Estimating a power utilization of a computer system
View Patent ↗One embodiment of the present invention provides a system that estimates a power utilization of a computer system. During operation, a set of performance parameters of the computer system is monitored, wherein the computer system includes a processor. Then the power utilization of the computer system is estimated based on the set of performance parameters and a power-utilization model, wherein the power-utilization model was trained by measuring a power utilization of the computer system while the processor is operating at a first frequency and measuring a power utilization of the computer system while the processor is operating at a second frequency.
1. A method for estimating a power utilization of a computer system, comprising:
monitoring a set of performance parameters of the computer system, wherein the computer system includes a processor;
using a model training mechanism to generate a power-utilization model;
training the power-utilization model by:
while a processor in a computer system is operating at a first frequency, measuring a power utilization of the computer system while cycling a load on the processor from a first minimum load to a first maximum load;
while the processor is operating at a second frequency, measuring a power utilization of the computer system while cycling a load on the processor from a second minimum load to a second maximum load; and
generating the power-utilization model using at least one of a nonlinear, nonparametric regression technique or a pattern-recognition technique; and
estimating the power utilization of the computer system based on the set of performance parameters and the power-utilization model.
2. The method of claim 1 ,
wherein monitoring the set of performance parameters of the computer system includes systematically monitoring and recording a set of performance parameters of the computer system; and
wherein the recording process keeps track of the temporal relationships between events in different performance parameters.
3. The method of claim 1 , wherein the first frequency is a minimum frequency of operation of the processor and the second frequency is a maximum frequency of operation of the processor.
4. The method of claim 1 , wherein estimating the power utilization of the computer system based on the set of performance parameters and the power-utilization model includes using a pattern-recognition technique.
5. The method of claim 1 , wherein estimating the power utilization of the computer system based on the set of performance parameters and the power-utilization model includes using a nonlinear, nonparametric regression technique.
6. The method of claim 5 , wherein estimating the power utilization of the computer system based on the set of performance parameters and the power-utilization model includes using a multivariate state estimation technique.
7. The method of claim 1 , wherein estimating the power utilization of the computer system based on the set of performance parameters and the power-utilization model includes processing the set of performance parameters using an analytical re-sampling technique.
8. The method of claim 1 , wherein the computer system includes a dynamic power-management feature.
9. The method of claim 8 , wherein the dynamic power-management feature includes a feature controlling an operating voltage of the processor.
10. The method of claim 8 , wherein the dynamic power-management feature includes a feature controlling an operating frequency of the processor.
11. The method of claim 1 , wherein training the power-utilization model includes using a multivariate state estimation technique.
12. A non-transitory computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for estimating a power utilization of a computer system, the method comprising:
monitoring a set of performance parameters of the computer system, wherein the computer system includes a processor;
training the power-utilization model by:
while a processor in a computer system is operating at a first frequency, measuring a power utilization of the computer system while cycling a load on the processor from a first minimum load to a first maximum load; and
while the processor is operating at a second frequency, measuring a power utilization of the computer system while cycling a load on the processor from a second minimum load to a second maximum load; and
generating the power-utilization model using at least one of a nonlinear, nonparametric regression technique or a pattern-recognition technique; and
estimating the power utilization of the computer system based on the set of performance parameters and the power-utilization model.
13. The computer-readable storage medium of claim 12 ,
wherein monitoring the set of performance parameters of the computer system includes systematically monitoring and recording a set of performance parameters of the computer system; and
wherein the recording process keeps track of the temporal relationships between events in different performance parameters.
14. The computer-readable storage medium of claim 12 , wherein the first frequency is a minimum frequency of operation of the processor and the second frequency is a maximum frequency of operation of the processor.
15. The computer-readable storage medium of claim 12 , wherein estimating the power utilization of the computer system based on the set of performance parameters and the power-utilization model includes using a pattern-recognition technique.
16. The computer-readable storage medium of claim 12 , wherein estimating the power utilization of the computer system based on the set of performance parameters and the power-utilization model includes using a nonlinear, nonparametric regression technique.
17. The computer-readable storage medium of claim 16 , wherein estimating the power utilization of the computer system based on the set of performance parameters and the power-utilization model includes using a multivariate state estimation technique.
18. The computer-readable storage medium of claim 12 , wherein estimating the power utilization of the computer system based on the set of performance parameters and the power-utilization model includes processing the set of performance parameters using an analytical re-sampling technique.
19. The computer-readable storage medium of claim 12 , wherein the computer system includes a dynamic power-management feature.
20. The computer-readable storage medium of claim 19 , wherein the dynamic power-management feature includes a feature controlling an operating voltage of the processor.
21. The computer-readable storage medium of claim 19 , wherein the dynamic power-management feature includes a feature controlling an operating frequency of the processor.
22. The computer-readable storage medium of claim 12 , wherein training the power-utilization model includes using a multivariate state estimation technique.
23. An apparatus for estimating a power utilization of a computer system, comprising:
a monitoring mechanism configured to monitor a set of performance parameters of the computer system, wherein the computer system includes a processor;
a model-training mechanism configured to train a power-utilization model by:
while a processor in a computer system is operating at a first frequency, measuring a power utilization of the computer system while cycling a load on the processor from a first minimum load to a first maximum load;
while the processor is operating at a second frequency, measuring a power utilization of the computer system while cycling a load on the processor from a second minimum load to a second maximum load; and
generating the power-utilization model using at least one of a nonlinear, nonparametric regression technique or a pattern-recognition technique; and
an estimating mechanism configured to estimate the power utilization of the computer system based on the set of performance parameters and the power-utilization model.
24. The apparatus of claim 23 , wherein the computer system includes a dynamic power-management feature.