level estimation techniques for switching activity and power consumption
Proceedings of the 1996 IEEE/ACM international conference on Computer-aided design
Gate-level current waveform simulation of CMOS integrated circuits
ISLPED '96 Proceedings of the 1996 international symposium on Low power electronics and design
Power macromodeling for high level power estimation
DAC '97 Proceedings of the 34th annual Design Automation Conference
Design and analysis of power distribution networks in PowerPC microprocessors
DAC '98 Proceedings of the 35th annual Design Automation Conference
Node sampling: a robust RTL power modeling approach
Proceedings of the 1998 IEEE/ACM international conference on Computer-aided design
Cycle-accurate macro-models for RT-level power analysis
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Energy-per-cycle estimation at RTL
ISLPED '99 Proceedings of the 1999 international symposium on Low power electronics and design
Frequency-domain supply current macro-model
ISLPED '01 Proceedings of the 2001 international symposium on Low power electronics and design
Statistical power supply dynamic noise prediction in hierarchical power grid and package networks
Integration, the VLSI Journal
Power supply noise aware workload assignment for multi-core systems
Proceedings of the 2008 IEEE/ACM International Conference on Computer-Aided Design
A study of tapered 3-D TSVs for power and thermal integrity
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
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We present a frequency domain current macro-modeling technique for capturing the dependence of the block current waveform on its input vectors. The macro-model is based on estimating the Discrete Cosine Transform (DCT) of the current waveform as a function of input vector pair and then taking the inverse transform to estimate the time domain current waveform. The input vector pairs are partitioned according to Hamming distance and a current macro-model is built for each Hamming distance using regression. Regression is done on a set of current waveforms generated for each circuit, using HSPICE. The average relative error in peak current estimation using the current macro-model is less than 20%.