Patent Grant
9292293
Currently, manufactures manage power consumption and thermal issues in multicore devices by throttling the processing clock frequency of the multiple processor cores. Throttling the processing clock frequency of multiple processor cores of the multicore devices can help manage power consumption and thermal issues by reducing the rate of work accomplished by the multicore processors. However, this technique focuses on managing these issues at the expense of performance.
Mobile devices are increasingly incorporating multicore processors to handle the demands of the system and application software run concurrently on the mobile devices. Mobile devices are limited by having restricted power budgets that deplete quicker as more power is consumed by the mobile device to achieve higher performance levels, or maintain performance levels while handling greater software processing demands. While the software processing demands are increasing, users expect to maintain a certain level of performance on their mobile devices in terms of processing speed and battery life. Maintaining the user expected level of performance on a mobile device creates a dilemma of whether to sacrifice performance for longevity, or sacrifice longevity for performance, all while managing the thermal issues of the multicore processors.
The methods and apparatuses of various aspects provide for control of a plurality of processor cores of a multicore integrated circuit including comparing temperature readings of the plurality of processor cores to a temperature threshold, calculating a map for the plurality of processor cores based on processor core information and a plurality of hypothetical cases, identifying a first configuration of processor cores to optimize power consumption for a given workload when the temperature readings are less than the temperature threshold, identifying a second configuration of processor cores to optimize performance for a given power budget when the temperature readings are greater than the temperature threshold, and controlling an activity state for each processor core of the plurality of processor cores based on the identified configuration. In an aspect method, calculating the map for the plurality of processor cores based on the processor core information and the plurality of hypothetical cases may include calculating a power map indicating relationships between power consumption and temperature for combinations of the plurality of processor cores for a given representative value of the given workload when the temperature readings are less than the temperature threshold, and calculating a performance map indicating relationships between power consumption and workload for combinations of the plurality of processor cores for a given temperature when the temperature readings are greater than the temperature threshold.
In an aspect method, the first and second configurations of processor cores may indicate a number of active processor cores. In an aspect method, the first and second configurations of processor cores may indicate which processor cores of the plurality of processor cores are active processor cores. In an aspect method, the first and second configurations of processor cores may include the processor cores with a lowest leakage, a lowest temperature, or a lowest voltage level for a given frequency.
An aspect method may further include reading the processor core information associated with each processor core, in which the processor core information includes a leakage current, a processor core speed, a processor voltage setting table, a maximum clock frequency, a temperature reading, and a current workload, and converting the current workload into a representative value of the current workload. In an aspect method, the processor core information may include dynamic information including the temperature reading and the current workload, and the aspect method may further include repeatedly reading the dynamic information.
In an aspect method, the processor cores of the multicore integrated circuit may include one or more processor core types selected from the group including a central processing unit, a shader processor of a graphics processing unit, a texture pipe of the graphics processing unit, or a digital signal processor.
An aspect includes an apparatus including a multicore integrated circuit having a plurality of processor cores in which the multicore integrated circuit is configured with processor-executable instructions to perform operations of one or more of the aspect methods described above.
An aspect includes an apparatus for multicore control of a plurality of processor cores of a multicore integrated circuit including means for performing functions of one or more of the aspect methods described above.
An aspect includes a non-transitory processor-readable medium having stored thereon processor-executable software instructions configured to cause a multicore integrated circuit to perform operations of one or more of the aspect methods described above.
The accompanying drawings, which are incorporated herein and constitute part of this specification, illustrate exemplary aspects of the invention, and together with the general description given above and the detailed description given below, serve to explain the features of the invention.
The various aspects will be described in detail with reference to the accompanying drawings. Wherever possible, the same reference numbers will be used throughout the drawings to refer to the same or like parts. References made to particular examples and implementations are for illustrative purposes, and are not intended to limit the scope of the invention or the claims.
As used herein, the term “computing device” refers to any one or all of smart phones, laptop computers, personal computers, servers, tablet computers, palm-top computers, and similar electronic devices which individually include a programmable processor and memory and circuitry for sending signals to an integrated circuit (IC).
As used herein, the term “multicore device” refers to any computing device having an IC/system-on-chip (SoC)/processor with multiple processor cores. The exemplary multicore devices herein are described as having multicore ICs. Describing the multicore devices in terms of multicore ICs is meant to be exemplary and in no way limiting. Descriptions of multicore ICs maybe interchangeable with multicore SoCs and multicore processors (such as central processing units (CPU), graphics processing units (GPU), accelerated processing units (APU), physics processing units (PPU), digital signal processors (DSP), microprocessors, and other programmable logic devices).
As used herein, the terms “silicon leakage,” “leakage”, “IDDQ,” and “leakage current” are used interchangeably and refer to electric current that flows through insulating regions of semiconductors or conduction regions of semiconductors when a device is off. The leakage current grows exponentially with increasing temperature.
Increased power consumption by multicore ICs of multicore devices often results in increased thermal radiation or increased temperature of the multicore ICs, and decreased battery life. When the temperature of a multicore IC rises, it may result in excessive heating and reduce performance of the multicore device by shutting down processors when reaching critical temperatures, lessening the user experience. Increased power consumption may greatly reduce the battery life of a multicore device having a limited power budget, also lessening the user experience. Current thermal and power management in multicore devices may involve throttling or reducing the processor clock frequency of the processor cores. A slower processor clock creates less thermal output and uses less power, but also reduces the throughput of the workload for the processor.
The methods and devices of the various aspects provide alternative ways of managing thermal and power issues in multicore devices by controlling the number of and which processor cores within multicore ICs of multicore devices are used to perform process tasks in order to achieve optimal performance per watt of expended power. Power consumption for the same workload varies depending on the number of active processor cores running the workload due to leakage and dynamic power trends. In the various aspects, the optimal number of active cores for the best performance per watt may be determined based on various factors, such as temperature, speed, leakage, part type, and total workload, for example.
Concurrent multimedia processes on multicore devices require considerable power profiles for multicore devices with limited power budgets. Examples of such multimedia processes include graphics, physics, video, image, audio, and communications processing for one or more outputs on one or more devices.
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To determine the optimal number of and which of the processor cores 302 to have active, a workload analyzer 306 may gather signals 316 having the processor core information 304 for each processor core 302. The workload analyzer 306 may be associated with a memory (not shown) that may be used to store certain static information from the processor cores 302. The static information of the processor cores 302 may be processor core information 304 that is constant, such as the leakage, the PVS table, the part type or speed, and the maximum clock frequency. Storing this static information may reduce the overhead of retrieving the static information for the processor cores 302, thereby reducing the time and power required to determine the optimal combination of processor cores 302. The static information may result from manufacturer specifications for and/or testing during the manufacturing process of the processor core 302. A manufacturer may store the static information on the processor core 302, separate processor, or memory during manufacturing such that the static information is contained within the multicore device prior to use of the processor core 302 by the user. The remaining processor core information 304 may be dynamic information, which may vary over time. Such dynamic information may include the temperature readings and workloads of the processor cores 302. Such dynamic information may be retrieved by the workload analyzer 306 as needed, for example, for each determination of the optimal combination of processor cores 302. The workload analyzer 306 may convert the current workload information of the processor cores 302 to a representative value of the workload for the processor cores 302. For example, the workload may be represented by MIPS, processor utilization, clock frequency, or some performance counter values. The current workload information and the representative value of the workload may be for the individual or a group of the processor cores 302.
A real-time multicore power model 308 may receive a signal 318 having some or all of the processor core information 304, including the converted workload representative value. The real-time multicore power model 308 may use the processor core information 304 to compute the power consumption for the current provided processor core information 304 and the processor core information 304 for a range of hypothetical cases. These hypothetical cases may include various combinations of the active processor cores 302 over a range of temperatures at a workload value. The real-time multicore power model 308 may create power maps, or data sets, consisting of the actual and hypothetical calculations and/or calculation results indicating relationships between power consumption and temperature for combinations of the processor cores 302 for the given workloads (or the given representative value of the workloads). The hypothetical cases may also include various combinations of active processor cores 302 over a range of workloads at a given temperature. The real-time multicore power model 308 may similarly create performance maps, or data sets, based on the current provided processor core information 304 and the processor core information 304 for a range of hypothetical cases. The calculations indicating relationships between power consumption and workload represented by, for example, throughput or instructions executed per second, for combinations of the processor cores 302 at selected temperatures. The power and performance maps may be output by the real-time multicore power model 308 along with the factors used to determine the maps, such as temperatures and representative workload values, and some or all of the processor core information 304 as a signal 320.
The real-time multicore power model 308 may create either the power or performance maps depending on a current optimization policy which may be one of lowest-power for a given workload or highest-performance for a given power budget. In another aspect, whether the real-time multicore power model 308 creates the power map or performance map may depend on certain factors. For example, a temperature threshold may be applied to determine which map to create. When the temperature readings are below the threshold, the real-time multicore power model 308 may create the power map to help determine the lowest power consumption for a given workload. This may allow the multicore device to meet the workload needs while keeping the power consumption as low as possible, thereby extending the life of the battery. Keeping the power consumption as low as possible also results in keeping the temperature as low as possible while still achieving the performance goals for the workload. When the temperature readings are above the threshold, the real-time multicore power model 308 may create the performance map to help determine the best performance, or highest workload at the lowest power consumption, for a given power budget or level. This may allow the multicore device to provide the highest workload with the least amount of power, thereby having the least impact on raising the temperature or even maintaining or reducing the temperature while providing the best user experience within these parameters.
In creating the maps, the real-time multicore power model 308 may use the processor core information 304 of each processor core 302 to calculate the results based on various combinations of the individual processor cores 302. For example, the real-time multicore power model 308 may select to combine processor cores 302 having the lowest temperatures, the least leakage, the highest speed, and/or the least workload. In another aspect, the real-time multicore power model 308 may make certain assumptions in its calculations. Such assumptions may include each processor core 302 belonging to the same multicore IC 300 may share certain characteristics, like the processor core static information. Other aspects may call for the real-time multicore power model 308 to abide by certain rules in creating the combinations of processor cores 302, such as processor core combinations must include only adjacent processor cores 302 (e.g. Core 0 and Core 1; Core 1 and Core 2; Core 2 and Core 3; Core 3 and Core 4; Core 0, Core 1 and Core 2; Core 1, Core 2 and Core 3; and Core 2, Core 3 and Core 4), or only processor cores 302 of the same type may be combined. Adjacent processor cores 302 do not have to be physically adjacent, they may be designated as adjacent by rule.
A performance/watt optimization engine 310 may receive the maps and factors from the real-time multicore power model 308 as signal 320, and also a power budget from a system power budget manager 314 as signal 322. The factors may include the factors used to determine the maps, such as temperatures and representative workload values, and some or all of the processor core information 304. The optimization engine 310 may execute a performance optimization algorithm in a multi-dimensional space to determine or identify the optimal configuration of processor cores 302 for the current workload. The configuration may include the number of active and/or inactive processor cores 302, and/or which processor cores 302 should be designated to be active and/or inactive. The number of processor cores 302 to have active may be derived from the performance optimization algorithm using the maps, and in some instances the factors as well. Like the real-time multicore power model 308, the optimization engine 310 may make any combination of processor cores 302 based on individual information, based on certain assumptions, or based on a set of rules. Choosing the active and/or inactive processor cores 302 may be based on any single part or combination of the processor core information 304 of individual processor cores 302. For example, the optimization engine 310 may choose active processor cores 302 with the lowest leakage, the lowest temperature, and/or lowest voltage level for a given frequency. The optimization engine 310 may identify how many and/or which processor cores 302 to be active and/or inactive for a unit measurement, such as time, workload, power consumption amount, and/or temperature level.
A multicore manager 312 may receive a signal 324 having the identified processor core information from the optimization engine 310. The multicore manager 312 may control an activity state for each processor core 302, thereby controlling how many and/or which processor cores 302 are active/inactive for the unit measurement. In an aspect, the multicore manager 312 may signal the multicore IC 300 or the individual processor cores 302 with a state signal 326 that induces an active state and/or an inactive state in a particular or a group of processor cores 302. In an aspect, the multicore manager 312 controls or interacts with a scheduler (not shown) to schedule processes only for processor cores 302 deemed to be active by the optimization engine 310. In another aspect, the multicore manager 312 controls or interacts with the scheduler to schedule processes for the active processor cores 302 and to avoid scheduling processes for processor cores 302 deemed to be inactive by the optimization engine 310.
In an aspect, a multicore device may have one or more multicore ICs 300. The multicore device may further include one or more of each of the workload analyzer 306, the real-time multicore power model 308, the optimization engine 310, and the multicore manager 312. Each of these components may be paired with one or more multicore ICs 300.
The workload analyzer 306, the real-time multicore power model 308, the optimization engine 310, and the multicore manager 312 may each be implemented as software stored on a memory (see
A graphical representation of a second exemplary power map 402 is also for a typical type multicore IC, but with a heavy work load (e.g. a high MIPS number). In this instance, the exemplary multicore IC used to generate this second exemplary power map may need two to four processor cores to handle the workload. An arrow 410 in this case indicates that at approximately 120 degrees Celsius, using three active processor cores results in the lowest power consumption, while still being able to handle the designated workload.
A graphical representation of a third exemplary power map 404 differs from the previous two graphical representations 400, 402, because it is for a slow type multicore IC, but uses the same workload as the graphical representation of the first exemplary power map 400. In this example, one to four processor cores may handle the workload, and an arrow 412 indicates that using two active processor cores results in the lowest power consumption for handling the workload at approximately 110 degrees Celsius.
A graphical representation of a fourth exemplary power map 406 is for a slow type multicore IC, but uses the same heavy workload as the graphical representation of the second exemplary power map 402. In this example, two to four processor cores may handle the workload, and an arrow 414 indicates that using four active processor cores results in the lowest power consumption for handling the workload at approximately 110 degrees Celsius.
A graphical representation of a second exemplary performance map 502 is also for a typical type multicore IC, having two to four processor cores able to handle the variable workloads. An arrow 506 in this case indicates that using four active processor cores results in the best performance of X4 MIPS at a power budget of P5 mW, while three active processor cores can handle fewer MIPS and two active cores can handle even fewer MIPS at approximately the same power budget.
In block 602 the multicore device may read the static information associated with some or all of the processor cores of the multicore device. The static information of the processor cores may be processor core information that is constant, such as the leakage, the PVS (processor voltage scaling) table, and the part type or Si speed. In block 604 the multicore device may read dynamic information associated the with processor cores of the multicore device. The dynamic information may vary over time, and may include the temperature readings and workloads of the processor cores. In block 606 the multicore device may convert the current workload reading to a representative workload value. For example, the workload may be represented by MIPS, processor utilization, operating clock frequency, or some performance counter value.
In determination block 608 the multicore device may determine a relationship of the temperature readings to a temperature threshold by comparing the temperature readings to the temperature threshold. The determination of this relationship may be made in various ways. The multicore device may compare the temperature readings of each processor core and the temperature threshold. The determination may be made on a processor core by processor core basis, and an overall determination may be made by a majority rule. For example, when the majority of processor core temperature readings are less than the temperature threshold, the entire group of processor cores is treated as having temperature readings below the threshold for the purposes of the determination in determination block 608. In an aspect, each processor core may be treated separately for the purposes of the determination in determination block 608. A further aspect may use a mean or median temperature of the group of processor cores to compare with the temperature threshold and treat the processor cores as a group for the purposes of the determination in determination block 608.
Depending on the determined relationship(s), the multicore device may calculate power maps or performance maps. When the determination in determination block 608 is that the temperature readings for the processor cores, either as a group or individually, are greater than the temperature threshold, in block 610 the multicore device may calculate a performance map to be used to achieve the optimal or best performance for the given power budget. In an aspect, when the temperature readings are equal to the threshold, the multicore device may calculate the performance map in block 610. In block 612 the multicore device may identify the configuration of processor cores that may optimize the performance for the given power budget. In an aspect, the configuration may include the number of active/inactive processor cores and/or which active/inactive processor cores may optimize the performance for the given power budget. In block 618 the multicore device may control the activity state of the processor cores, thereby controlling the number and/or which processor cores are active and/or inactive to execute the workload within the parameters of achieving the best performance for the given power budget.
When the determination in determination block 608 is that the temperature readings for the processor cores, either as a group or individually, are less than the temperature threshold, in block 614 the multicore device may calculate a power map to be used to achieve the optimal or lowest power for the given workload. In an aspect, when the temperature readings are equal to the threshold the multicore device may calculate the power map in block 614. In block 616 the multicore device may identify the configuration of processor cores that may optimize power for the given workload. In an aspect, the configuration may include the number of active/inactive processor cores and/or which active/inactive processor cores may optimize power for the given workload. In block 618 the multicore device may control the activity state of the processor cores, thereby controlling the number and/or which processor cores are active and/or inactive to execute the workload within the parameters of achieving the lowest power for the given workload.
The multicore device may repeatedly perform the intelligent multicore control method 600 for each workload of processes to be executed. In an aspect, it may be unnecessary to repeat block 602 since the static information may be unchanging. In such cases, the multicore device may repeat the intelligent multicore control method 600 from block 604 by reading the dynamic information of the processor cores.
The various aspects may be implemented in modular shader processor/texture pipe units. This architecture allows for the creation of GPU variations that may vary in shader and texture processing capabilities. Shader processing is just one of many steps in the graphics processing performed by GPUs, and thus the discussions above regarding shader processor/texture pipe units addresses only a portion of the complete working core. Shader processor/texture pipe units may be driven purely by the preceding hardware blocks, and may not be individually controlled from software. However, future computing system architectures may permit shader processor/texture pipe units to be controlled from software.
The foregoing method descriptions and the process flow diagrams are provided merely as illustrative examples and are not intended to require or imply that the steps of the various aspects must be performed in the order presented. As will be appreciated by one of skill in the art the order of steps in the foregoing aspects may be performed in any order. Words such as “thereafter,” “then,” “next,” etc. are not intended to limit the order of the steps; these words are simply used to guide the reader through the description of the methods. Further, any reference to claim elements in the singular, for example, using the articles “a,” “an” or “the” is not to be construed as limiting the element to the singular.
As used in this application, the terms “component,” “module,” “system,” “engine,” “generator,” “manager” and the like are intended to include a computer-related entity, such as, but not limited to, hardware, firmware, a combination of hardware and software, software, or software in execution, which are configured to perform particular operations or functions. For example, a component may be, but is not limited to, a process running on a processor, a processor, an object, an executable, a thread of execution, a program, and/or a computer. By way of illustration, both an application running on a computing device and the computing device may be referred to as a component. One or more components may reside within a process and/or thread of execution and a component may be localized on one processor or core and/or distributed between two or more processors or cores. In addition, these components may execute from various non-transitory computer readable media having various instructions and/or data structures stored thereon. Components may communicate by way of local and/or remote processes, function or procedure calls, electronic signals, data packets, memory read/writes, and other known network, computer, processor, and/or process related communication methodologies.
The various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the aspects disclosed herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The hardware used to implement the various illustrative logics, logical blocks, modules, and circuits described in connection with the aspects disclosed herein may be implemented or performed with a general purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic circuit, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general-purpose processor may be a multiprocessor, but, in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a combination of a DSP and a multiprocessor, a plurality of multiprocessors, one or more multiprocessors in conjunction with a DSP core, or any other such configuration. Alternatively, some steps or methods may be performed by circuitry that is specific to a given function.
In one or more exemplary aspects, the functions described may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions may be stored as one or more instructions or code on a non-transitory computer-readable medium or non-transitory processor-readable medium. The steps of a method or algorithm disclosed herein may be embodied in a processor-executable software module which may reside on a non-transitory computer-readable or processor-readable storage medium. Non-transitory computer-readable or processor-readable storage media may be any storage media that may be accessed by a computer or a processor. By way of example but not limitation, such non-transitory computer-readable or processor-readable media may include RAM, ROM, EEPROM, FLASH memory, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that may be used to store desired program code in the form of instructions or data structures and that may be accessed by a computer. Disk and disc, as used herein, includes compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk, and blu-ray disc where disks usually reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above are also included within the scope of non-transitory computer-readable and processor-readable media. Additionally, the operations of a method or algorithm may reside as one or any combination or set of codes and/or instructions on a non-transitory processor-readable medium and/or computer-readable medium, which may be incorporated into a computer program product.
The preceding description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other aspects without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the aspects shown herein but is to be accorded the widest scope consistent with the following claims and the principles and novel features disclosed herein.
This application claims the benefit of priority to U.S. Provisional Patent Application No. 61/863,554 entitled “Intelligent Multicore Control For Optimal Performance Per Watt” filed Aug. 8, 2013, the entire contents of which are hereby incorporated by reference.
| Number | Name | Date | Kind |
|---|---|---|---|
| 6804632 | Orenstien et al. | Oct 2004 | B2 |
| 8180997 | Burger et al. | May 2012 | B2 |
| 20080244227 | Gee et al. | Oct 2008 | A1 |
| 20090309243 | Carmack et al. | Dec 2009 | A1 |
| 20120144217 | Sistla et al. | Jun 2012 | A1 |
| 20120266179 | Osborn | Oct 2012 | A1 |
| 20130132972 | Sur et al. | May 2013 | A1 |
| 20130155081 | Khodorkovsky et al. | Jun 2013 | A1 |
| 20140229750 | Bhandaru et al. | Aug 2014 | A1 |
| Entry |
|---|
| Li J., et al., “Dynamic Power-Performance Adaptation of Parallel Computation on Chip Multiprocessors,” The Twelfth International Symposium on High-Performance Computer Architecture, 2006, pp. 77-87. |
| Li S., et al., “McPAT: An Integrated Power, Area, and Timing Modeling Framework for Multicore and Manycore Architectures,” 42nd Annual IEEE/ACM International Symposium on Microarchitecture, 2009, pp. 469-480. |
| Nathuji R., et al., “VirtualPower: Coordinated Power Management in Virtualized Enterprise Systems,” In Proceedings of twenty-first ACM SIGOPS symposium on Operating systems principles, vol. 41, Oct. 2007, pp. 265-278. |
| Nowroz A.N. et al., “Thermal monitoring of real processors: Techniques for sensor allocation and full Characterization”, Design Automation Conference (DAC), 2010 47th ACM/IEEE. Publication Date: Jun. 13-18, 2010, pp. 56-61. ISSN: 0738-100X. |
| International Search Report and Written Opinion—PCT/US2014/050230—ISA/EPO—Oct. 23, 2014. |
| Number | Date | Country | |
|---|---|---|---|
| 20150046685 A1 | Feb 2015 | US |
| Number | Date | Country | |
|---|---|---|---|
| 61863554 | Aug 2013 | US |
