Efficient statistical approach to estimate power considering uncertain properties of primary inputs

Authors:
Zhanping Chen;Kaushik Roy;Tan-Li Chou
Affiliations:
School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN;School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN;Intel Corporation, Hillsboro, OR
Venue:
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Year:
1998

Citing 8
Cited 0

Transition density, a stochastic measure of activity in digital circuits

DAC '91 Proceedings of the 28th ACM/IEEE Design Automation Conference
Estimation of average switching activity in combinational and sequential circuits

DAC '92 Proceedings of the 29th ACM/IEEE Design Automation Conference
Switching activity analysis considering spatiotemporal correlations

ICCAD '94 Proceedings of the 1994 IEEE/ACM international conference on Computer-aided design
Estimation of circuit activity considering signal correlations and simultaneous switching

ICCAD '94 Proceedings of the 1994 IEEE/ACM international conference on Computer-aided design
A survey of power estimation techniques in VLSI circuits

IEEE Transactions on Very Large Scale Integration (VLSI) Systems - Special issue on low-power design
Statistical estimation of the switching activity in digital circuits

DAC '94 Proceedings of the 31st annual Design Automation Conference
Efficient power estimation for highly correlated input streams

DAC '95 Proceedings of the 32nd annual ACM/IEEE Design Automation Conference
Power sensitivity—a new method to estimate power dissipation considering uncertain specifications of primary inputs

ICCAD '97 Proceedings of the 1997 IEEE/ACM international conference on Computer-aided design

Quantified Score

Hi-index	0.00

Visualization

Abstract

Power dissipation in complementary metal-oxide-semiconductor (CMOS) circuits is heavily dependent on the signal properties of the primary inputs. Due to uncertainties in specification of such properties, the average power should be specified between a maximum and a minimum possible value. Due to the complex nature of the problem, it is practically impossible to use traditional power estimation techniques to determine such bounds. In this paper, we present a novel approach to accurately estimate the maximum and minimum bounds for average power using a technique which calculates the sensitivities of average power dissipation to uncertainties in specification of primary inputs. The sensitivities are calculated using a novel statistical technique and can be obtained as a by-product of average power estimation using Monte Carlo-based approaches. The signal properties are specified in terms of signal probability (probability of a signal being logic ONE) and signal activity (probability of signal switching). Results show that the maximum and minimum average power dissipation can vary widely if the primary input probabilities and activities are not specified accurately.