Abstract: An energy based framework is disclosed that allows a software compiler or developer to make decisions between performance and energy consumption. In one aspect, a first program code (e.g., vector engine based computation) may alternatively be compiled into a second program code (e.g., register operations). Using measurements obtained from a processor for which the first and second program codes are being compiled, and the expected size of the data and a number of iterations, a comparison can be made between the expected energy consumption profile of the first program code and the equivalent second program code. Based on the comparison, a software developer or the compiler can choose the program code that minimizes energy consumption.

Abstract: Methods and apparatuses to perform calibration of imprecise sensors for power monitoring in a data-processing system are described. The system includes a load coupled to one or more sensors. An electronic load changes a first input signal through one or more sensors by a predetermined amount. A difference in an output signal from the one or more sensors in response to the changing is obtained. The output signal is measured and sampled. A distribution of samples of the output signal is determined. The estimated parameters of the distribution that most likely to explain actual data are determined. Next, a transfer function of the one or more sensors is determined based on the estimated parameters. The input signal through the load is accurately predicted using the transfer function of the one or more sensors to monitor the power usage by the load.

Abstract: Methods and apparatuses to perform calibration of imprecise sensors for power monitoring in a data-processing system are described. The system includes a load coupled to one or more sensors. An electronic load changes a first input signal through one or more sensors by a predetermined amount. A difference in an output signal from the one or more sensors in response to the changing is obtained. The output signal is measured and sampled. A distribution of samples of the output signal is determined. The estimated parameters of the distribution that most likely to explain actual data are determined. Next, a transfer function of the one or more sensors is determined based on the estimated parameters. The input signal through the load is accurately predicted using the transfer function of the one or more sensors to monitor the power usage by the load.

Abstract: Methods and apparatuses to perform calibration of imprecise sensors for power monitoring in a data-processing system are described. The system includes a load coupled to one or more sensors. An electronic load changes a first input signal through one or more sensors by a predetermined amount. A difference in an output signal from the one or more sensors in response to the changing is obtained. The output signal is measured and sampled. A distribution of samples of the output signal is determined. The estimated parameters of the distribution that most likely to explain actual data are determined. Next, a transfer function of the one or more sensors is determined based on the estimated parameters. The input signal through the load is accurately predicted using the transfer function of the one or more sensors to monitor the power usage by the load.

Abstract: Methods and apparatuses to perform calibration of imprecise sensors for power monitoring in a data-processing system are described. The system includes a load coupled to one or more sensors. An electronic load changes a first input signal through one or more sensors by a predetermined amount. A difference in an output signal from the one or more sensors in response to the changing is obtained. The output signal is measured and sampled. A distribution of samples of the output signal is determined. The estimated parameters of the distribution that most likely to explain actual data are determined. Next, a transfer function of the one or more sensors is determined based on the estimated parameters. The input signal through the load is accurately predicted using the transfer function of the one or more sensors to monitor the power usage by the load.