mirror of https://gitee.com/openkylin/linux.git
198 lines
8.6 KiB
Plaintext
198 lines
8.6 KiB
Plaintext
CPU cooling APIs How To
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===================================
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Written by Amit Daniel Kachhap <amit.kachhap@linaro.org>
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Updated: 6 Jan 2015
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Copyright (c) 2012 Samsung Electronics Co., Ltd(http://www.samsung.com)
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0. Introduction
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The generic cpu cooling(freq clipping) provides registration/unregistration APIs
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to the caller. The binding of the cooling devices to the trip point is left for
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the user. The registration APIs returns the cooling device pointer.
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1. cpu cooling APIs
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1.1 cpufreq registration/unregistration APIs
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1.1.1 struct thermal_cooling_device *cpufreq_cooling_register(
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struct cpumask *clip_cpus)
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This interface function registers the cpufreq cooling device with the name
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"thermal-cpufreq-%x". This api can support multiple instances of cpufreq
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cooling devices.
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clip_cpus: cpumask of cpus where the frequency constraints will happen.
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1.1.2 struct thermal_cooling_device *of_cpufreq_cooling_register(
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struct device_node *np, const struct cpumask *clip_cpus)
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This interface function registers the cpufreq cooling device with
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the name "thermal-cpufreq-%x" linking it with a device tree node, in
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order to bind it via the thermal DT code. This api can support multiple
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instances of cpufreq cooling devices.
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np: pointer to the cooling device device tree node
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clip_cpus: cpumask of cpus where the frequency constraints will happen.
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1.1.3 struct thermal_cooling_device *cpufreq_power_cooling_register(
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const struct cpumask *clip_cpus, u32 capacitance,
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get_static_t plat_static_func)
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Similar to cpufreq_cooling_register, this function registers a cpufreq
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cooling device. Using this function, the cooling device will
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implement the power extensions by using a simple cpu power model. The
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cpus must have registered their OPPs using the OPP library.
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The additional parameters are needed for the power model (See 2. Power
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models). "capacitance" is the dynamic power coefficient (See 2.1
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Dynamic power). "plat_static_func" is a function to calculate the
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static power consumed by these cpus (See 2.2 Static power).
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1.1.4 struct thermal_cooling_device *of_cpufreq_power_cooling_register(
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struct device_node *np, const struct cpumask *clip_cpus, u32 capacitance,
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get_static_t plat_static_func)
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Similar to cpufreq_power_cooling_register, this function register a
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cpufreq cooling device with power extensions using the device tree
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information supplied by the np parameter.
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1.1.5 void cpufreq_cooling_unregister(struct thermal_cooling_device *cdev)
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This interface function unregisters the "thermal-cpufreq-%x" cooling device.
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cdev: Cooling device pointer which has to be unregistered.
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2. Power models
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The power API registration functions provide a simple power model for
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CPUs. The current power is calculated as dynamic + (optionally)
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static power. This power model requires that the operating-points of
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the CPUs are registered using the kernel's opp library and the
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`cpufreq_frequency_table` is assigned to the `struct device` of the
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cpu. If you are using CONFIG_CPUFREQ_DT then the
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`cpufreq_frequency_table` should already be assigned to the cpu
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device.
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The `plat_static_func` parameter of `cpufreq_power_cooling_register()`
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and `of_cpufreq_power_cooling_register()` is optional. If you don't
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provide it, only dynamic power will be considered.
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2.1 Dynamic power
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The dynamic power consumption of a processor depends on many factors.
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For a given processor implementation the primary factors are:
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- The time the processor spends running, consuming dynamic power, as
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compared to the time in idle states where dynamic consumption is
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negligible. Herein we refer to this as 'utilisation'.
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- The voltage and frequency levels as a result of DVFS. The DVFS
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level is a dominant factor governing power consumption.
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- In running time the 'execution' behaviour (instruction types, memory
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access patterns and so forth) causes, in most cases, a second order
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variation. In pathological cases this variation can be significant,
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but typically it is of a much lesser impact than the factors above.
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A high level dynamic power consumption model may then be represented as:
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Pdyn = f(run) * Voltage^2 * Frequency * Utilisation
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f(run) here represents the described execution behaviour and its
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result has a units of Watts/Hz/Volt^2 (this often expressed in
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mW/MHz/uVolt^2)
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The detailed behaviour for f(run) could be modelled on-line. However,
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in practice, such an on-line model has dependencies on a number of
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implementation specific processor support and characterisation
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factors. Therefore, in initial implementation that contribution is
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represented as a constant coefficient. This is a simplification
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consistent with the relative contribution to overall power variation.
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In this simplified representation our model becomes:
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Pdyn = Capacitance * Voltage^2 * Frequency * Utilisation
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Where `capacitance` is a constant that represents an indicative
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running time dynamic power coefficient in fundamental units of
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mW/MHz/uVolt^2. Typical values for mobile CPUs might lie in range
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from 100 to 500. For reference, the approximate values for the SoC in
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ARM's Juno Development Platform are 530 for the Cortex-A57 cluster and
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140 for the Cortex-A53 cluster.
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2.2 Static power
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Static leakage power consumption depends on a number of factors. For a
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given circuit implementation the primary factors are:
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- Time the circuit spends in each 'power state'
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- Temperature
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- Operating voltage
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- Process grade
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The time the circuit spends in each 'power state' for a given
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evaluation period at first order means OFF or ON. However,
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'retention' states can also be supported that reduce power during
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inactive periods without loss of context.
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Note: The visibility of state entries to the OS can vary, according to
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platform specifics, and this can then impact the accuracy of a model
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based on OS state information alone. It might be possible in some
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cases to extract more accurate information from system resources.
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The temperature, operating voltage and process 'grade' (slow to fast)
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of the circuit are all significant factors in static leakage power
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consumption. All of these have complex relationships to static power.
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Circuit implementation specific factors include the chosen silicon
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process as well as the type, number and size of transistors in both
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the logic gates and any RAM elements included.
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The static power consumption modelling must take into account the
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power managed regions that are implemented. Taking the example of an
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ARM processor cluster, the modelling would take into account whether
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each CPU can be powered OFF separately or if only a single power
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region is implemented for the complete cluster.
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In one view, there are others, a static power consumption model can
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then start from a set of reference values for each power managed
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region (e.g. CPU, Cluster/L2) in each state (e.g. ON, OFF) at an
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arbitrary process grade, voltage and temperature point. These values
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are then scaled for all of the following: the time in each state, the
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process grade, the current temperature and the operating voltage.
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However, since both implementation specific and complex relationships
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dominate the estimate, the appropriate interface to the model from the
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cpu cooling device is to provide a function callback that calculates
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the static power in this platform. When registering the cpu cooling
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device pass a function pointer that follows the `get_static_t`
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prototype:
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int plat_get_static(cpumask_t *cpumask, int interval,
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unsigned long voltage, u32 &power);
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`cpumask` is the cpumask of the cpus involved in the calculation.
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`voltage` is the voltage at which they are operating. The function
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should calculate the average static power for the last `interval`
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milliseconds. It returns 0 on success, -E* on error. If it
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succeeds, it should store the static power in `power`. Reading the
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temperature of the cpus described by `cpumask` is left for
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plat_get_static() to do as the platform knows best which thermal
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sensor is closest to the cpu.
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If `plat_static_func` is NULL, static power is considered to be
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negligible for this platform and only dynamic power is considered.
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The platform specific callback can then use any combination of tables
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and/or equations to permute the estimated value. Process grade
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information is not passed to the model since access to such data, from
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on-chip measurement capability or manufacture time data, is platform
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specific.
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Note: the significance of static power for CPUs in comparison to
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dynamic power is highly dependent on implementation. Given the
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potential complexity in implementation, the importance and accuracy of
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its inclusion when using cpu cooling devices should be assessed on a
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case by case basis.
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