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Commit 0db9723c authored by Linus Torvalds's avatar Linus Torvalds
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Pull thermal management updates from Zhang Rui:
 "Specifics:

   - enhance Thermal Framework with several new capabilities:

       * use power estimates
       * compute weights with relative integers instead of percentages
       * allow governors to have private data in thermal zones
       * export thermal zone parameters through sysfs

     Thanks to the ARM thermal team (Javi, Punit, KP).

   - introduce a new thermal governor: power allocator.  First in kernel
     closed loop PI(D) controller for thermal control.  Thanks to ARM
     thermal team.

   - enhance OF thermal to allow thermal zones to have sustainable power
     HW specification.  Thanks to Punit.

   - introduce thermal driver for Intel Quark SoC x1000platform.  Thanks
     to Ong, Boon Leong.

   - introduce QPNP PMIC temperature alarm driver.  Thanks to Ivan T. I.

   - introduce thermal driver for Hisilicon hi6220.  Thanks to
     kongxinwei.

   - enhance Exynos thermal driver to handle Exynos5433 TMU.  Thanks to
     Chanwoo C.

   - TI thermal driver now has a better implementation for EOCZ bit.
     From Pavel M.

   - add id for Skylake processors in int340x processor thermal driver.

   - a couple of small fixes and cleanups."

* 'next' of git://git.kernel.org/pub/scm/linux/kernel/git/rzhang/linux: (36 commits)
  thermal: hisilicon: add new hisilicon thermal sensor driver
  dt-bindings: Document the hi6220 thermal sensor bindings
  thermal: of-thermal: add support for reading coefficients property
  thermal: support slope and offset coefficients
  thermal: power_allocator: round the division when divvying up power
  thermal: exynos: Add the support for Exynos5433 TMU
  thermal: cpu_cooling: Fix power calculation when CPUs are offline
  thermal: cpu_cooling: Remove cpu_dev update on policy CPU update
  thermal: export thermal_zone_parameters to sysfs
  thermal: cpu_cooling: Check memory allocation of power_table
  ti-soc-thermal: request temperature periodically if hw can't do that itself
  ti-soc-thermal: implement eocz bit to make driver useful on omap3
  cleanup ti-soc-thermal
  thermal: remove stale THERMAL_POWER_ACTOR select
  thermal: Default OF created trip points to writable
  thermal: core: Add Kconfig option to enable writable trips
  thermal: x86_pkg_temp: drop const for thermal_zone_parameters
  of: thermal: Introduce sustainable power for a thermal zone
  thermal: add trace events to the power allocator governor
  thermal: introduce the Power Allocator governor
  ...
parents 4570a371 111b23cf
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* Temperature Sensor on hisilicon SoCs

** Required properties :

- compatible: "hisilicon,tsensor".
- reg: physical base address of thermal sensor and length of memory mapped
  region.
- interrupt: The interrupt number to the cpu. Defines the interrupt used
  by /SOCTHERM/tsensor.
- clock-names: Input clock name, should be 'thermal_clk'.
- clocks: phandles for clock specified in "clock-names" property.
- #thermal-sensor-cells: Should be 1. See ./thermal.txt for a description.

Example :

	tsensor: tsensor@0,f7030700 {
		compatible = "hisilicon,tsensor";
		reg = <0x0 0xf7030700 0x0 0x1000>;
		interrupts = <0 7 0x4>;
		clocks = <&sys_ctrl HI6220_TSENSOR_CLK>;
		clock-names = "thermal_clk";
		#thermal-sensor-cells = <1>;
	}
+57 −0
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Qualcomm QPNP PMIC Temperature Alarm

QPNP temperature alarm peripherals are found inside of Qualcomm PMIC chips
that utilize the Qualcomm SPMI implementation. These peripherals provide an
interrupt signal and status register to identify high PMIC die temperature.

Required properties:
- compatible:      Should contain "qcom,spmi-temp-alarm".
- reg:             Specifies the SPMI address and length of the controller's
                   registers.
- interrupts:      PMIC temperature alarm interrupt.
- #thermal-sensor-cells: Should be 0. See thermal.txt for a description.

Optional properties:
- io-channels:     Should contain IIO channel specifier for the ADC channel,
                   which report chip die temperature.
- io-channel-names: Should contain "thermal".

Example:

	pm8941_temp: thermal-alarm@2400 {
		compatible = "qcom,spmi-temp-alarm";
		reg = <0x2400 0x100>;
		interrupts = <0 0x24 0 IRQ_TYPE_EDGE_RISING>;
		#thermal-sensor-cells = <0>;

		io-channels = <&pm8941_vadc VADC_DIE_TEMP>;
		io-channel-names = "thermal";
	};

	thermal-zones {
		pm8941 {
			polling-delay-passive = <250>;
			polling-delay = <1000>;

			thermal-sensors = <&pm8941_temp>;

			trips {
				passive {
					temperature = <1050000>;
					hysteresis = <2000>;
					type = "passive";
				};
				alert {
					temperature = <125000>;
					hysteresis = <2000>;
					type = "hot";
				};
				crit {
					temperature = <145000>;
					hysteresis = <2000>;
					type = "critical";
				};
			};
		};
	};
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@@ -167,6 +167,13 @@ Optional property:
			by means of sensor ID. Additional coefficients are
			interpreted as constant offset.

- sustainable-power:	An estimate of the sustainable power (in mW) that the
  Type: unsigned	thermal zone can dissipate at the desired
  Size: one cell	control temperature.  For reference, the
			sustainable power of a 4'' phone is typically
			2000mW, while on a 10'' tablet is around
			4500mW.

Note: The delay properties are bound to the maximum dT/dt (temperature
derivative over time) in two situations for a thermal zone:
(i)  - when passive cooling is activated (polling-delay-passive); and
@@ -546,6 +553,8 @@ thermal-zones {
		 */
		coefficients =		<1200	-345	890>;

		sustainable-power = <2500>;

		trips {
			/* Trips are based on resulting linear equation */
			cpu_trip: cpu-trip {
+155 −1
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@@ -36,8 +36,162 @@ the user. The registration APIs returns the cooling device pointer.
    np: pointer to the cooling device device tree node
    clip_cpus: cpumask of cpus where the frequency constraints will happen.

1.1.3 void cpufreq_cooling_unregister(struct thermal_cooling_device *cdev)
1.1.3 struct thermal_cooling_device *cpufreq_power_cooling_register(
    const struct cpumask *clip_cpus, u32 capacitance,
    get_static_t plat_static_func)

Similar to cpufreq_cooling_register, this function registers a cpufreq
cooling device.  Using this function, the cooling device will
implement the power extensions by using a simple cpu power model.  The
cpus must have registered their OPPs using the OPP library.

The additional parameters are needed for the power model (See 2. Power
models).  "capacitance" is the dynamic power coefficient (See 2.1
Dynamic power).  "plat_static_func" is a function to calculate the
static power consumed by these cpus (See 2.2 Static power).

1.1.4 struct thermal_cooling_device *of_cpufreq_power_cooling_register(
    struct device_node *np, const struct cpumask *clip_cpus, u32 capacitance,
    get_static_t plat_static_func)

Similar to cpufreq_power_cooling_register, this function register a
cpufreq cooling device with power extensions using the device tree
information supplied by the np parameter.

1.1.5 void cpufreq_cooling_unregister(struct thermal_cooling_device *cdev)

    This interface function unregisters the "thermal-cpufreq-%x" cooling device.

    cdev: Cooling device pointer which has to be unregistered.

2. Power models

The power API registration functions provide a simple power model for
CPUs.  The current power is calculated as dynamic + (optionally)
static power.  This power model requires that the operating-points of
the CPUs are registered using the kernel's opp library and the
`cpufreq_frequency_table` is assigned to the `struct device` of the
cpu.  If you are using CONFIG_CPUFREQ_DT then the
`cpufreq_frequency_table` should already be assigned to the cpu
device.

The `plat_static_func` parameter of `cpufreq_power_cooling_register()`
and `of_cpufreq_power_cooling_register()` is optional.  If you don't
provide it, only dynamic power will be considered.

2.1 Dynamic power

The dynamic power consumption of a processor depends on many factors.
For a given processor implementation the primary factors are:

- The time the processor spends running, consuming dynamic power, as
  compared to the time in idle states where dynamic consumption is
  negligible.  Herein we refer to this as 'utilisation'.
- The voltage and frequency levels as a result of DVFS.  The DVFS
  level is a dominant factor governing power consumption.
- In running time the 'execution' behaviour (instruction types, memory
  access patterns and so forth) causes, in most cases, a second order
  variation.  In pathological cases this variation can be significant,
  but typically it is of a much lesser impact than the factors above.

A high level dynamic power consumption model may then be represented as:

Pdyn = f(run) * Voltage^2 * Frequency * Utilisation

f(run) here represents the described execution behaviour and its
result has a units of Watts/Hz/Volt^2 (this often expressed in
mW/MHz/uVolt^2)

The detailed behaviour for f(run) could be modelled on-line.  However,
in practice, such an on-line model has dependencies on a number of
implementation specific processor support and characterisation
factors.  Therefore, in initial implementation that contribution is
represented as a constant coefficient.  This is a simplification
consistent with the relative contribution to overall power variation.

In this simplified representation our model becomes:

Pdyn = Capacitance * Voltage^2 * Frequency * Utilisation

Where `capacitance` is a constant that represents an indicative
running time dynamic power coefficient in fundamental units of
mW/MHz/uVolt^2.  Typical values for mobile CPUs might lie in range
from 100 to 500.  For reference, the approximate values for the SoC in
ARM's Juno Development Platform are 530 for the Cortex-A57 cluster and
140 for the Cortex-A53 cluster.


2.2 Static power

Static leakage power consumption depends on a number of factors.  For a
given circuit implementation the primary factors are:

- Time the circuit spends in each 'power state'
- Temperature
- Operating voltage
- Process grade

The time the circuit spends in each 'power state' for a given
evaluation period at first order means OFF or ON.  However,
'retention' states can also be supported that reduce power during
inactive periods without loss of context.

Note: The visibility of state entries to the OS can vary, according to
platform specifics, and this can then impact the accuracy of a model
based on OS state information alone.  It might be possible in some
cases to extract more accurate information from system resources.

The temperature, operating voltage and process 'grade' (slow to fast)
of the circuit are all significant factors in static leakage power
consumption.  All of these have complex relationships to static power.

Circuit implementation specific factors include the chosen silicon
process as well as the type, number and size of transistors in both
the logic gates and any RAM elements included.

The static power consumption modelling must take into account the
power managed regions that are implemented.  Taking the example of an
ARM processor cluster, the modelling would take into account whether
each CPU can be powered OFF separately or if only a single power
region is implemented for the complete cluster.

In one view, there are others, a static power consumption model can
then start from a set of reference values for each power managed
region (e.g. CPU, Cluster/L2) in each state (e.g. ON, OFF) at an
arbitrary process grade, voltage and temperature point.  These values
are then scaled for all of the following: the time in each state, the
process grade, the current temperature and the operating voltage.
However, since both implementation specific and complex relationships
dominate the estimate, the appropriate interface to the model from the
cpu cooling device is to provide a function callback that calculates
the static power in this platform.  When registering the cpu cooling
device pass a function pointer that follows the `get_static_t`
prototype:

    int plat_get_static(cpumask_t *cpumask, int interval,
                        unsigned long voltage, u32 &power);

`cpumask` is the cpumask of the cpus involved in the calculation.
`voltage` is the voltage at which they are operating.  The function
should calculate the average static power for the last `interval`
milliseconds.  It returns 0 on success, -E* on error.  If it
succeeds, it should store the static power in `power`.  Reading the
temperature of the cpus described by `cpumask` is left for
plat_get_static() to do as the platform knows best which thermal
sensor is closest to the cpu.

If `plat_static_func` is NULL, static power is considered to be
negligible for this platform and only dynamic power is considered.

The platform specific callback can then use any combination of tables
and/or equations to permute the estimated value.  Process grade
information is not passed to the model since access to such data, from
on-chip measurement capability or manufacture time data, is platform
specific.

Note: the significance of static power for CPUs in comparison to
dynamic power is highly dependent on implementation.  Given the
potential complexity in implementation, the importance and accuracy of
its inclusion when using cpu cooling devices should be assessed on a
case by case basis.
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Power allocator governor tunables
=================================

Trip points
-----------

The governor requires the following two passive trip points:

1.  "switch on" trip point: temperature above which the governor
    control loop starts operating.  This is the first passive trip
    point of the thermal zone.

2.  "desired temperature" trip point: it should be higher than the
    "switch on" trip point.  This the target temperature the governor
    is controlling for.  This is the last passive trip point of the
    thermal zone.

PID Controller
--------------

The power allocator governor implements a
Proportional-Integral-Derivative controller (PID controller) with
temperature as the control input and power as the controlled output:

    P_max = k_p * e + k_i * err_integral + k_d * diff_err + sustainable_power

where
    e = desired_temperature - current_temperature
    err_integral is the sum of previous errors
    diff_err = e - previous_error

It is similar to the one depicted below:

                                      k_d
                                       |
current_temp                           |
     |                                 v
     |                +----------+   +---+
     |         +----->| diff_err |-->| X |------+
     |         |      +----------+   +---+      |
     |         |                                |      tdp        actor
     |         |                      k_i       |       |  get_requested_power()
     |         |                       |        |       |        |     |
     |         |                       |        |       |        |     | ...
     v         |                       v        v       v        v     v
   +---+       |      +-------+      +---+    +---+   +---+   +----------+
   | S |-------+----->| sum e |----->| X |--->| S |-->| S |-->|power     |
   +---+       |      +-------+      +---+    +---+   +---+   |allocation|
     ^         |                                ^             +----------+
     |         |                                |                |     |
     |         |        +---+                   |                |     |
     |         +------->| X |-------------------+                v     v
     |                  +---+                               granted performance
desired_temperature       ^
                          |
                          |
                      k_po/k_pu

Sustainable power
-----------------

An estimate of the sustainable dissipatable power (in mW) should be
provided while registering the thermal zone.  This estimates the
sustained power that can be dissipated at the desired control
temperature.  This is the maximum sustained power for allocation at
the desired maximum temperature.  The actual sustained power can vary
for a number of reasons.  The closed loop controller will take care of
variations such as environmental conditions, and some factors related
to the speed-grade of the silicon.  `sustainable_power` is therefore
simply an estimate, and may be tuned to affect the aggressiveness of
the thermal ramp. For reference, the sustainable power of a 4" phone
is typically 2000mW, while on a 10" tablet is around 4500mW (may vary
depending on screen size).

If you are using device tree, do add it as a property of the
thermal-zone.  For example:

	thermal-zones {
		soc_thermal {
			polling-delay = <1000>;
			polling-delay-passive = <100>;
			sustainable-power = <2500>;
			...

Instead, if the thermal zone is registered from the platform code, pass a
`thermal_zone_params` that has a `sustainable_power`.  If no
`thermal_zone_params` were being passed, then something like below
will suffice:

	static const struct thermal_zone_params tz_params = {
		.sustainable_power = 3500,
	};

and then pass `tz_params` as the 5th parameter to
`thermal_zone_device_register()`

k_po and k_pu
-------------

The implementation of the PID controller in the power allocator
thermal governor allows the configuration of two proportional term
constants: `k_po` and `k_pu`.  `k_po` is the proportional term
constant during temperature overshoot periods (current temperature is
above "desired temperature" trip point).  Conversely, `k_pu` is the
proportional term constant during temperature undershoot periods
(current temperature below "desired temperature" trip point).

These controls are intended as the primary mechanism for configuring
the permitted thermal "ramp" of the system.  For instance, a lower
`k_pu` value will provide a slower ramp, at the cost of capping
available capacity at a low temperature.  On the other hand, a high
value of `k_pu` will result in the governor granting very high power
whilst temperature is low, and may lead to temperature overshooting.

The default value for `k_pu` is:

    2 * sustainable_power / (desired_temperature - switch_on_temp)

This means that at `switch_on_temp` the output of the controller's
proportional term will be 2 * `sustainable_power`.  The default value
for `k_po` is:

    sustainable_power / (desired_temperature - switch_on_temp)

Focusing on the proportional and feed forward values of the PID
controller equation we have:

    P_max = k_p * e + sustainable_power

The proportional term is proportional to the difference between the
desired temperature and the current one.  When the current temperature
is the desired one, then the proportional component is zero and
`P_max` = `sustainable_power`.  That is, the system should operate in
thermal equilibrium under constant load.  `sustainable_power` is only
an estimate, which is the reason for closed-loop control such as this.

Expanding `k_pu` we get:
    P_max = 2 * sustainable_power * (T_set - T) / (T_set - T_on) +
        sustainable_power

where
    T_set is the desired temperature
    T is the current temperature
    T_on is the switch on temperature

When the current temperature is the switch_on temperature, the above
formula becomes:

    P_max = 2 * sustainable_power * (T_set - T_on) / (T_set - T_on) +
        sustainable_power = 2 * sustainable_power + sustainable_power =
        3 * sustainable_power

Therefore, the proportional term alone linearly decreases power from
3 * `sustainable_power` to `sustainable_power` as the temperature
rises from the switch on temperature to the desired temperature.

k_i and integral_cutoff
-----------------------

`k_i` configures the PID loop's integral term constant.  This term
allows the PID controller to compensate for long term drift and for
the quantized nature of the output control: cooling devices can't set
the exact power that the governor requests.  When the temperature
error is below `integral_cutoff`, errors are accumulated in the
integral term.  This term is then multiplied by `k_i` and the result
added to the output of the controller.  Typically `k_i` is set low (1
or 2) and `integral_cutoff` is 0.

k_d
---

`k_d` configures the PID loop's derivative term constant.  It's
recommended to leave it as the default: 0.

Cooling device power API
========================

Cooling devices controlled by this governor must supply the additional
"power" API in their `cooling_device_ops`.  It consists on three ops:

1. int get_requested_power(struct thermal_cooling_device *cdev,
	struct thermal_zone_device *tz, u32 *power);
@cdev: The `struct thermal_cooling_device` pointer
@tz: thermal zone in which we are currently operating
@power: pointer in which to store the calculated power

`get_requested_power()` calculates the power requested by the device
in milliwatts and stores it in @power .  It should return 0 on
success, -E* on failure.  This is currently used by the power
allocator governor to calculate how much power to give to each cooling
device.

2. int state2power(struct thermal_cooling_device *cdev, struct
        thermal_zone_device *tz, unsigned long state, u32 *power);
@cdev: The `struct thermal_cooling_device` pointer
@tz: thermal zone in which we are currently operating
@state: A cooling device state
@power: pointer in which to store the equivalent power

Convert cooling device state @state into power consumption in
milliwatts and store it in @power.  It should return 0 on success, -E*
on failure.  This is currently used by thermal core to calculate the
maximum power that an actor can consume.

3. int power2state(struct thermal_cooling_device *cdev, u32 power,
	unsigned long *state);
@cdev: The `struct thermal_cooling_device` pointer
@power: power in milliwatts
@state: pointer in which to store the resulting state

Calculate a cooling device state that would make the device consume at
most @power mW and store it in @state.  It should return 0 on success,
-E* on failure.  This is currently used by the thermal core to convert
a given power set by the power allocator governor to a state that the
cooling device can set.  It is a function because this conversion may
depend on external factors that may change so this function should the
best conversion given "current circumstances".

Cooling device weights
----------------------

Weights are a mechanism to bias the allocation among cooling
devices.  They express the relative power efficiency of different
cooling devices.  Higher weight can be used to express higher power
efficiency.  Weighting is relative such that if each cooling device
has a weight of one they are considered equal.  This is particularly
useful in heterogeneous systems where two cooling devices may perform
the same kind of compute, but with different efficiency.  For example,
a system with two different types of processors.

If the thermal zone is registered using
`thermal_zone_device_register()` (i.e., platform code), then weights
are passed as part of the thermal zone's `thermal_bind_parameters`.
If the platform is registered using device tree, then they are passed
as the `contribution` property of each map in the `cooling-maps` node.

Limitations of the power allocator governor
===========================================

The power allocator governor's PID controller works best if there is a
periodic tick.  If you have a driver that calls
`thermal_zone_device_update()` (or anything that ends up calling the
governor's `throttle()` function) repetitively, the governor response
won't be very good.  Note that this is not particular to this
governor, step-wise will also misbehave if you call its throttle()
faster than the normal thermal framework tick (due to interrupts for
example) as it will overreact.
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