Release 4.7 drivers/cpuidle/governors/menu.c
  
  
/*
 * menu.c - the menu idle governor
 *
 * Copyright (C) 2006-2007 Adam Belay <abelay@novell.com>
 * Copyright (C) 2009 Intel Corporation
 * Author:
 *        Arjan van de Ven <arjan@linux.intel.com>
 *
 * This code is licenced under the GPL version 2 as described
 * in the COPYING file that acompanies the Linux Kernel.
 */
#include <linux/kernel.h>
#include <linux/cpuidle.h>
#include <linux/pm_qos.h>
#include <linux/time.h>
#include <linux/ktime.h>
#include <linux/hrtimer.h>
#include <linux/tick.h>
#include <linux/sched.h>
#include <linux/math64.h>
#include <linux/module.h>
/*
 * Please note when changing the tuning values:
 * If (MAX_INTERESTING-1) * RESOLUTION > UINT_MAX, the result of
 * a scaling operation multiplication may overflow on 32 bit platforms.
 * In that case, #define RESOLUTION as ULL to get 64 bit result:
 * #define RESOLUTION 1024ULL
 *
 * The default values do not overflow.
 */
#define BUCKETS 12
#define INTERVAL_SHIFT 3
#define INTERVALS (1UL << INTERVAL_SHIFT)
#define RESOLUTION 1024
#define DECAY 8
#define MAX_INTERESTING 50000
/*
 * Concepts and ideas behind the menu governor
 *
 * For the menu governor, there are 3 decision factors for picking a C
 * state:
 * 1) Energy break even point
 * 2) Performance impact
 * 3) Latency tolerance (from pmqos infrastructure)
 * These these three factors are treated independently.
 *
 * Energy break even point
 * -----------------------
 * C state entry and exit have an energy cost, and a certain amount of time in
 * the  C state is required to actually break even on this cost. CPUIDLE
 * provides us this duration in the "target_residency" field. So all that we
 * need is a good prediction of how long we'll be idle. Like the traditional
 * menu governor, we start with the actual known "next timer event" time.
 *
 * Since there are other source of wakeups (interrupts for example) than
 * the next timer event, this estimation is rather optimistic. To get a
 * more realistic estimate, a correction factor is applied to the estimate,
 * that is based on historic behavior. For example, if in the past the actual
 * duration always was 50% of the next timer tick, the correction factor will
 * be 0.5.
 *
 * menu uses a running average for this correction factor, however it uses a
 * set of factors, not just a single factor. This stems from the realization
 * that the ratio is dependent on the order of magnitude of the expected
 * duration; if we expect 500 milliseconds of idle time the likelihood of
 * getting an interrupt very early is much higher than if we expect 50 micro
 * seconds of idle time. A second independent factor that has big impact on
 * the actual factor is if there is (disk) IO outstanding or not.
 * (as a special twist, we consider every sleep longer than 50 milliseconds
 * as perfect; there are no power gains for sleeping longer than this)
 *
 * For these two reasons we keep an array of 12 independent factors, that gets
 * indexed based on the magnitude of the expected duration as well as the
 * "is IO outstanding" property.
 *
 * Repeatable-interval-detector
 * ----------------------------
 * There are some cases where "next timer" is a completely unusable predictor:
 * Those cases where the interval is fixed, for example due to hardware
 * interrupt mitigation, but also due to fixed transfer rate devices such as
 * mice.
 * For this, we use a different predictor: We track the duration of the last 8
 * intervals and if the stand deviation of these 8 intervals is below a
 * threshold value, we use the average of these intervals as prediction.
 *
 * Limiting Performance Impact
 * ---------------------------
 * C states, especially those with large exit latencies, can have a real
 * noticeable impact on workloads, which is not acceptable for most sysadmins,
 * and in addition, less performance has a power price of its own.
 *
 * As a general rule of thumb, menu assumes that the following heuristic
 * holds:
 *     The busier the system, the less impact of C states is acceptable
 *
 * This rule-of-thumb is implemented using a performance-multiplier:
 * If the exit latency times the performance multiplier is longer than
 * the predicted duration, the C state is not considered a candidate
 * for selection due to a too high performance impact. So the higher
 * this multiplier is, the longer we need to be idle to pick a deep C
 * state, and thus the less likely a busy CPU will hit such a deep
 * C state.
 *
 * Two factors are used in determing this multiplier:
 * a value of 10 is added for each point of "per cpu load average" we have.
 * a value of 5 points is added for each process that is waiting for
 * IO on this CPU.
 * (these values are experimentally determined)
 *
 * The load average factor gives a longer term (few seconds) input to the
 * decision, while the iowait value gives a cpu local instantanious input.
 * The iowait factor may look low, but realize that this is also already
 * represented in the system load average.
 *
 */
struct menu_device {
	
int		last_state_idx;
	
int             needs_update;
	
unsigned int	next_timer_us;
	
unsigned int	predicted_us;
	
unsigned int	bucket;
	
unsigned int	correction_factor[BUCKETS];
	
unsigned int	intervals[INTERVALS];
	
int		interval_ptr;
};
#define LOAD_INT(x) ((x) >> FSHIFT)
#define LOAD_FRAC(x) LOAD_INT(((x) & (FIXED_1-1)) * 100)
static inline int get_loadavg(unsigned long load)
{
	return LOAD_INT(load) * 10 + LOAD_FRAC(load) / 10;
}
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static inline int which_bucket(unsigned int duration, unsigned long nr_iowaiters)
{
	int bucket = 0;
	/*
         * We keep two groups of stats; one with no
         * IO pending, one without.
         * This allows us to calculate
         * E(duration)|iowait
         */
	if (nr_iowaiters)
		bucket = BUCKETS/2;
	if (duration < 10)
		return bucket;
	if (duration < 100)
		return bucket + 1;
	if (duration < 1000)
		return bucket + 2;
	if (duration < 10000)
		return bucket + 3;
	if (duration < 100000)
		return bucket + 4;
	return bucket + 5;
}
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 | Total | 89 | 100.00% | 2 | 100.00% | 
/*
 * Return a multiplier for the exit latency that is intended
 * to take performance requirements into account.
 * The more performance critical we estimate the system
 * to be, the higher this multiplier, and thus the higher
 * the barrier to go to an expensive C state.
 */
static inline int performance_multiplier(unsigned long nr_iowaiters, unsigned long load)
{
	int mult = 1;
	/* for higher loadavg, we are more reluctant */
	mult += 2 * get_loadavg(load);
	/* for IO wait tasks (per cpu!) we add 5x each */
	mult += 10 * nr_iowaiters;
	return mult;
}
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 | Total | 40 | 100.00% | 3 | 100.00% | 
static DEFINE_PER_CPU(struct menu_device, menu_devices);
static void menu_update(struct cpuidle_driver *drv, struct cpuidle_device *dev);
/*
 * Try detecting repeating patterns by keeping track of the last 8
 * intervals, and checking if the standard deviation of that set
 * of points is below a threshold. If it is... then use the
 * average of these 8 points as the estimated value.
 */
static unsigned int get_typical_interval(struct menu_device *data)
{
	int i, divisor;
	unsigned int max, thresh, avg;
	uint64_t sum, variance;
	thresh = UINT_MAX; /* Discard outliers above this value */
again:
	/* First calculate the average of past intervals */
	max = 0;
	sum = 0;
	divisor = 0;
	for (i = 0; i < INTERVALS; i++) {
		unsigned int value = data->intervals[i];
		if (value <= thresh) {
			sum += value;
			divisor++;
			if (value > max)
				max = value;
		}
	}
	if (divisor == INTERVALS)
		avg = sum >> INTERVAL_SHIFT;
	else
		avg = div_u64(sum, divisor);
	/* Then try to determine variance */
	variance = 0;
	for (i = 0; i < INTERVALS; i++) {
		unsigned int value = data->intervals[i];
		if (value <= thresh) {
			int64_t diff = (int64_t)value - avg;
			variance += diff * diff;
		}
	}
	if (divisor == INTERVALS)
		variance >>= INTERVAL_SHIFT;
	else
		do_div(variance, divisor);
	/*
         * The typical interval is obtained when standard deviation is
         * small (stddev <= 20 us, variance <= 400 us^2) or standard
         * deviation is small compared to the average interval (avg >
         * 6*stddev, avg^2 > 36*variance). The average is smaller than
         * UINT_MAX aka U32_MAX, so computing its square does not
         * overflow a u64. We simply reject this candidate average if
         * the standard deviation is greater than 715 s (which is
         * rather unlikely).
         *
         * Use this result only if there is no timer to wake us up sooner.
         */
	if (likely(variance <= U64_MAX/36)) {
		if ((((u64)avg*avg > variance*36) && (divisor * 4 >= INTERVALS * 3))
							|| variance <= 400) {
			return avg;
		}
	}
	/*
         * If we have outliers to the upside in our distribution, discard
         * those by setting the threshold to exclude these outliers, then
         * calculate the average and standard deviation again. Once we get
         * down to the bottom 3/4 of our samples, stop excluding samples.
         *
         * This can deal with workloads that have long pauses interspersed
         * with sporadic activity with a bunch of short pauses.
         */
	if ((divisor * 4) <= INTERVALS * 3)
		return UINT_MAX;
	thresh = max - 1;
	goto again;
}
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| rasmus villemoes | rasmus villemoes | 35 | 12.92% | 2 | 18.18% | 
| tuukka tikkanen | tuukka tikkanen | 34 | 12.55% | 4 | 36.36% | 
| mel gorman | mel gorman | 20 | 7.38% | 1 | 9.09% | 
| rik van riel | rik van riel | 7 | 2.58% | 1 | 9.09% | 
 | Total | 271 | 100.00% | 11 | 100.00% | 
/**
 * menu_select - selects the next idle state to enter
 * @drv: cpuidle driver containing state data
 * @dev: the CPU
 */
static int menu_select(struct cpuidle_driver *drv, struct cpuidle_device *dev)
{
	struct menu_device *data = this_cpu_ptr(&menu_devices);
	int latency_req = pm_qos_request(PM_QOS_CPU_DMA_LATENCY);
	int i;
	unsigned int interactivity_req;
	unsigned int expected_interval;
	unsigned long nr_iowaiters, cpu_load;
	if (data->needs_update) {
		menu_update(drv, dev);
		data->needs_update = 0;
	}
	/* Special case when user has set very strict latency requirement */
	if (unlikely(latency_req == 0))
		return 0;
	/* determine the expected residency time, round up */
	data->next_timer_us = ktime_to_us(tick_nohz_get_sleep_length());
	get_iowait_load(&nr_iowaiters, &cpu_load);
	data->bucket = which_bucket(data->next_timer_us, nr_iowaiters);
	/*
         * Force the result of multiplication to be 64 bits even if both
         * operands are 32 bits.
         * Make sure to round up for half microseconds.
         */
	data->predicted_us = DIV_ROUND_CLOSEST_ULL((uint64_t)data->next_timer_us *
					 data->correction_factor[data->bucket],
					 RESOLUTION * DECAY);
	expected_interval = get_typical_interval(data);
	expected_interval = min(expected_interval, data->next_timer_us);
	if (CPUIDLE_DRIVER_STATE_START > 0) {
		struct cpuidle_state *s = &drv->states[CPUIDLE_DRIVER_STATE_START];
		unsigned int polling_threshold;
		/*
                 * We want to default to C1 (hlt), not to busy polling
                 * unless the timer is happening really really soon, or
                 * C1's exit latency exceeds the user configured limit.
                 */
		polling_threshold = max_t(unsigned int, 20, s->target_residency);
		if (data->next_timer_us > polling_threshold &&
		    latency_req > s->exit_latency && !s->disabled &&
		    !dev->states_usage[CPUIDLE_DRIVER_STATE_START].disable)
			data->last_state_idx = CPUIDLE_DRIVER_STATE_START;
		else
			data->last_state_idx = CPUIDLE_DRIVER_STATE_START - 1;
	} else {
		data->last_state_idx = CPUIDLE_DRIVER_STATE_START;
	}
	/*
         * Use the lowest expected idle interval to pick the idle state.
         */
	data->predicted_us = min(data->predicted_us, expected_interval);
	/*
         * Use the performance multiplier and the user-configurable
         * latency_req to determine the maximum exit latency.
         */
	interactivity_req = data->predicted_us / performance_multiplier(nr_iowaiters, cpu_load);
	if (latency_req > interactivity_req)
		latency_req = interactivity_req;
	/*
         * Find the idle state with the lowest power while satisfying
         * our constraints.
         */
	for (i = data->last_state_idx + 1; i < drv->state_count; i++) {
		struct cpuidle_state *s = &drv->states[i];
		struct cpuidle_state_usage *su = &dev->states_usage[i];
		if (s->disabled || su->disable)
			continue;
		if (s->target_residency > data->predicted_us)
			continue;
		if (s->exit_latency > latency_req)
			continue;
		data->last_state_idx = i;
	}
	return data->last_state_idx;
}
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| len brown | len brown | 77 | 20.10% | 1 | 3.85% | 
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| rik van riel | rik van riel | 62 | 16.19% | 1 | 3.85% | 
| arjan van de ven | arjan van de ven | 42 | 10.97% | 2 | 7.69% | 
| liu shuox | liu shuox | 30 | 7.83% | 2 | 7.69% | 
| venkatesh pallipadi | venkatesh pallipadi | 29 | 7.57% | 2 | 7.69% | 
| mel gorman | mel gorman | 22 | 5.74% | 3 | 11.54% | 
| corrado zoccolo | corrado zoccolo | 19 | 4.96% | 1 | 3.85% | 
| tuukka tikkanen | tuukka tikkanen | 12 | 3.13% | 3 | 11.54% | 
| deepthi dharwar | deepthi dharwar | 9 | 2.35% | 1 | 3.85% | 
| ai li | ai li | 5 | 1.31% | 1 | 3.85% | 
| tero kristo | tero kristo | 2 | 0.52% | 1 | 3.85% | 
| christoph lameter | christoph lameter | 2 | 0.52% | 1 | 3.85% | 
| youquan song | youquan song | 1 | 0.26% | 1 | 3.85% | 
| javi merino | javi merino | 1 | 0.26% | 1 | 3.85% | 
| mark gross | mark gross | 1 | 0.26% | 1 | 3.85% | 
 | Total | 383 | 100.00% | 26 | 100.00% | 
/**
 * menu_reflect - records that data structures need update
 * @dev: the CPU
 * @index: the index of actual entered state
 *
 * NOTE: it's important to be fast here because this operation will add to
 *       the overall exit latency.
 */
static void menu_reflect(struct cpuidle_device *dev, int index)
{
	struct menu_device *data = this_cpu_ptr(&menu_devices);
	data->last_state_idx = index;
	data->needs_update = 1;
}
Contributors
 | Person | Tokens | Prop | Commits | CommitProp | 
| len brown | len brown | 19 | 51.35% | 1 | 25.00% | 
| deepthi dharwar | deepthi dharwar | 9 | 24.32% | 1 | 25.00% | 
| corrado zoccolo | corrado zoccolo | 7 | 18.92% | 1 | 25.00% | 
| christoph lameter | christoph lameter | 2 | 5.41% | 1 | 25.00% | 
 | Total | 37 | 100.00% | 4 | 100.00% | 
/**
 * menu_update - attempts to guess what happened after entry
 * @drv: cpuidle driver containing state data
 * @dev: the CPU
 */
static void menu_update(struct cpuidle_driver *drv, struct cpuidle_device *dev)
{
	struct menu_device *data = this_cpu_ptr(&menu_devices);
	int last_idx = data->last_state_idx;
	struct cpuidle_state *target = &drv->states[last_idx];
	unsigned int measured_us;
	unsigned int new_factor;
	/*
         * Try to figure out how much time passed between entry to low
         * power state and occurrence of the wakeup event.
         *
         * If the entered idle state didn't support residency measurements,
         * we use them anyway if they are short, and if long,
         * truncate to the whole expected time.
         *
         * Any measured amount of time will include the exit latency.
         * Since we are interested in when the wakeup begun, not when it
         * was completed, we must subtract the exit latency. However, if
         * the measured amount of time is less than the exit latency,
         * assume the state was never reached and the exit latency is 0.
         */
	/* measured value */
	measured_us = cpuidle_get_last_residency(dev);
	/* Deduct exit latency */
	if (measured_us > 2 * target->exit_latency)
		measured_us -= target->exit_latency;
	else
		measured_us /= 2;
	/* Make sure our coefficients do not exceed unity */
	if (measured_us > data->next_timer_us)
		measured_us = data->next_timer_us;
	/* Update our correction ratio */
	new_factor = data->correction_factor[data->bucket];
	new_factor -= new_factor / DECAY;
	if (data->next_timer_us > 0 && measured_us < MAX_INTERESTING)
		new_factor += RESOLUTION * measured_us / data->next_timer_us;
	else
		/*
                 * we were idle so long that we count it as a perfect
                 * prediction
                 */
		new_factor += RESOLUTION;
	/*
         * We don't want 0 as factor; we always want at least
         * a tiny bit of estimated time. Fortunately, due to rounding,
         * new_factor will stay nonzero regardless of measured_us values
         * and the compiler can eliminate this test as long as DECAY > 1.
         */
	if (DECAY == 1 && unlikely(new_factor == 0))
		new_factor = 1;
	data->correction_factor[data->bucket] = new_factor;
	/* update the repeating-pattern data */
	data->intervals[data->interval_ptr++] = measured_us;
	if (data->interval_ptr >= INTERVALS)
		data->interval_ptr = 0;
}
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| len brown | len brown | 47 | 23.15% | 2 | 14.29% | 
| tuukka tikkanen | tuukka tikkanen | 42 | 20.69% | 5 | 35.71% | 
| corrado zoccolo | corrado zoccolo | 19 | 9.36% | 1 | 7.14% | 
| venkatesh pallipadi | venkatesh pallipadi | 8 | 3.94% | 1 | 7.14% | 
| rik van riel | rik van riel | 7 | 3.45% | 1 | 7.14% | 
| deepthi dharwar | deepthi dharwar | 6 | 2.96% | 1 | 7.14% | 
| christoph lameter | christoph lameter | 2 | 0.99% | 1 | 7.14% | 
 | Total | 203 | 100.00% | 14 | 100.00% | 
/**
 * menu_enable_device - scans a CPU's states and does setup
 * @drv: cpuidle driver
 * @dev: the CPU
 */
static int menu_enable_device(struct cpuidle_driver *drv,
				struct cpuidle_device *dev)
{
	struct menu_device *data = &per_cpu(menu_devices, dev->cpu);
	int i;
	memset(data, 0, sizeof(struct menu_device));
	/*
         * if the correction factor is 0 (eg first time init or cpu hotplug
         * etc), we actually want to start out with a unity factor.
         */
	for(i = 0; i < BUCKETS; i++)
		data->correction_factor[i] = RESOLUTION * DECAY;
	return 0;
}
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| chander kashyap | chander kashyap | 28 | 37.33% | 1 | 33.33% | 
| deepthi dharwar | deepthi dharwar | 5 | 6.67% | 1 | 33.33% | 
 | Total | 75 | 100.00% | 3 | 100.00% | 
static struct cpuidle_governor menu_governor = {
	.name =		"menu",
	.rating =	20,
	.enable =	menu_enable_device,
	.select =	menu_select,
	.reflect =	menu_reflect,
	.owner =	THIS_MODULE,
};
/**
 * init_menu - initializes the governor
 */
static int __init init_menu(void)
{
	return cpuidle_register_governor(&menu_governor);
}
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postcore_initcall(init_menu);
Overall Contributors
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| arjan van de ven | arjan van de ven | 361 | 27.27% | 2 | 4.00% | 
| len brown | len brown | 288 | 21.75% | 2 | 4.00% | 
| youquan song | youquan song | 111 | 8.38% | 2 | 4.00% | 
| tuukka tikkanen | tuukka tikkanen | 96 | 7.25% | 12 | 24.00% | 
| rik van riel | rik van riel | 76 | 5.74% | 2 | 4.00% | 
| rafael j. wysocki | rafael j. wysocki | 69 | 5.21% | 4 | 8.00% | 
| mel gorman | mel gorman | 69 | 5.21% | 4 | 8.00% | 
| corrado zoccolo | corrado zoccolo | 58 | 4.38% | 1 | 2.00% | 
| venkatesh pallipadi | venkatesh pallipadi | 39 | 2.95% | 3 | 6.00% | 
| deepthi dharwar | deepthi dharwar | 38 | 2.87% | 2 | 4.00% | 
| rasmus villemoes | rasmus villemoes | 35 | 2.64% | 2 | 4.00% | 
| liu shuox | liu shuox | 30 | 2.27% | 2 | 4.00% | 
| chander kashyap | chander kashyap | 28 | 2.11% | 1 | 2.00% | 
| christoph lameter | christoph lameter | 6 | 0.45% | 1 | 2.00% | 
| ai li | ai li | 5 | 0.38% | 1 | 2.00% | 
| stephen hemminger | stephen hemminger | 3 | 0.23% | 1 | 2.00% | 
| paul gortmaker | paul gortmaker | 3 | 0.23% | 1 | 2.00% | 
| richard kennedy | richard kennedy | 2 | 0.15% | 1 | 2.00% | 
| tero kristo | tero kristo | 2 | 0.15% | 1 | 2.00% | 
| mark gross | mark gross | 1 | 0.08% | 1 | 2.00% | 
| daniel lezcano | daniel lezcano | 1 | 0.08% | 1 | 2.00% | 
| jean pihet | jean pihet | 1 | 0.08% | 1 | 2.00% | 
| javi merino | javi merino | 1 | 0.08% | 1 | 2.00% | 
| lucas de marchi | lucas de marchi | 1 | 0.08% | 1 | 2.00% | 
 | Total | 1324 | 100.00% | 50 | 100.00% | 
  
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