Power consumption reduction systems and methods

Information

  • Patent Grant
  • 8839006
  • Patent Number
    8,839,006
  • Date Filed
    Friday, May 28, 2010
    14 years ago
  • Date Issued
    Tuesday, September 16, 2014
    10 years ago
Abstract
Power management systems and methods that facilitate efficient and effective power conservation are presented. In one embodiment a power management method comprises: performing an initiation metric determination process, and adjusting operations of a logic component based on said threshold value. In one exemplary implementation, the initiation metric determination process includes monitoring activity of a logic component, and establishing a power conservation initiation threshold value. The initiation metric determination process can include performing a system architecture characteristic analysis in which a system architecture power-consumption break-even time (BE) is determined for the system. The initiation metric determination process can also include performing a system utilization analysis process is performed in which idle period durations detected during said monitoring are sorted into a variety of different length intervals and analyzed accordingly. Histograms of idle period durations can be collected. Adjusting operations can include entering a low power state.
Description
FIELD

Embodiments according to the present invention generally relate to power consumption management in electronic devices.


BACKGROUND

Electronic systems and circuits have made a significant contribution towards the advancement of modern society and are utilized in a number of applications to achieve advantageous results. Numerous electronic technologies such as digital computers, calculators, audio devices, video equipment, and telephone systems facilitate increased productivity and cost reduction in analyzing and communicating data, ideas and trends in most areas of business, science, education and entertainment. Frequently, these activities often involve processing devices consuming power. However, many modern mobile processing devices have limited power supplies, and utilization of ever increasingly sophisticated and complex applications is putting even greater demands on the limited power supplies.


Most conventional approaches to power management involve putting a device in a low or reduced power state. However, entering and exiting a low state typically consumes power, and since most processing activities can not be performed during low power states, power expended inappropriately entering and exiting a low power state is essentially wasted. In addition, the lag in application processing while a system enters and exists a low power state can impact responsiveness to application activities.


Conventional power conservation typically includes monitoring activity and transitioning the logic to the low power state (e.g., power gating) after detecting that the logic has been inactive for a period of time. However, traditional power management approaches usually involve a fixed pre-determined trigger for entering a power reduction state, and the fixed pre-determined triggers are typically set during product design and not adjustable. Typical modern portable devices attempt to apply relatively unsophisticated power saving techniques while running very diverse complex applications with widely varying operating characteristics, resulting in a higher probability of wasted power and reduced responsiveness during inappropriate low power state initiation.


SUMMARY

Power management systems and methods that facilitate efficient and effective power conservation are presented. In one embodiment a power management method comprises: performing an initiation metric determination process, and adjusting operations of a logic component based on said threshold value. In one exemplary implementation, the initiation metric determination process includes monitoring activity of a logic component, and establishing a power conservation initiation threshold value. The initiation metric determination process can include performing a system architecture characteristic analysis in which a system architecture power-consumption break-even time (BE) is determined for the system. The initiation metric determination process can also include performing a system utilization analysis process in which idle period durations detected during said monitoring are sorted into a variety of different length intervals and analyzed accordingly. Histograms of idle period durations can be collected. Adjusting operations can include entering a low power state.


These and other objects and advantages of the various embodiments of the present invention will be recognized by those of ordinary skill in the art after reading the following detailed description of the embodiments that are illustrated in the various drawing figures.





BRIEF DESCRIPTION OF THE DRAWINGS

The present invention is illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings and in which like reference numerals refer to similar elements. The drawings are not necessarily to scale.



FIG. 1 is a graph of exemplary power state transitions in accordance with one embodiment of the present invention.



FIG. 2 is flow chart of exemplary power management method in accordance with one embodiment of the present invention.



FIG. 3 is a flowchart of an exemplary power state metric or threshold determination process in accordance with one embodiment of the present invention.



FIG. 4A is a block diagram of a histogram in accordance with one embodiment of the present invention.



FIG. 4B is another block diagram of a histogram in accordance with one embodiment of the present invention.



FIG. 4C is a block diagram of another exemplary histogram with a different number of buckets in accordance with one embodiment of the present invention.



FIG. 4D is a block diagram of another exemplary histogram with different duration buckets in accordance with one embodiment of the present invention.



FIG. 5 is a block diagram of an example of a computer system upon which an intelligent power saving process can be implemented in accordance with the one embodiment of the present invention.



FIG. 6 is a block diagram showing the elements of an exemplary power management system in accordance with one embodiment of the present invention.



FIG. 7 is a block diagram showing an exemplary power management system within a portion of the computer system in accordance with one embodiment of the present invention.





DETAILED DESCRIPTION

Reference will now be made in detail to embodiments in accordance with the present invention, examples of which are illustrated in the accompanying drawings. While the invention will be described in conjunction with these embodiments, it will be understood that they are not intended to limit the invention to these embodiments. On the contrary, the invention is intended to cover alternatives, modifications and equivalents, which may be included within the spirit and scope of the invention as defined by the appended claims. Furthermore, in the following detailed description of embodiments of the present invention, numerous specific details are set forth in order to provide a thorough understanding of the present invention. However, it will be recognized by one of ordinary skill in the art that the present invention may be practiced without these specific details. In other instances, well-known methods, procedures, components, and circuits have not been described in detail as not to unnecessarily obscure aspects of the embodiments of the present invention.


Some portions of the detailed descriptions, which follow, are presented in terms of procedures, steps, logic blocks, processing, and other symbolic representations of operations on data bits within a computer memory. These descriptions and representations are the means used by those skilled in the data processing arts to most effectively convey the substance of their work to others skilled in the art. A procedure, computer-executed step, logic block, process, etc., is here, and generally, conceived to be a self-consistent sequence of steps or instructions leading to a desired result. The steps are those requiring physical manipulations of physical quantities. Usually, though not necessarily, these quantities take the form of electrical or magnetic signals capable of being stored, transferred, combined, compared, and otherwise manipulated in a computer system. It has proven convenient at times, principally for reasons of common usage, to refer to these signals as bits, values, elements, symbols, characters, terms, numbers, or the like.


It should be borne in mind, however, that all of these and similar terms are to be associated with the appropriate physical quantities and are merely convenient labels applied to these quantities. Unless specifically stated otherwise as apparent from the following discussions, it is appreciated that throughout the present invention, discussions utilizing terms such as “encoding,” “decoding,” “deblocking,” “receiving,” “sending,” “using,” “applying,” “calculating,” “incrementing,” “comparing,” “selecting,” “summing,” “weighting,” “computing,” “accessing” or the like, refer to the actions and processes of a computer system, or similar electronic computing device, that manipulates and transforms data represented as physical (electronic) quantities within the computer system's registers and memories into other data similarly represented as physical quantities within the computer system memories or registers or other such information storage, transmission or display devices.


Present systems and methods facilitate efficient and effective conservation of power resources. In one embodiment, parameters of when to enter a reduced power state are automatically adjusted. In one exemplary implementation, automatic adjustments are made based upon automated intelligent analysis of recent processing activities (e.g., post production, in the field, etc.). For example, an “idle detect” threshold time value can be automatically adjusted based upon flexible and intelligent analysis of processing activities associated with currently running applications.


A present system can enter various power states. In one exemplary embodiment, a system has a high power state and a low power state. In one exemplary implementation, during a high power state a relatively large number of the possible sub-components in a system are enabled and during a low power state a much smaller number of possible sub-components are enabled. It is appreciated that there can also be intermediate power states.



FIG. 1 is a graph of exemplary power state transitions in accordance with one embodiment of the present invention. The vertical axis represents power consumption and the horizontal axis represents time. The graph shows a system after initial power up and active application processing. The system is in a high power state with active application processing occurring during time frame Z1. Then at time A the active application processing stops and the system is in a high power state with inactive application processing during time frame X. At time B the system begins to “turn components off” during period Y1 to enter a low power state. Initially at time B more power is consumed in entering a low power state but shortly reaches a low power state. At time C “turning off” selected components is complete and the system enters a low power state during period P. At time D the system receives an indication that active application processing is attempting to begin again and the system begins to exit the low power state and turns on the selected components during period Y2. At time E the system enters another high power state with active application processing during period Z2.



FIG. 1 is explained in terms of a low power state in which active application processing is “stopped”. It is appreciated that some processing can continue in the system. In one embodiment, a reduced amount of application processing can continue during the low power state.


In one embodiment, the system consumes some power when entering the low power state (e.g., during period Y1), during the low power state (e.g., during period P) and during the exit of the low power state (e.g., during period Y2). It is also appreciated that once the system begins to enter the low power state at time B that the system is not able to perform full application processing until the system completes exiting the low power system at time E. Thus, it is desirable for the power saved by entering the low power state to be greater than the additional or extra power consumed during periods Y1 and Y2. With reference to FIG. 1, it is desirable to have the energy saved (e.g., represented by area 120) associated with entering the low power state be greater than energy expended (e.g., represented by areas 110 and 130). Inappropriate utilization of the low power states (e.g., expending more power entering and exiting the low power state than is saved being in the low power state, etc.) can waste power. The present systems and method facilitate adaptive efficient utilization of reduced or low power states.



FIG. 2 is a flow chart of exemplary power management method 200 in accordance with one embodiment of the present invention. Power management method 200 facilitates efficient and effective power management. Power management method 200 can facilitate on the fly power management with updated parameters.


In block 210, an automated initiation metric determination process is performed. In one embodiment, an automated initiation metric determination process determines a metric or threshold for initiating or triggering a power state adjustment process. An automated initiation metric determination process can facilitate adjustments in a power saving initiating or triggering threshold value or indication. The threshold adjustments can be based upon relatively recent activities or temporally proximate behavior or characteristics. The threshold adjustments can also be automatically determined and updated in the field.


In one embodiment, the initiation metric or threshold for initiation or triggering a power state adjustment process corresponds to the duration of a high power inactive period (e.g., duration X in FIG. 1, etc.). For example, the threshold can be a time duration (e.g., 2 seconds, 100 milliseconds, 3 minutes, etc.) that the system waits after an idle period starts (e.g., at time A of FIG. 1, etc.) before initiating or entering a low power state transition (e.g., at time B of FIG. 1, etc.). Additional exemplary aspects of initiation metric determination processes are set forth in description below.


In block 220, a power state adjustment process is performed. The power state adjustment process is performed in accordance with results of the automated initiation metric or threshold determination process. In one embodiment, a reduced power consumption state or mode is entered and exited. For example, the power state adjustment process can begin at time B of FIG. 1 when the system enters a low power state. In one exemplary implementation, the power state (e.g., high power state, low power state, etc.) is controlled by power-gating.



FIG. 3 is a flowchart of an exemplary automated initiation metric determination or threshold determination process 300 in accordance with one embodiment of the present invention. A an automated initiation metric or threshold determination process can include a number of factors or considerations. The factors or considerations can include examining the probability that initiating a power reduction operation will save more power than the power cost of entering and exiting a power reduced state. The an automated initiation metric or threshold determination process can automatically update the threshold value. In addition, the threshold determination process can be directed to establishing an optimized threshold setting that also facilitate minimizing detrimental response effects, such as lag after wake-up indications.


In block 310, an activity monitoring process is performed. It is appreciated that durations of component active operations and inactive operations can be tracked. The monitored or tracked active operations and inactive operations can be directed to tasks or activities other than changing power levels. For example, operations associated with an application (e.g. receiving input, calculating results, presenting output, activities that occur during period Z1 of FIG. 1, etc.) are monitored for purposes of determining application activity, and operations directly associated with entering and exiting the low power state (e.g. power gating, activities during period Y1 of FIG. 1, etc.) are not monitored for purposes of determining application activity. In other words, if an application is inactive and the system begins to enter a low power state, the operations directly associated with entering the low power state are not monitored for purposes of initiating an exit of the low power state.


In block 320, a system architecture characteristic analysis process is performed. In one embodiment, the system architecture power-consumption break-even time (BE) is determined for the system. In one exemplary implementation, the power-consumption break-even time is the amount of time the system has to stay in the low power state to save an amount of power equal to the amount or power overhead consumed entering and leaving the power state.


In step 330, a system utilization analysis process is performed. In one embodiment, the idle period durations measured in step 310 can be sorted into a variety of different length intervals and analyzed accordingly. In one embodiment, histograms are created based upon sorted idle time durations. The idle period durations can be sorted into “bins” or “buckets” associated with an idle time duration.


In one embodiment, the idle periods within particular durations are tracked or counted. The “bin” or “bucket” count is increased for each corresponding idle period. For example, idle periods that are less than 2X clock cycles are counted and stored in a bucket 0; idle periods that are between 2X and 2(X+1) clock cycles are counted and stored in a bucket 1; . . . up to idle periods that are greater than 2(X+14) clock cycles that are stored in a bucket 16. The variable X is a programmable number that is based on clock frequency changes for different operating modes (e.g., X can be adjusted to cover a desired range of idle periods as the clock frequency is changed for different operating modes). In the current embodiment, sixteen buckets are used. Bucket 0 stores the number of idle periods that are less than 2X clock cycles. Bucket 1 stores the number of idle periods that are between than 2X and 2(X+1) clock cycles. Up to, bucket 16 that stores the number of idle periods that are greater than 2(X+14) clock cycles. In alternate embodiments, different numbers of buckets may be used. For example, increasing the number of buckets can improve resolution in critical ranges.


It is appreciated the present systems and methods can be utilized in weighted average type analysis. In one exemplary implementation an algorithm in which the total power saved during the time periods beyond the threshold can be analyzed. In one embodiment, for each bucket greater than or equal to the threshold the following algorithm is performed;

(idle period of the bucket−threshold−BE)*(bucket count).

In one embodiment, If the sum from the buckets greater than the threshold is positive there is a the net power savings and if the sum negative there is not a net power savings.



FIG. 4A is a block diagram of a histogram of idle times or durations in accordance with one embodiment of the present invention. The X axis corresponds to the number of seconds in an idle period and the Y axis corresponds to a count of the number of times the system entered a corresponding idle period. In one exemplary implementation, the breakeven time is 3 seconds. If the threshold value is set at 2 seconds the following analysis:

((2−2−3)*10)+((3−2−3)*10)+((4−2−3)*2)+((5−2−3)*1)+((6−2−3)*1)+((7−2−3)*8)+((8−2−3)*5)+((9−2−3)*2)=−12

which indicates that there would be a net power loss. A similar analysis indicates there is a net power loss if the threshold is set at 3 seconds. However, if the threshold is set at 4 seconds the following analysis:

((4−4−3)*2)+((5−4−3)*1)+((6−4−3)*1)+((7−4−3)*8)+((8−4−3)*5)+((9−4−3)*2)=6

which indicates that there would be a net power savings.


The histogram of FIG. 4A indicates that if the threshold or wait period (e.g., period X of FIG. 1) is set to 4 seconds the probability of saving energy overall when entering the low power state after inactivity for 4 seconds or more is relatively high and beneficial. Therefore, while there may be a few instances (e.g., 4, 5, and 6 second bins of the histogram) where the system may not remain inactive long enough to break even on power consumption, these instances are significantly outweighed by the instances (e.g., 7, 8 and 9 second bins of the histogram) where the system remains inactive long enough to more than break even on power consumption. Thus, the 4 second threshold can provide a significant overall power savings. It is appreciated that the durations can be measured in a variety of units (e.g., microseconds (μs), milliseconds (ms), etc.).)



FIG. 4B is another block diagram of a histogram in accordance with one embodiment of the present invention. FIG. 4B can represent an entirely different system from FIG. 4A, or FIG. 4B can represent the same system as FIG. 4A monitored at a different time. In one exemplary implementation, the breakeven time is 3 seconds. The histogram of FIG. 4B indicates that if the threshold or wait period (e.g., period X of FIG. 1) is set to 2 seconds there is a likelihood of an overall net energy savings. For example, if the threshold value is set at 2 seconds the following analysis:

((2−2−3)*1)+((3−2−3)*5)+((4−2−3)*10)+((5−2−3)*2)+((6−2−3)*1)+((7−2−3)*1)+((8−2−3)*1)+((9−2−3)*10)=−23

which indicates that there would be a net power savings.


In another embodiment, a different algorithm can be utilized. If the threshold or wait period (e.g., period X of FIG. 1) is set to 5 seconds the number of times the system stays in low power for more than three seconds indicates the probability remaining in an idle state for longer than 3 seconds (e.g., saving power for 3 or more seconds) when entering the low power state after inactivity for more than 5 seconds is beneficial. There are a relatively few instances (e.g., 5 times total for the 5, 6, 7 and 8 second bins of the histogram) where the system does not remain inactive long enough to break even on power consumption, but these are outnumbered by instances (e.g., 10 times total for the 9 second bin of the histogram) where the system may does remain inactive long enough to at least break even on power consumption. Thus, the 5 second threshold is likely to provide an overall power savings and probably beneficial.


While “guessing wrong” or inappropriately entering a power reduction state for a system that has a wakeup process that requires a relatively short time may have relatively little impact to the overall performance, when the wakeup process requires a relatively long time the impact of guessing wrong can increase. It can be important to avoid entering the low power state when the logic is not likely to remain in the low power state for a sufficiently long enough time to permit power savings commensurate with power consumption during a long wake up process.


It is appreciated that adjustments to the buckets can be utilized to tweak appropriate threshold prediction. In alternate embodiments, different numbers of buckets may be used. For example, increasing the number of buckets can improve resolution in critical ranges. FIG. 4C is a block diagram of another exemplary histogram with a different number of buckets in accordance with one embodiment of the present invention. The resolution or duration of 12 buckets in FIG. 4C is a half a second as compared to the resolution or duration of one second for the 9 buckets in FIG. 4A. In one exemplary implementation, the total number of buckets remains the same but the time duration associated with the buckets can be adjusted. For example, some buckets can be associated with a two second duration and other buckets can be associated with half a second duration. FIG. 4D is a block diagram of another exemplary histogram with different duration buckets in accordance with one embodiment of the present invention. There are a total of nine buckets similar to FIG. 4A except in FIG. 4D the duration of the buckets between 4.5 to 6.5 are incremented by half a second while the others are incremented by 2 second durations.


With reference again to FIG. 3, in step 340 a threshold value is established. The threshold is set based on the previous activity patterns stored in the binning. The threshold is calculated to maximize power efficiency, while maintaining performance. In one exemplary implementation, the threshold value is established by a threshold determining component (e.g., threshold determining component 608, etc.). In one embodiment, the threshold is forwarded. For example, the threshold is communicated to a power control component. In one embodiment, a power control component (e.g., power control component 604, etc.) sets a power level based on the threshold.



FIGS. 2 and 3 are exemplary flowcharts and although specific steps are disclosed in the flowcharts, such steps are exemplary. That is, embodiments of the present invention are well-suited to performing various other steps or variations of the steps. The flowcharts of FIGS. 2 and 3 can be implemented as computer-executable instructions residing on some form of computer-usable medium, such as program modules, executed by one or more computers or other devices. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform particular tasks or implement particular abstract data types. The functionality of the program modules may be combined or distributed as desired in various embodiments.


By way of example, and not limitation, computer-usable media may comprise computer storage media and communication media. Computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer-readable instructions, data structures, program modules or other data. Computer storage media includes, but is not limited to, random access memory (RAM), read only memory (ROM), electrically erasable programmable ROM (EEPROM), flash memory or other memory technology, compact disk ROM (CD-ROM), digital versatile disks (DVDs) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information.


Communication media can embody computer-readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media. The term “modulated data signal” means a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. By way of example, and not limitation, communication media includes wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, radio frequency (RF), infrared and other wireless media. Combinations of any of the above should also be included within the scope of computer-readable media.



FIG. 5 is a block diagram of an exemplary computer system 500, one embodiment of a computer system upon which embodiments of the present invention can be implemented. Computer system 500 includes central processor unit 510, main memory 520 (e.g., random access memory), chip set 530 with north bridge 531 and south bridge 532, user interface 570, and graphics subsystem 540 which is coupled to display 550. Computer system 500 includes several busses (e.g., the Advanced Graphics Port interface, a PCI bus, etc.) for communicatively coupling the components of computer system 500. It is appreciated that other components (bulk storage component, removable storage component, communications port, etc.) can be included in computer system 500.


The components of computer system 500 cooperatively operate to provide versatile functionality and performance, including implementing power conservation (e.g., during low power states or modes, etc.). Communications bus communicates information, central processor 510 processes information, main memory 520 stores information and instructions, and user interface 570 (e.g., a keyboard, a mouse, etc,) provides a mechanism for inputting information and/or for pointing to or highlighting information on display 550. Graphics processor 541 processes graphics commands from central processor 510 and provides the resulting data to frame buffer 542 for storage and retrieval by display monitor 550.


Generally speaking, the computer system 500 includes the basic components of a computer system platform that implements functionality in accordance with embodiments of the present invention. The computer system 500 can be implemented as, for example, any of a number of different types of computer systems (e.g., servers, laptops, desktops and notebooks), as well as a home entertainment system (e.g., a DVD player) such as a set-top box or digital television, or a portable or handheld electronic device (e.g., a portable phone, personal digital assistant, or handheld gaming device).



FIG. 6 is a block diagram showing the elements of a power management system 600 according to one embodiment of the present invention. In the example of FIG. 6, the system 600 includes a power-consuming element 602, such as a logic circuit. The power-consuming element 602 is communicatively coupled to a power control component 604 and a monitoring component 606. The power control component 604 and the monitoring component 606 are communicatively coupled to a threshold-determining component 608.


In one embodiment, the monitoring component 606 monitors the activity pattern of the power-consuming element 602 in real time and forwards the results to threshold determining component 608 and power control component 604. Based on the activity of the power-consuming element 602, the threshold determining component 608 determines a beneficial threshold or duration of inactivity for indicating power reduction initiation (e.g., initiate transition to a low power state, begin power-gating, etc.). Power control component 604 directs power consumption state adjustment based upon the threshold received from the threshold determining component 608. In one embodiment, power control component 604 regulates power consumption by directing power-gating


As part of analyzing the monitored activity pattern of the power-consuming element 602, the threshold determining component 608 can direct allocation or binning (e.g., to create a histogram, etc.) of the duration of previous idle periods. In one embodiment, sixteen buckets or bins can be used. Bucket 0 stores the number of idle periods that are less than 2X clock cycles. Bucket 1 stores the number of idle periods that are between than 2X and 2(X+1) clock cycles. Up to, bucket 16 that stores the number of idle periods that are greater than 2(X+14) clock cycles. X is programmable and can be adjusted to cover a desired range of idle periods as the clock frequency is changed for different operating modes. In alternate embodiments, different numbers of buckets and bucket durations may be used (e.g., see FIGS. 4A through 4D). For example, increasing the number of buckets can improve resolution in critical ranges (e.g., ranges close to a breakeven threshold value, other ranges, etc.).


The monitoring component 606 can sample continued activity at various times and process the results to form an updated histogram. In the one embodiment, the histogram is sampled once very second. However, alternate embodiments may sample the histogram at any interval. An optimal interval to use can depend on the minimum monitoring time necessary to get a useful history of the activity pattern. However, if the sampling interval is set too long, then the power management system 600 might be too slow to adapt to changing activity patterns.


In one embodiment, power gating is utilized. Power-gating is a technique by which the power or ground connection of a logic circuit is electrically disconnected using on-chip field-effect transistors (“FETs”) in order to save static power when the circuit is not being used. It can reduce power consumption in nanometer-scale process technologies with high sub-threshold leakage. A successful power reduction or power-gating cycle of a graphics engine can be modeled as follows:

    • 1. The power-consuming element 602 (e.g., a graphics engine, CPU component, etc.) becomes idle.
    • 2. The monitoring component 606 (e.g., idle-detection hardware, etc.) waits for [X] idle clock cycles, rejecting idle periods that are too short to be efficiently power-gated.
    • 3. The control component 604 power-gates the graphics engine, taking [Y1] seconds.
    • 4. The power-consuming element 602 is power-gated.
    • 5. The power-consuming element 602 must be powered-on to perform new work.
    • 6. The control component 604 powers-on the power-consuming element 202, taking [Y2] seconds.
    • 7. The power-consuming element 602 is now active again.


The above model time line can be summarized as follows:

    • 1. Idle starts; delay for [X]
    • 2. Power-gating takes [Y1]
    • 3. Remain power-gated for [P]
    • 4. Wakeup starts; powering-on takes [Y2]
    • 5. Work starts again


      Thus, the total idle time [I]=[X]+[Y1]+[P], or the time between going idle and waking-up. Therefore, power-gated time [P]=[I]−[X]−[Y1].


There can be power consumption overhead to go in and out of power-gating. In one embodiment, the threshold determining component 608 can consider the break-even time [BE], such that the effective power-gated time [P′]=[I]−[X]−[Y1]−[BE]. The break-even time can be a very important factor, because if [I] is too small, the effective power-gated time can be negative with the potential for more power to be wasted than saved.


There is also a potential performance impact due to power-gating. The impact can be characterized as the delay between the start of the wakeup process and the resumption of work (e.g., duration Y2 for each power-gating cycle, etc.).


In one embodiment [Y1], [BE], and [Y2] can be characterized per system design, and the changing variables are the total idle periods [I] and the idle filter setting [X]. Given a sample of the idle period durations with the above mentioned hardware, the total effective power-gated time [P′] can be calculated for each idle filter setting [X]. Then the optimal idle filter setting that yields the highest total effective power-gated time can be analytically determined in real time.


In one embodiment, a negative performance impact from power-gating can also be controlled by limiting the number of power-gating cycles over an interval to a programmable maximum of [N]. In one exemplary implementation, this can ensure that the total latency impact over the interval would be limited to a maximum of [N]*[Y2].


In one embodiment, power management system 600 monitors past activity to determine configuration settings for future events. In this situation, the performance of the power management system 600 can be dependent on how well future activity corresponds to previous activity. Therefore, it can be useful to evaluate how well the power management system 600 is performing on a relatively often or frequent basis. The power management system 600 can suspend or turn off power reduction activities when they would perform poorly or be detrimental.


In one embodiment, the performance of the power management system 600 results are measured. In one exemplary implementation, the results for different histograms created during different sampling intervals can be compared. The results of a first histogram collected over a first time frame of [T0] to [T1] and the results of a second histogram collected over a second time frame from [T1] to [T2]. For example, the first histogram can be similar to the histogram of FIG. 4A and the second histogram can be similar to the histogram of FIG. 4B. A first optimal idle filter setting [X0] can be established based on the histogram collected from [T0] to [T1]. A second optimal idle filter setting [X1] can be established based on the histogram collected from [T1] to [T2]. The activity pattern between [T1] and [T2] can compared with the [X0] idle filter setting. If [X0] provides acceptable power efficiency relative to the system-specific break-even point, in one exemplary implementation the power management system 600 is considered to be performing well and can continue to be enabled.


In one embodiment, it is possible to enable power-gating when the previous prediction has been proven to be successful. This ensures that the power management system can be applied on stable activity patterns, where successful application is most likely.


In one exemplary implementation, entrance of low power states is suspended when the monitoring indicates an activity pattern is changing rapidly or erratically and entering the low power state is less likely to be successful or beneficial (e.g., save more power than the power consumed entering, during and existing the low power state). For example, if the monitoring of activity and analysis indicates that reasonable predictions can not be made regarding the probability that a threshold value is a good indication that entering a power reduction state is not likely to lead to wasted power consumption entering and existing the low power state, then the power management system can suspend entering low power states. The entering of low power states can be suspended until the monitoring of activity and analysis indicates that reasonable predictions can be made regarding the probability that a threshold value is a good indication that entering a power reduction state is not likely to lead to wasted power consumption entering and exiting the low power state.



FIG. 7 is a block diagram showing a power management system within a portion of the computer system, according to an embodiment of the present invention. In the current embodiment, the power consuming element 733 is located in the graphics processing unit GPU 730. The threshold-determining component 721 is located in the central processing unit CPU 720. Portions of the power control component 732 and the monitoring component 731 are located in the CPU 720 and the GPU 730. However, the components are not limited to these locations and may be located in alternate locations, including but not limited to, the GPU 730, the CPU 720, outside both the GPU 730 and the CPU 720, or combinations of the above. Furthermore, the components may be hardware, software, firmware, combinations of the above, etc.


In one embodiment, the power management system can determine when to power-gate in a variety of GPU operating modes:


during idle in a natively 3D operating system, in between rendering activities,


during video playback, in between rendering of video frames, and


during 3D rendering, in between rendering of 3D frames.


However, a power management system can be applied to any power consuming element, operation, task, device, or system.


Thus, the present systems and methods facilitate efficient and effective power conservation. In one embodiment, a present system and method can facilitate minimization of adverse power reduction activities.


The foregoing descriptions of specific embodiments of the present invention have been presented for purposes of illustration and description. They are not intended to be exhaustive or to limit the invention to the precise forms disclosed, and many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and its practical application, to thereby enable others skilled in the art to best utilize the invention and various embodiments with various modifications as are suited to the particular use contemplated. It is intended that the scope of the invention be defined by the claims appended hereto and their equivalents.

Claims
  • 1. A power management method comprising: performing an initiation metric determination process, wherein said initiation metric determination process includes:performing an activity monitoring process;performing, by a processor, a system architecture characteristic analysis in which a system architecture power-consumption break-even time (BE) is determined for the system;establishing, by said processor, a power conservation initiation threshold value automatically; andperforming a power state adjustment process to an electronic system based on said threshold value.
  • 2. The method of claim 1 wherein said adjusting operations comprises entering a low power state.
  • 3. The method of claim 1 wherein said monitoring comprises collecting a histogram of previous idle period durations.
  • 4. The method of claim 1 wherein said initiation metric determination process further comprises performing a system utilization analysis process in which idle period durations detected during said activity monitoring process are sorted into a variety of different length intervals and analyzed accordingly.
  • 5. The method of claim 1 wherein said activity monitoring process includes tracking durations of component active operations and inactive operations.
  • 6. The method of claim 1 further comprising suspending entrance of low power states when said activity monitoring process indicates an activity pattern is changing rapidly or erratically and entering the low power state is less likely to be successful.
  • 7. A system of power management comprising: a monitoring component that tracks power usage;a threshold determining component, included in a processor, that establishes a threshold based on said power usage, wherein the threshold value includes examining the probability that initiating a power reduction operation saves more power than a power cost of entering and existing a power reduced state; anda power control component that directs power consumption state adjustment of an electronic component based on said threshold.
  • 8. The system of claim 7 wherein said power control component regulates power consumption by directing power-gating.
  • 9. The system of claim 7 wherein said threshold determining component establishes said threshold such that time in a power reduction state conserves more power than is consumed entering said power reduction state.
  • 10. The system of claim 7 wherein said threshold determining component comprises an idle detect counter that tracks respective idle period counts.
  • 11. The system of claim 7 wherein said power control component directs power consumption state adjustment during a total idle time [I]; wherein said total idle time [I]=[X]+[Y1]+[P], wherein [X] is a duration in an inactive high power state, [Y1] is a duration while entering a low power state, and [P] is the duration at said low power level.
  • 12. The system of claim 7 wherein an effective time at a low power level is determined based upon the equation [P′]=[I]−[X]−[Y1]−[BE], wherein [BE] is a break even time and [P′] is a positive value.
  • 13. The system of claim 12 wherein [Y1] and [BE] are characterized per system design and said threshold determining component calculates an idle filter setting associated with the idle start delay [X] for each total idle period [I].
  • 14. A power management method comprising: measuring idle of an electronic component;binning said idle measurement, wherein said binning comprises counting idle periods that correspond to respective 2X clock cycles wherein X is a programmable number; andautomatically determining, by a processor, a threshold for said electronic component based on said binning.
  • 15. The method of claim 14 further comprising setting a power level based on said threshold.
  • 16. The method of claim 14 further comprising communicating said threshold to a power control component.
  • 17. The method of claim 14 further comprising adjusting X based on clock frequency changes for different operating modes.
US Referenced Citations (264)
Number Name Date Kind
4335445 Nercessian Jun 1982 A
4544910 Hoberman Oct 1985 A
4679130 Moscovici Jul 1987 A
4706180 Wills Nov 1987 A
4739252 Malaviya et al. Apr 1988 A
4868832 Marrington et al. Sep 1989 A
4893228 Orrick et al. Jan 1990 A
5086501 DeLuca et al. Feb 1992 A
5103110 Housworth et al. Apr 1992 A
5167024 Smith et al. Nov 1992 A
5177431 Smith et al. Jan 1993 A
5201059 Nguyen Apr 1993 A
5204863 Saint-Joigny et al. Apr 1993 A
5218704 Watts, Jr. et al. Jun 1993 A
5218705 DeLuca et al. Jun 1993 A
5230055 Katz et al. Jul 1993 A
5239652 Seibert et al. Aug 1993 A
5254878 Olsen Oct 1993 A
5300831 Pham et al. Apr 1994 A
5307003 Fairbanks et al. Apr 1994 A
5337254 Knee et al. Aug 1994 A
5339445 Gasztonyi Aug 1994 A
5350988 Le Sep 1994 A
5396443 Mese et al. Mar 1995 A
5410278 Itoh et al. Apr 1995 A
5422806 Chen et al. Jun 1995 A
5440520 Schutz et al. Aug 1995 A
5446365 Nomura et al. Aug 1995 A
5461266 Koreeda et al. Oct 1995 A
5502838 Kikinis Mar 1996 A
5511203 Wisor et al. Apr 1996 A
5513152 Cabaniss Apr 1996 A
5560020 Nakatani et al. Sep 1996 A
5561692 Maitland et al. Oct 1996 A
5568103 Nakashima et al. Oct 1996 A
5568350 Brown Oct 1996 A
5583875 Weiss Dec 1996 A
5586308 Hawkins et al. Dec 1996 A
5587672 Ranganathan et al. Dec 1996 A
5589762 Iannuzo Dec 1996 A
5590342 Marisetty Dec 1996 A
5592173 Lau et al. Jan 1997 A
5594360 Wojciechowski Jan 1997 A
5630110 Mote, Jr. May 1997 A
5648766 Stengel et al. Jul 1997 A
5666522 Klein Sep 1997 A
5675272 Chu Oct 1997 A
5680359 Jeong Oct 1997 A
5682093 Kivela Oct 1997 A
5692204 Rawson et al. Nov 1997 A
5710929 Fung Jan 1998 A
5717319 Jokinen Feb 1998 A
5719800 Mittal et al. Feb 1998 A
5727208 Brown Mar 1998 A
5737613 Mensch, Jr. Apr 1998 A
5742142 Witt Apr 1998 A
5745375 Reinhardt et al. Apr 1998 A
5752011 Thomas et al. May 1998 A
5754869 Holzhammer et al. May 1998 A
5757171 Babcock May 1998 A
5757172 Hunsdorf et al. May 1998 A
5760636 Noble et al. Jun 1998 A
5764110 Ishibashi Jun 1998 A
5774703 Weiss et al. Jun 1998 A
5774704 Williams Jun 1998 A
5778237 Yamamoto et al. Jul 1998 A
5787011 Ko Jul 1998 A
5796313 Eitan Aug 1998 A
5812860 Horden et al. Sep 1998 A
5815724 Mates Sep 1998 A
5825674 Jackson Oct 1998 A
5825972 Brown Oct 1998 A
5847552 Brown Dec 1998 A
5848281 Smalley et al. Dec 1998 A
5864225 Bryson Jan 1999 A
5884049 Atkinson Mar 1999 A
5884068 Conary et al. Mar 1999 A
5894577 MacDonald et al. Apr 1999 A
5913067 Klein Jun 1999 A
5923545 Nguyen Jul 1999 A
5926394 Nguyen et al. Jul 1999 A
5933649 Lim et al. Aug 1999 A
5940785 Georgiou et al. Aug 1999 A
5940786 Steeby Aug 1999 A
5952798 Jones et al. Sep 1999 A
5974557 Thomas et al. Oct 1999 A
5977763 Loughmiller et al. Nov 1999 A
5978926 Ries et al. Nov 1999 A
5996083 Gupta et al. Nov 1999 A
5996084 Watts Nov 1999 A
6005904 Knapp et al. Dec 1999 A
6011403 Gillette Jan 2000 A
6023776 Ozaki Feb 2000 A
6025737 Patel et al. Feb 2000 A
6035357 Sakaki Mar 2000 A
6035407 Gebara et al. Mar 2000 A
6040668 Huynh et al. Mar 2000 A
6047248 Georgiou et al. Apr 2000 A
6065126 Tran et al. May 2000 A
6065131 Andrews et al. May 2000 A
6124732 Zilic et al. Sep 2000 A
6134167 Atkinson Oct 2000 A
6141762 Nicol et al. Oct 2000 A
6163583 Lin et al. Dec 2000 A
6167524 Goodnow et al. Dec 2000 A
6167529 Dalvi Dec 2000 A
6172943 Yuzuki Jan 2001 B1
6216234 Sager et al. Apr 2001 B1
6219795 Klein Apr 2001 B1
6229747 Cho et al. May 2001 B1
6242936 Ho et al. Jun 2001 B1
6243656 Arai et al. Jun 2001 B1
6255974 Morizio et al. Jul 2001 B1
6304824 Bausch et al. Oct 2001 B1
6310912 Maiocchi et al. Oct 2001 B1
6311287 Dischler et al. Oct 2001 B1
6360327 Hobson Mar 2002 B1
6363490 Senyk Mar 2002 B1
6366157 Abdesselem et al. Apr 2002 B1
6369557 Agiman Apr 2002 B1
6407571 Furuya et al. Jun 2002 B1
6415388 Browning et al. Jul 2002 B1
6422746 Weiss et al. Jul 2002 B1
6425086 Clark et al. Jul 2002 B1
6426641 Koch et al. Jul 2002 B1
6448815 Talbot et al. Sep 2002 B1
6456049 Tsuji Sep 2002 B2
6457134 Lemke et al. Sep 2002 B1
6470289 Peters et al. Oct 2002 B1
6476632 La Rosa et al. Nov 2002 B1
6484041 Aho et al. Nov 2002 B1
6489796 Tomishima Dec 2002 B2
6535424 Le et al. Mar 2003 B2
6535986 Rosno et al. Mar 2003 B1
6600575 Kohara Jul 2003 B1
6621242 Huang et al. Sep 2003 B2
6630754 Pippin Oct 2003 B1
6650074 Vyssotski et al. Nov 2003 B1
6650740 Adamczyk et al. Nov 2003 B1
6657504 Deal et al. Dec 2003 B1
6662775 Hauser Dec 2003 B2
6668346 Schulz et al. Dec 2003 B1
6674587 Chhabra et al. Jan 2004 B2
6678831 Mustafa et al. Jan 2004 B1
6690219 Chuang Feb 2004 B2
6703803 Ohiwa et al. Mar 2004 B2
6714891 Dendinger Mar 2004 B2
6718496 Fukuhisa et al. Apr 2004 B1
6721892 Osborn et al. Apr 2004 B1
6737860 Hsu et al. May 2004 B2
6748408 Bredin et al. Jun 2004 B1
6774587 Makaran et al. Aug 2004 B2
6792379 Ando Sep 2004 B2
6794836 Strothmann et al. Sep 2004 B2
6795075 Streitenberger et al. Sep 2004 B1
6795927 Altmejd et al. Sep 2004 B1
6799134 Borchers et al. Sep 2004 B2
6801004 Frankel et al. Oct 2004 B2
6804131 Galbiati et al. Oct 2004 B2
6806673 Ho Oct 2004 B2
6815938 Horimoto Nov 2004 B2
6815971 Wang et al. Nov 2004 B2
6831448 Ishii et al. Dec 2004 B2
6836849 Brock et al. Dec 2004 B2
6837063 Hood, III et al. Jan 2005 B1
6853259 Norman et al. Feb 2005 B2
6853569 Cheng et al. Feb 2005 B2
6885233 Huard et al. Apr 2005 B2
6889331 Soerensen et al. May 2005 B2
6889332 Helms et al. May 2005 B2
6914492 Hui et al. Jul 2005 B2
6938176 Alben et al. Aug 2005 B1
6947865 Mimberg et al. Sep 2005 B1
6970798 Cao et al. Nov 2005 B1
6975087 Crabill et al. Dec 2005 B1
6976112 Franke et al. Dec 2005 B2
6987370 Chheda et al. Jan 2006 B2
6990594 Kim Jan 2006 B2
7003421 Allen, III et al. Feb 2006 B1
7005894 Weder Feb 2006 B2
7042296 Hui et al. May 2006 B2
7043649 Terrell, II May 2006 B2
7045993 Tomiyoshi May 2006 B1
7051215 Zimmer et al. May 2006 B2
7068557 Norman et al. Jun 2006 B2
7071640 Kurosawa et al. Jul 2006 B2
7100061 Halepete et al. Aug 2006 B2
7112978 Koniaris et al. Sep 2006 B1
7119522 Tomiyoshi Oct 2006 B1
7122978 Nakanishi et al. Oct 2006 B2
7129745 Lewis et al. Oct 2006 B2
7149909 Cui et al. Dec 2006 B2
7180322 Koniaris et al. Feb 2007 B1
7256571 Mimberg et al. Aug 2007 B1
7256788 Luu et al. Aug 2007 B1
7334198 Ditzel et al. Feb 2008 B2
7336090 Koniaris et al. Feb 2008 B1
7336092 Koniaris et al. Feb 2008 B1
7348827 Rahim et al. Mar 2008 B2
7348836 Velmurugan Mar 2008 B1
7363176 Patel et al. Apr 2008 B2
7409570 Suzuoki Aug 2008 B2
7414450 Luo et al. Aug 2008 B2
7490256 Marshall et al. Feb 2009 B2
7509504 Koniaris et al. Mar 2009 B1
7574613 Holle et al. Aug 2009 B2
7725749 Mitarai May 2010 B2
7739531 Krishnan Jun 2010 B1
7849332 Alben et al. Dec 2010 B1
7882369 Kelleher et al. Feb 2011 B1
7886164 Alben et al. Feb 2011 B1
8762761 Zheng et al. Jun 2014 B2
20010033504 Galbiati et al. Oct 2001 A1
20010045779 Lee et al. Nov 2001 A1
20020002689 Yeh Jan 2002 A1
20020004912 Fung Jan 2002 A1
20020026597 Dai et al. Feb 2002 A1
20020029352 Borkar et al. Mar 2002 A1
20020032829 Dalrymple Mar 2002 A1
20020049920 Staiger Apr 2002 A1
20020073348 Tani Jun 2002 A1
20020083356 Dai Jun 2002 A1
20020087896 Cline et al. Jul 2002 A1
20020099964 Zdravkovic Jul 2002 A1
20020113622 Tang Aug 2002 A1
20020116650 Halepete et al. Aug 2002 A1
20020138778 Cole et al. Sep 2002 A1
20020178390 Lee Nov 2002 A1
20020194509 Plante et al. Dec 2002 A1
20030036876 Fuller, III et al. Feb 2003 A1
20030065960 Rusu et al. Apr 2003 A1
20030074591 McClendon et al. Apr 2003 A1
20030079151 Bohrer et al. Apr 2003 A1
20030110423 Helms et al. Jun 2003 A1
20030133621 Fujii et al. Jul 2003 A1
20030189465 Abadeer et al. Oct 2003 A1
20040025061 Lawrence Feb 2004 A1
20040032414 Jain et al. Feb 2004 A1
20040073821 Naveh et al. Apr 2004 A1
20040105237 Hoover et al. Jun 2004 A1
20040105327 Tanno Jun 2004 A1
20040123170 Tschanz et al. Jun 2004 A1
20040123172 Sheller Jun 2004 A1
20040128631 Ditzel et al. Jul 2004 A1
20040215779 Weber Oct 2004 A1
20050007047 Strothmann et al. Jan 2005 A1
20050071705 Bruno et al. Mar 2005 A1
20050218871 Kang et al. Oct 2005 A1
20050268141 Alben et al. Dec 2005 A1
20050268189 Soltis Dec 2005 A1
20050289367 Clark et al. Dec 2005 A1
20060074576 Patel et al. Apr 2006 A1
20070220289 Holle et al. Sep 2007 A1
20070229054 Dobberpuhl et al. Oct 2007 A1
20070234088 Marshall et al. Oct 2007 A1
20070257710 Mari et al. Nov 2007 A1
20070296440 Takamiya et al. Dec 2007 A1
20080143372 Koniaris et al. Jun 2008 A1
20090072885 Kawasaki Mar 2009 A1
20100216524 Thomas et al. Aug 2010 A1
20100318828 Elting et al. Dec 2010 A1
20110264946 Goodemote et al. Oct 2011 A1
20110283130 Pai et al. Nov 2011 A1
20120102344 Kocev et al. Apr 2012 A1
Foreign Referenced Citations (21)
Number Date Country
0381021 Aug 1990 EP
0474963 Mar 1992 EP
0501655 Sep 1992 EP
0632360 Jan 1995 EP
0978781 Feb 2000 EP
1096360 May 2001 EP
1182538 Feb 2002 EP
1182556 Feb 2002 EP
1398639 Mar 2004 EP
2342471 Apr 2000 GB
2393540 Mar 2004 GB
2404792 Feb 2005 GB
H07129277 May 1995 JP
409185589 Jul 1997 JP
10187300 Jul 1998 JP
2000284862 Oct 2000 JP
3076234 Mar 2001 JP
2003122459 Apr 2003 JP
2003195981 Jul 2003 JP
0127728 Apr 2001 WO
03079171 Sep 2003 WO
Non-Patent Literature Citations (21)
Entry
“Computer Software”, Wikipedia, http://en.wikipedia.org/wiki/software, retrieved May 2, 2007.
“High Speed, Digitally Adjusted Stepdown Controllers for Notebook CPUS”, Maxim Manual, pp. 11& 21.
Alben, et al.; A Processor Speed Adjustment System and Method; U.S. Appl. No. 10/449,942, filed May 30, 2003.
Alben, et al.; A Processor Voltage Adjustment System and Method; U.S. Appl. No. 10/448,891, filed May 30, 2003.
Baker, K. et al.; “Wafer Burn-In Isolation Circuit” IBM Technical Disclosure Bulletin, IBM Corp., New York, US, vol. 32, No. 6B, Nov. 1, 1989, pp. 442-443, XP00073858 ISSN: 0018-8689.
Baker, K. et al.; 'Shmoo Plotting: The Black Art of IC Testing, IEEE Design and Test of Computers, IEEE vol. 14, No. 3; Jul. 1, 1997; pp. 90-97; XP000793305 ISSNL 0740-7475.
Calavert, J.B., “The Phase-Locked Loop”, Jul. 24, 2001, http://www.du.edut/˜etuttle/electron/elect12.htm.
Grishman, Ralph; Lecture Notes, “Computer System Design-Spring 2002”, “Lecture 2: Combinational Logic Design”, 2002, Department of Computer Science, New York University.
Operation U (Refer to Functional Diagram), LTC 1736 Linear Technology Manual, p. 9.
Kelleher, et al.; A Processor Performance Adjustment System and Method; U.S. Appl. No. 10/295,619, filed Nov. 14, 2002.
Laplante, P. Comprehensive Dictionary of Electrical Engineering, CRC Press, IEEE Press, pp. 164-165.
Microsoft Technology Inc. Linear Voltage Fan Speed Control Using Microchips TC64X Family, pp. 1-4, 2003.
Migdal, et al.; “A Processor Temperature and ODE Adjustment System and Method”, U.S. Appl. No. 10/295,748, filed Nov. 14, 2002.
Oner, H et al.; “A Compact Monitoring Circuit for Real-Time-On-Chip Diagnosis of Hot-Carrier Induced Degradation”. Microelectronics Test Structures, 1997. ICMTS 1997. Proceedings, IEEE International Conference on Monterey, CA May 17 1993-May 20, 1997, pp. 72-76.
Govil, K. et al.; “Comparing Algorithms for Dynamic Speed-Setting of a Low-Power PCU”; International Computer Science Institute; Berkeley, CA; Apr. 1995.
Mobile Pentium® III Processors-Thermal Management, http://support.intel.com/support/processors/mobile/pentiumiii/thermal.htm, Sep. 12, 2002, pp. 1-4.
Hong, I. et al.; Power Optimization of Variable Voltag Core Based Systems; Jun. 1998; Design Automation Conference Proceedings.
Hong, I. et al.; Synthesis Techniques for Low-Power Hard Real-Time Systems on Variable Voltage Processors; Real-Time System Symposium Proceedings. Dec. 1998.
Intel, Intel Pentium 4 Processor in the 423-pin Package, pp. 78-80, (Date believed prior to Nov. 14, 2002).
Mobile Pentium® III Processors-Thermal Diode, http://support.intel.com/support/processors/mobile/pentiumiii/diode.htm, Sep. 12, 2002, pp. 1-2.
Mobile Pentium® III Processors-Enhanced Intel® SpeedStep™ Technology, http://support.intel.com/support/processors/mobile/pentiumiii/tti004.htm, Sep. 12, 2002, pp. 1-4.
Related Publications (1)
Number Date Country
20110291748 A1 Dec 2011 US