WSL2-Linux-Kernel/block/blk-iocost.c

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blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
/* SPDX-License-Identifier: GPL-2.0
*
* IO cost model based controller.
*
* Copyright (C) 2019 Tejun Heo <tj@kernel.org>
* Copyright (C) 2019 Andy Newell <newella@fb.com>
* Copyright (C) 2019 Facebook
*
* One challenge of controlling IO resources is the lack of trivially
* observable cost metric. This is distinguished from CPU and memory where
* wallclock time and the number of bytes can serve as accurate enough
* approximations.
*
* Bandwidth and iops are the most commonly used metrics for IO devices but
* depending on the type and specifics of the device, different IO patterns
* easily lead to multiple orders of magnitude variations rendering them
* useless for the purpose of IO capacity distribution. While on-device
* time, with a lot of clutches, could serve as a useful approximation for
* non-queued rotational devices, this is no longer viable with modern
* devices, even the rotational ones.
*
* While there is no cost metric we can trivially observe, it isn't a
* complete mystery. For example, on a rotational device, seek cost
* dominates while a contiguous transfer contributes a smaller amount
* proportional to the size. If we can characterize at least the relative
* costs of these different types of IOs, it should be possible to
* implement a reasonable work-conserving proportional IO resource
* distribution.
*
* 1. IO Cost Model
*
* IO cost model estimates the cost of an IO given its basic parameters and
* history (e.g. the end sector of the last IO). The cost is measured in
* device time. If a given IO is estimated to cost 10ms, the device should
* be able to process ~100 of those IOs in a second.
*
* Currently, there's only one builtin cost model - linear. Each IO is
* classified as sequential or random and given a base cost accordingly.
* On top of that, a size cost proportional to the length of the IO is
* added. While simple, this model captures the operational
* characteristics of a wide varienty of devices well enough. Default
* paramters for several different classes of devices are provided and the
* parameters can be configured from userspace via
* /sys/fs/cgroup/io.cost.model.
*
* If needed, tools/cgroup/iocost_coef_gen.py can be used to generate
* device-specific coefficients.
*
* If needed, tools/cgroup/iocost_coef_gen.py can be used to generate
* device-specific coefficients.
*
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
* 2. Control Strategy
*
* The device virtual time (vtime) is used as the primary control metric.
* The control strategy is composed of the following three parts.
*
* 2-1. Vtime Distribution
*
* When a cgroup becomes active in terms of IOs, its hierarchical share is
* calculated. Please consider the following hierarchy where the numbers
* inside parentheses denote the configured weights.
*
* root
* / \
* A (w:100) B (w:300)
* / \
* A0 (w:100) A1 (w:100)
*
* If B is idle and only A0 and A1 are actively issuing IOs, as the two are
* of equal weight, each gets 50% share. If then B starts issuing IOs, B
* gets 300/(100+300) or 75% share, and A0 and A1 equally splits the rest,
* 12.5% each. The distribution mechanism only cares about these flattened
* shares. They're called hweights (hierarchical weights) and always add
* upto 1 (HWEIGHT_WHOLE).
*
* A given cgroup's vtime runs slower in inverse proportion to its hweight.
* For example, with 12.5% weight, A0's time runs 8 times slower (100/12.5)
* against the device vtime - an IO which takes 10ms on the underlying
* device is considered to take 80ms on A0.
*
* This constitutes the basis of IO capacity distribution. Each cgroup's
* vtime is running at a rate determined by its hweight. A cgroup tracks
* the vtime consumed by past IOs and can issue a new IO iff doing so
* wouldn't outrun the current device vtime. Otherwise, the IO is
* suspended until the vtime has progressed enough to cover it.
*
* 2-2. Vrate Adjustment
*
* It's unrealistic to expect the cost model to be perfect. There are too
* many devices and even on the same device the overall performance
* fluctuates depending on numerous factors such as IO mixture and device
* internal garbage collection. The controller needs to adapt dynamically.
*
* This is achieved by adjusting the overall IO rate according to how busy
* the device is. If the device becomes overloaded, we're sending down too
* many IOs and should generally slow down. If there are waiting issuers
* but the device isn't saturated, we're issuing too few and should
* generally speed up.
*
* To slow down, we lower the vrate - the rate at which the device vtime
* passes compared to the wall clock. For example, if the vtime is running
* at the vrate of 75%, all cgroups added up would only be able to issue
* 750ms worth of IOs per second, and vice-versa for speeding up.
*
* Device business is determined using two criteria - rq wait and
* completion latencies.
*
* When a device gets saturated, the on-device and then the request queues
* fill up and a bio which is ready to be issued has to wait for a request
* to become available. When this delay becomes noticeable, it's a clear
* indication that the device is saturated and we lower the vrate. This
* saturation signal is fairly conservative as it only triggers when both
* hardware and software queues are filled up, and is used as the default
* busy signal.
*
* As devices can have deep queues and be unfair in how the queued commands
* are executed, soley depending on rq wait may not result in satisfactory
* control quality. For a better control quality, completion latency QoS
* parameters can be configured so that the device is considered saturated
* if N'th percentile completion latency rises above the set point.
*
* The completion latency requirements are a function of both the
* underlying device characteristics and the desired IO latency quality of
* service. There is an inherent trade-off - the tighter the latency QoS,
* the higher the bandwidth lossage. Latency QoS is disabled by default
* and can be set through /sys/fs/cgroup/io.cost.qos.
*
* 2-3. Work Conservation
*
* Imagine two cgroups A and B with equal weights. A is issuing a small IO
* periodically while B is sending out enough parallel IOs to saturate the
* device on its own. Let's say A's usage amounts to 100ms worth of IO
* cost per second, i.e., 10% of the device capacity. The naive
* distribution of half and half would lead to 60% utilization of the
* device, a significant reduction in the total amount of work done
* compared to free-for-all competition. This is too high a cost to pay
* for IO control.
*
* To conserve the total amount of work done, we keep track of how much
* each active cgroup is actually using and yield part of its weight if
* there are other cgroups which can make use of it. In the above case,
* A's weight will be lowered so that it hovers above the actual usage and
* B would be able to use the rest.
*
* As we don't want to penalize a cgroup for donating its weight, the
* surplus weight adjustment factors in a margin and has an immediate
* snapback mechanism in case the cgroup needs more IO vtime for itself.
*
* Note that adjusting down surplus weights has the same effects as
* accelerating vtime for other cgroups and work conservation can also be
* implemented by adjusting vrate dynamically. However, squaring who can
* donate and should take back how much requires hweight propagations
* anyway making it easier to implement and understand as a separate
* mechanism.
*
* 3. Monitoring
*
* Instead of debugfs or other clumsy monitoring mechanisms, this
* controller uses a drgn based monitoring script -
* tools/cgroup/iocost_monitor.py. For details on drgn, please see
* https://github.com/osandov/drgn. The ouput looks like the following.
*
* sdb RUN per=300ms cur_per=234.218:v203.695 busy= +1 vrate= 62.12%
* active weight hweight% inflt% dbt delay usages%
* test/a * 50/ 50 33.33/ 33.33 27.65 2 0*041 033:033:033
* test/b * 100/ 100 66.67/ 66.67 17.56 0 0*000 066:079:077
*
* - per : Timer period
* - cur_per : Internal wall and device vtime clock
* - vrate : Device virtual time rate against wall clock
* - weight : Surplus-adjusted and configured weights
* - hweight : Surplus-adjusted and configured hierarchical weights
* - inflt : The percentage of in-flight IO cost at the end of last period
* - del_ms : Deferred issuer delay induction level and duration
* - usages : Usage history
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
*/
#include <linux/kernel.h>
#include <linux/module.h>
#include <linux/timer.h>
#include <linux/time64.h>
#include <linux/parser.h>
#include <linux/sched/signal.h>
#include <linux/blk-cgroup.h>
#include "blk-rq-qos.h"
#include "blk-stat.h"
#include "blk-wbt.h"
#ifdef CONFIG_TRACEPOINTS
/* copied from TRACE_CGROUP_PATH, see cgroup-internal.h */
#define TRACE_IOCG_PATH_LEN 1024
static DEFINE_SPINLOCK(trace_iocg_path_lock);
static char trace_iocg_path[TRACE_IOCG_PATH_LEN];
#define TRACE_IOCG_PATH(type, iocg, ...) \
do { \
unsigned long flags; \
if (trace_iocost_##type##_enabled()) { \
spin_lock_irqsave(&trace_iocg_path_lock, flags); \
cgroup_path(iocg_to_blkg(iocg)->blkcg->css.cgroup, \
trace_iocg_path, TRACE_IOCG_PATH_LEN); \
trace_iocost_##type(iocg, trace_iocg_path, \
##__VA_ARGS__); \
spin_unlock_irqrestore(&trace_iocg_path_lock, flags); \
} \
} while (0)
#else /* CONFIG_TRACE_POINTS */
#define TRACE_IOCG_PATH(type, iocg, ...) do { } while (0)
#endif /* CONFIG_TRACE_POINTS */
enum {
MILLION = 1000000,
/* timer period is calculated from latency requirements, bound it */
MIN_PERIOD = USEC_PER_MSEC,
MAX_PERIOD = USEC_PER_SEC,
/*
* A cgroup's vtime can run 50% behind the device vtime, which
* serves as its IO credit buffer. Surplus weight adjustment is
* immediately canceled if the vtime margin runs below 10%.
*/
MARGIN_PCT = 50,
INUSE_MARGIN_PCT = 10,
/* Have some play in waitq timer operations */
WAITQ_TIMER_MARGIN_PCT = 5,
/*
* vtime can wrap well within a reasonable uptime when vrate is
* consistently raised. Don't trust recorded cgroup vtime if the
* period counter indicates that it's older than 5mins.
*/
VTIME_VALID_DUR = 300 * USEC_PER_SEC,
/*
* Remember the past three non-zero usages and use the max for
* surplus calculation. Three slots guarantee that we remember one
* full period usage from the last active stretch even after
* partial deactivation and re-activation periods. Don't start
* giving away weight before collecting two data points to prevent
* hweight adjustments based on one partial activation period.
*/
NR_USAGE_SLOTS = 3,
MIN_VALID_USAGES = 2,
/* 1/64k is granular enough and can easily be handled w/ u32 */
HWEIGHT_WHOLE = 1 << 16,
/*
* As vtime is used to calculate the cost of each IO, it needs to
* be fairly high precision. For example, it should be able to
* represent the cost of a single page worth of discard with
* suffificient accuracy. At the same time, it should be able to
* represent reasonably long enough durations to be useful and
* convenient during operation.
*
* 1s worth of vtime is 2^37. This gives us both sub-nanosecond
* granularity and days of wrap-around time even at extreme vrates.
*/
VTIME_PER_SEC_SHIFT = 37,
VTIME_PER_SEC = 1LLU << VTIME_PER_SEC_SHIFT,
VTIME_PER_USEC = VTIME_PER_SEC / USEC_PER_SEC,
/* bound vrate adjustments within two orders of magnitude */
VRATE_MIN_PPM = 10000, /* 1% */
VRATE_MAX_PPM = 100000000, /* 10000% */
VRATE_MIN = VTIME_PER_USEC * VRATE_MIN_PPM / MILLION,
VRATE_CLAMP_ADJ_PCT = 4,
/* if IOs end up waiting for requests, issue less */
RQ_WAIT_BUSY_PCT = 5,
/* unbusy hysterisis */
UNBUSY_THR_PCT = 75,
/* don't let cmds which take a very long time pin lagging for too long */
MAX_LAGGING_PERIODS = 10,
/*
* If usage% * 1.25 + 2% is lower than hweight% by more than 3%,
* donate the surplus.
*/
SURPLUS_SCALE_PCT = 125, /* * 125% */
SURPLUS_SCALE_ABS = HWEIGHT_WHOLE / 50, /* + 2% */
SURPLUS_MIN_ADJ_DELTA = HWEIGHT_WHOLE / 33, /* 3% */
/* switch iff the conditions are met for longer than this */
AUTOP_CYCLE_NSEC = 10LLU * NSEC_PER_SEC,
/*
* Count IO size in 4k pages. The 12bit shift helps keeping
* size-proportional components of cost calculation in closer
* numbers of digits to per-IO cost components.
*/
IOC_PAGE_SHIFT = 12,
IOC_PAGE_SIZE = 1 << IOC_PAGE_SHIFT,
IOC_SECT_TO_PAGE_SHIFT = IOC_PAGE_SHIFT - SECTOR_SHIFT,
/* if apart further than 16M, consider randio for linear model */
LCOEF_RANDIO_PAGES = 4096,
};
enum ioc_running {
IOC_IDLE,
IOC_RUNNING,
IOC_STOP,
};
/* io.cost.qos controls including per-dev enable of the whole controller */
enum {
QOS_ENABLE,
QOS_CTRL,
NR_QOS_CTRL_PARAMS,
};
/* io.cost.qos params */
enum {
QOS_RPPM,
QOS_RLAT,
QOS_WPPM,
QOS_WLAT,
QOS_MIN,
QOS_MAX,
NR_QOS_PARAMS,
};
/* io.cost.model controls */
enum {
COST_CTRL,
COST_MODEL,
NR_COST_CTRL_PARAMS,
};
/* builtin linear cost model coefficients */
enum {
I_LCOEF_RBPS,
I_LCOEF_RSEQIOPS,
I_LCOEF_RRANDIOPS,
I_LCOEF_WBPS,
I_LCOEF_WSEQIOPS,
I_LCOEF_WRANDIOPS,
NR_I_LCOEFS,
};
enum {
LCOEF_RPAGE,
LCOEF_RSEQIO,
LCOEF_RRANDIO,
LCOEF_WPAGE,
LCOEF_WSEQIO,
LCOEF_WRANDIO,
NR_LCOEFS,
};
enum {
AUTOP_INVALID,
AUTOP_HDD,
AUTOP_SSD_QD1,
AUTOP_SSD_DFL,
AUTOP_SSD_FAST,
};
struct ioc_gq;
struct ioc_params {
u32 qos[NR_QOS_PARAMS];
u64 i_lcoefs[NR_I_LCOEFS];
u64 lcoefs[NR_LCOEFS];
u32 too_fast_vrate_pct;
u32 too_slow_vrate_pct;
};
struct ioc_missed {
u32 nr_met;
u32 nr_missed;
u32 last_met;
u32 last_missed;
};
struct ioc_pcpu_stat {
struct ioc_missed missed[2];
u64 rq_wait_ns;
u64 last_rq_wait_ns;
};
/* per device */
struct ioc {
struct rq_qos rqos;
bool enabled;
struct ioc_params params;
u32 period_us;
u32 margin_us;
u64 vrate_min;
u64 vrate_max;
spinlock_t lock;
struct timer_list timer;
struct list_head active_iocgs; /* active cgroups */
struct ioc_pcpu_stat __percpu *pcpu_stat;
enum ioc_running running;
atomic64_t vtime_rate;
seqcount_t period_seqcount;
u32 period_at; /* wallclock starttime */
u64 period_at_vtime; /* vtime starttime */
atomic64_t cur_period; /* inc'd each period */
int busy_level; /* saturation history */
u64 inuse_margin_vtime;
bool weights_updated;
atomic_t hweight_gen; /* for lazy hweights */
u64 autop_too_fast_at;
u64 autop_too_slow_at;
int autop_idx;
bool user_qos_params:1;
bool user_cost_model:1;
};
/* per device-cgroup pair */
struct ioc_gq {
struct blkg_policy_data pd;
struct ioc *ioc;
/*
* A iocg can get its weight from two sources - an explicit
* per-device-cgroup configuration or the default weight of the
* cgroup. `cfg_weight` is the explicit per-device-cgroup
* configuration. `weight` is the effective considering both
* sources.
*
* When an idle cgroup becomes active its `active` goes from 0 to
* `weight`. `inuse` is the surplus adjusted active weight.
* `active` and `inuse` are used to calculate `hweight_active` and
* `hweight_inuse`.
*
* `last_inuse` remembers `inuse` while an iocg is idle to persist
* surplus adjustments.
*/
u32 cfg_weight;
u32 weight;
u32 active;
u32 inuse;
u32 last_inuse;
sector_t cursor; /* to detect randio */
/*
* `vtime` is this iocg's vtime cursor which progresses as IOs are
* issued. If lagging behind device vtime, the delta represents
* the currently available IO budget. If runnning ahead, the
* overage.
*
* `vtime_done` is the same but progressed on completion rather
* than issue. The delta behind `vtime` represents the cost of
* currently in-flight IOs.
*
* `last_vtime` is used to remember `vtime` at the end of the last
* period to calculate utilization.
*/
atomic64_t vtime;
atomic64_t done_vtime;
blk-iocost: Account force-charged overage in absolute vtime Currently, when a bio needs to be force-charged and there isn't enough budget, vtime is simply pushed into the future. This means that the cost of the whole bio is scaled using the current hweight and then charged immediately. Until the global vtime advances beyond this future vtime, the cgroup won't be allowed to issue normal IOs. This is incorrect and can lead to, for example, exploding vrate or extended stalls if vrate range is constrained. Consider the following scenario. 1. A cgroup with a very low hweight runs out of budget. 2. A storm of swap-out happens on it. All of them are scaled according to the current low hweight and charged to vtime pushing it to a far future. 3. All other cgroups go idle and now the above cgroup has access to the whole device. However, because vtime is already wound using the past low hweight, what its current hweight is doesn't matter until global vtime catches up to the local vtime. 4. As a result, either vrate gets ramped up extremely or the IOs stall while the underlying device is idle. This is because the hweight the overage is calculated at is different from the hweight that it's being paid at. Fix it by remembering the overage in absoulte vtime and continuously paying with the actual budget according to the current hweight at each period. Note that non-forced bios which wait already remembers the cost in absolute vtime. This brings forced-bio accounting in line. Signed-off-by: Tejun Heo <tj@kernel.org> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-09-04 22:45:52 +03:00
atomic64_t abs_vdebt;
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
u64 last_vtime;
/*
* The period this iocg was last active in. Used for deactivation
* and invalidating `vtime`.
*/
atomic64_t active_period;
struct list_head active_list;
/* see __propagate_active_weight() and current_hweight() for details */
u64 child_active_sum;
u64 child_inuse_sum;
int hweight_gen;
u32 hweight_active;
u32 hweight_inuse;
bool has_surplus;
struct wait_queue_head waitq;
struct hrtimer waitq_timer;
struct hrtimer delay_timer;
/* usage is recorded as fractions of HWEIGHT_WHOLE */
int usage_idx;
u32 usages[NR_USAGE_SLOTS];
/* this iocg's depth in the hierarchy and ancestors including self */
int level;
struct ioc_gq *ancestors[];
};
/* per cgroup */
struct ioc_cgrp {
struct blkcg_policy_data cpd;
unsigned int dfl_weight;
};
struct ioc_now {
u64 now_ns;
u32 now;
u64 vnow;
u64 vrate;
};
struct iocg_wait {
struct wait_queue_entry wait;
struct bio *bio;
u64 abs_cost;
bool committed;
};
struct iocg_wake_ctx {
struct ioc_gq *iocg;
u32 hw_inuse;
s64 vbudget;
};
static const struct ioc_params autop[] = {
[AUTOP_HDD] = {
.qos = {
[QOS_RLAT] = 250000, /* 250ms */
[QOS_WLAT] = 250000,
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
[QOS_MIN] = VRATE_MIN_PPM,
[QOS_MAX] = VRATE_MAX_PPM,
},
.i_lcoefs = {
[I_LCOEF_RBPS] = 174019176,
[I_LCOEF_RSEQIOPS] = 41708,
[I_LCOEF_RRANDIOPS] = 370,
[I_LCOEF_WBPS] = 178075866,
[I_LCOEF_WSEQIOPS] = 42705,
[I_LCOEF_WRANDIOPS] = 378,
},
},
[AUTOP_SSD_QD1] = {
.qos = {
[QOS_RLAT] = 25000, /* 25ms */
[QOS_WLAT] = 25000,
[QOS_MIN] = VRATE_MIN_PPM,
[QOS_MAX] = VRATE_MAX_PPM,
},
.i_lcoefs = {
[I_LCOEF_RBPS] = 245855193,
[I_LCOEF_RSEQIOPS] = 61575,
[I_LCOEF_RRANDIOPS] = 6946,
[I_LCOEF_WBPS] = 141365009,
[I_LCOEF_WSEQIOPS] = 33716,
[I_LCOEF_WRANDIOPS] = 26796,
},
},
[AUTOP_SSD_DFL] = {
.qos = {
[QOS_RLAT] = 25000, /* 25ms */
[QOS_WLAT] = 25000,
[QOS_MIN] = VRATE_MIN_PPM,
[QOS_MAX] = VRATE_MAX_PPM,
},
.i_lcoefs = {
[I_LCOEF_RBPS] = 488636629,
[I_LCOEF_RSEQIOPS] = 8932,
[I_LCOEF_RRANDIOPS] = 8518,
[I_LCOEF_WBPS] = 427891549,
[I_LCOEF_WSEQIOPS] = 28755,
[I_LCOEF_WRANDIOPS] = 21940,
},
.too_fast_vrate_pct = 500,
},
[AUTOP_SSD_FAST] = {
.qos = {
[QOS_RLAT] = 5000, /* 5ms */
[QOS_WLAT] = 5000,
[QOS_MIN] = VRATE_MIN_PPM,
[QOS_MAX] = VRATE_MAX_PPM,
},
.i_lcoefs = {
[I_LCOEF_RBPS] = 3102524156LLU,
[I_LCOEF_RSEQIOPS] = 724816,
[I_LCOEF_RRANDIOPS] = 778122,
[I_LCOEF_WBPS] = 1742780862LLU,
[I_LCOEF_WSEQIOPS] = 425702,
[I_LCOEF_WRANDIOPS] = 443193,
},
.too_slow_vrate_pct = 10,
},
};
/*
* vrate adjust percentages indexed by ioc->busy_level. We adjust up on
* vtime credit shortage and down on device saturation.
*/
static u32 vrate_adj_pct[] =
{ 0, 0, 0, 0,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
4, 4, 4, 4, 4, 4, 4, 4, 8, 8, 8, 8, 8, 8, 8, 8, 16 };
static struct blkcg_policy blkcg_policy_iocost;
/* accessors and helpers */
static struct ioc *rqos_to_ioc(struct rq_qos *rqos)
{
return container_of(rqos, struct ioc, rqos);
}
static struct ioc *q_to_ioc(struct request_queue *q)
{
return rqos_to_ioc(rq_qos_id(q, RQ_QOS_COST));
}
static const char *q_name(struct request_queue *q)
{
if (test_bit(QUEUE_FLAG_REGISTERED, &q->queue_flags))
return kobject_name(q->kobj.parent);
else
return "<unknown>";
}
static const char __maybe_unused *ioc_name(struct ioc *ioc)
{
return q_name(ioc->rqos.q);
}
static struct ioc_gq *pd_to_iocg(struct blkg_policy_data *pd)
{
return pd ? container_of(pd, struct ioc_gq, pd) : NULL;
}
static struct ioc_gq *blkg_to_iocg(struct blkcg_gq *blkg)
{
return pd_to_iocg(blkg_to_pd(blkg, &blkcg_policy_iocost));
}
static struct blkcg_gq *iocg_to_blkg(struct ioc_gq *iocg)
{
return pd_to_blkg(&iocg->pd);
}
static struct ioc_cgrp *blkcg_to_iocc(struct blkcg *blkcg)
{
return container_of(blkcg_to_cpd(blkcg, &blkcg_policy_iocost),
struct ioc_cgrp, cpd);
}
/*
* Scale @abs_cost to the inverse of @hw_inuse. The lower the hierarchical
blk-iocost: Account force-charged overage in absolute vtime Currently, when a bio needs to be force-charged and there isn't enough budget, vtime is simply pushed into the future. This means that the cost of the whole bio is scaled using the current hweight and then charged immediately. Until the global vtime advances beyond this future vtime, the cgroup won't be allowed to issue normal IOs. This is incorrect and can lead to, for example, exploding vrate or extended stalls if vrate range is constrained. Consider the following scenario. 1. A cgroup with a very low hweight runs out of budget. 2. A storm of swap-out happens on it. All of them are scaled according to the current low hweight and charged to vtime pushing it to a far future. 3. All other cgroups go idle and now the above cgroup has access to the whole device. However, because vtime is already wound using the past low hweight, what its current hweight is doesn't matter until global vtime catches up to the local vtime. 4. As a result, either vrate gets ramped up extremely or the IOs stall while the underlying device is idle. This is because the hweight the overage is calculated at is different from the hweight that it's being paid at. Fix it by remembering the overage in absoulte vtime and continuously paying with the actual budget according to the current hweight at each period. Note that non-forced bios which wait already remembers the cost in absolute vtime. This brings forced-bio accounting in line. Signed-off-by: Tejun Heo <tj@kernel.org> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-09-04 22:45:52 +03:00
* weight, the more expensive each IO. Must round up.
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
*/
static u64 abs_cost_to_cost(u64 abs_cost, u32 hw_inuse)
{
return DIV64_U64_ROUND_UP(abs_cost * HWEIGHT_WHOLE, hw_inuse);
}
blk-iocost: Account force-charged overage in absolute vtime Currently, when a bio needs to be force-charged and there isn't enough budget, vtime is simply pushed into the future. This means that the cost of the whole bio is scaled using the current hweight and then charged immediately. Until the global vtime advances beyond this future vtime, the cgroup won't be allowed to issue normal IOs. This is incorrect and can lead to, for example, exploding vrate or extended stalls if vrate range is constrained. Consider the following scenario. 1. A cgroup with a very low hweight runs out of budget. 2. A storm of swap-out happens on it. All of them are scaled according to the current low hweight and charged to vtime pushing it to a far future. 3. All other cgroups go idle and now the above cgroup has access to the whole device. However, because vtime is already wound using the past low hweight, what its current hweight is doesn't matter until global vtime catches up to the local vtime. 4. As a result, either vrate gets ramped up extremely or the IOs stall while the underlying device is idle. This is because the hweight the overage is calculated at is different from the hweight that it's being paid at. Fix it by remembering the overage in absoulte vtime and continuously paying with the actual budget according to the current hweight at each period. Note that non-forced bios which wait already remembers the cost in absolute vtime. This brings forced-bio accounting in line. Signed-off-by: Tejun Heo <tj@kernel.org> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-09-04 22:45:52 +03:00
/*
* The inverse of abs_cost_to_cost(). Must round up.
*/
static u64 cost_to_abs_cost(u64 cost, u32 hw_inuse)
{
return DIV64_U64_ROUND_UP(cost * hw_inuse, HWEIGHT_WHOLE);
}
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
static void iocg_commit_bio(struct ioc_gq *iocg, struct bio *bio, u64 cost)
{
bio->bi_iocost_cost = cost;
atomic64_add(cost, &iocg->vtime);
}
#define CREATE_TRACE_POINTS
#include <trace/events/iocost.h>
/* latency Qos params changed, update period_us and all the dependent params */
static void ioc_refresh_period_us(struct ioc *ioc)
{
u32 ppm, lat, multi, period_us;
lockdep_assert_held(&ioc->lock);
/* pick the higher latency target */
if (ioc->params.qos[QOS_RLAT] >= ioc->params.qos[QOS_WLAT]) {
ppm = ioc->params.qos[QOS_RPPM];
lat = ioc->params.qos[QOS_RLAT];
} else {
ppm = ioc->params.qos[QOS_WPPM];
lat = ioc->params.qos[QOS_WLAT];
}
/*
* We want the period to be long enough to contain a healthy number
* of IOs while short enough for granular control. Define it as a
* multiple of the latency target. Ideally, the multiplier should
* be scaled according to the percentile so that it would nominally
* contain a certain number of requests. Let's be simpler and
* scale it linearly so that it's 2x >= pct(90) and 10x at pct(50).
*/
if (ppm)
multi = max_t(u32, (MILLION - ppm) / 50000, 2);
else
multi = 2;
period_us = multi * lat;
period_us = clamp_t(u32, period_us, MIN_PERIOD, MAX_PERIOD);
/* calculate dependent params */
ioc->period_us = period_us;
ioc->margin_us = period_us * MARGIN_PCT / 100;
ioc->inuse_margin_vtime = DIV64_U64_ROUND_UP(
period_us * VTIME_PER_USEC * INUSE_MARGIN_PCT, 100);
}
static int ioc_autop_idx(struct ioc *ioc)
{
int idx = ioc->autop_idx;
const struct ioc_params *p = &autop[idx];
u32 vrate_pct;
u64 now_ns;
/* rotational? */
if (!blk_queue_nonrot(ioc->rqos.q))
return AUTOP_HDD;
/* handle SATA SSDs w/ broken NCQ */
if (blk_queue_depth(ioc->rqos.q) == 1)
return AUTOP_SSD_QD1;
/* use one of the normal ssd sets */
if (idx < AUTOP_SSD_DFL)
return AUTOP_SSD_DFL;
/* if user is overriding anything, maintain what was there */
if (ioc->user_qos_params || ioc->user_cost_model)
return idx;
/* step up/down based on the vrate */
vrate_pct = div64_u64(atomic64_read(&ioc->vtime_rate) * 100,
VTIME_PER_USEC);
now_ns = ktime_get_ns();
if (p->too_fast_vrate_pct && p->too_fast_vrate_pct <= vrate_pct) {
if (!ioc->autop_too_fast_at)
ioc->autop_too_fast_at = now_ns;
if (now_ns - ioc->autop_too_fast_at >= AUTOP_CYCLE_NSEC)
return idx + 1;
} else {
ioc->autop_too_fast_at = 0;
}
if (p->too_slow_vrate_pct && p->too_slow_vrate_pct >= vrate_pct) {
if (!ioc->autop_too_slow_at)
ioc->autop_too_slow_at = now_ns;
if (now_ns - ioc->autop_too_slow_at >= AUTOP_CYCLE_NSEC)
return idx - 1;
} else {
ioc->autop_too_slow_at = 0;
}
return idx;
}
/*
* Take the followings as input
*
* @bps maximum sequential throughput
* @seqiops maximum sequential 4k iops
* @randiops maximum random 4k iops
*
* and calculate the linear model cost coefficients.
*
* *@page per-page cost 1s / (@bps / 4096)
* *@seqio base cost of a seq IO max((1s / @seqiops) - *@page, 0)
* @randiops base cost of a rand IO max((1s / @randiops) - *@page, 0)
*/
static void calc_lcoefs(u64 bps, u64 seqiops, u64 randiops,
u64 *page, u64 *seqio, u64 *randio)
{
u64 v;
*page = *seqio = *randio = 0;
if (bps)
*page = DIV64_U64_ROUND_UP(VTIME_PER_SEC,
DIV_ROUND_UP_ULL(bps, IOC_PAGE_SIZE));
if (seqiops) {
v = DIV64_U64_ROUND_UP(VTIME_PER_SEC, seqiops);
if (v > *page)
*seqio = v - *page;
}
if (randiops) {
v = DIV64_U64_ROUND_UP(VTIME_PER_SEC, randiops);
if (v > *page)
*randio = v - *page;
}
}
static void ioc_refresh_lcoefs(struct ioc *ioc)
{
u64 *u = ioc->params.i_lcoefs;
u64 *c = ioc->params.lcoefs;
calc_lcoefs(u[I_LCOEF_RBPS], u[I_LCOEF_RSEQIOPS], u[I_LCOEF_RRANDIOPS],
&c[LCOEF_RPAGE], &c[LCOEF_RSEQIO], &c[LCOEF_RRANDIO]);
calc_lcoefs(u[I_LCOEF_WBPS], u[I_LCOEF_WSEQIOPS], u[I_LCOEF_WRANDIOPS],
&c[LCOEF_WPAGE], &c[LCOEF_WSEQIO], &c[LCOEF_WRANDIO]);
}
static bool ioc_refresh_params(struct ioc *ioc, bool force)
{
const struct ioc_params *p;
int idx;
lockdep_assert_held(&ioc->lock);
idx = ioc_autop_idx(ioc);
p = &autop[idx];
if (idx == ioc->autop_idx && !force)
return false;
if (idx != ioc->autop_idx)
atomic64_set(&ioc->vtime_rate, VTIME_PER_USEC);
ioc->autop_idx = idx;
ioc->autop_too_fast_at = 0;
ioc->autop_too_slow_at = 0;
if (!ioc->user_qos_params)
memcpy(ioc->params.qos, p->qos, sizeof(p->qos));
if (!ioc->user_cost_model)
memcpy(ioc->params.i_lcoefs, p->i_lcoefs, sizeof(p->i_lcoefs));
ioc_refresh_period_us(ioc);
ioc_refresh_lcoefs(ioc);
ioc->vrate_min = DIV64_U64_ROUND_UP((u64)ioc->params.qos[QOS_MIN] *
VTIME_PER_USEC, MILLION);
ioc->vrate_max = div64_u64((u64)ioc->params.qos[QOS_MAX] *
VTIME_PER_USEC, MILLION);
return true;
}
/* take a snapshot of the current [v]time and vrate */
static void ioc_now(struct ioc *ioc, struct ioc_now *now)
{
unsigned seq;
now->now_ns = ktime_get();
now->now = ktime_to_us(now->now_ns);
now->vrate = atomic64_read(&ioc->vtime_rate);
/*
* The current vtime is
*
* vtime at period start + (wallclock time since the start) * vrate
*
* As a consistent snapshot of `period_at_vtime` and `period_at` is
* needed, they're seqcount protected.
*/
do {
seq = read_seqcount_begin(&ioc->period_seqcount);
now->vnow = ioc->period_at_vtime +
(now->now - ioc->period_at) * now->vrate;
} while (read_seqcount_retry(&ioc->period_seqcount, seq));
}
static void ioc_start_period(struct ioc *ioc, struct ioc_now *now)
{
lockdep_assert_held(&ioc->lock);
WARN_ON_ONCE(ioc->running != IOC_RUNNING);
write_seqcount_begin(&ioc->period_seqcount);
ioc->period_at = now->now;
ioc->period_at_vtime = now->vnow;
write_seqcount_end(&ioc->period_seqcount);
ioc->timer.expires = jiffies + usecs_to_jiffies(ioc->period_us);
add_timer(&ioc->timer);
}
/*
* Update @iocg's `active` and `inuse` to @active and @inuse, update level
* weight sums and propagate upwards accordingly.
*/
static void __propagate_active_weight(struct ioc_gq *iocg, u32 active, u32 inuse)
{
struct ioc *ioc = iocg->ioc;
int lvl;
lockdep_assert_held(&ioc->lock);
inuse = min(active, inuse);
for (lvl = iocg->level - 1; lvl >= 0; lvl--) {
struct ioc_gq *parent = iocg->ancestors[lvl];
struct ioc_gq *child = iocg->ancestors[lvl + 1];
u32 parent_active = 0, parent_inuse = 0;
/* update the level sums */
parent->child_active_sum += (s32)(active - child->active);
parent->child_inuse_sum += (s32)(inuse - child->inuse);
/* apply the udpates */
child->active = active;
child->inuse = inuse;
/*
* The delta between inuse and active sums indicates that
* that much of weight is being given away. Parent's inuse
* and active should reflect the ratio.
*/
if (parent->child_active_sum) {
parent_active = parent->weight;
parent_inuse = DIV64_U64_ROUND_UP(
parent_active * parent->child_inuse_sum,
parent->child_active_sum);
}
/* do we need to keep walking up? */
if (parent_active == parent->active &&
parent_inuse == parent->inuse)
break;
active = parent_active;
inuse = parent_inuse;
}
ioc->weights_updated = true;
}
static void commit_active_weights(struct ioc *ioc)
{
lockdep_assert_held(&ioc->lock);
if (ioc->weights_updated) {
/* paired with rmb in current_hweight(), see there */
smp_wmb();
atomic_inc(&ioc->hweight_gen);
ioc->weights_updated = false;
}
}
static void propagate_active_weight(struct ioc_gq *iocg, u32 active, u32 inuse)
{
__propagate_active_weight(iocg, active, inuse);
commit_active_weights(iocg->ioc);
}
static void current_hweight(struct ioc_gq *iocg, u32 *hw_activep, u32 *hw_inusep)
{
struct ioc *ioc = iocg->ioc;
int lvl;
u32 hwa, hwi;
int ioc_gen;
/* hot path - if uptodate, use cached */
ioc_gen = atomic_read(&ioc->hweight_gen);
if (ioc_gen == iocg->hweight_gen)
goto out;
/*
* Paired with wmb in commit_active_weights(). If we saw the
* updated hweight_gen, all the weight updates from
* __propagate_active_weight() are visible too.
*
* We can race with weight updates during calculation and get it
* wrong. However, hweight_gen would have changed and a future
* reader will recalculate and we're guaranteed to discard the
* wrong result soon.
*/
smp_rmb();
hwa = hwi = HWEIGHT_WHOLE;
for (lvl = 0; lvl <= iocg->level - 1; lvl++) {
struct ioc_gq *parent = iocg->ancestors[lvl];
struct ioc_gq *child = iocg->ancestors[lvl + 1];
u32 active_sum = READ_ONCE(parent->child_active_sum);
u32 inuse_sum = READ_ONCE(parent->child_inuse_sum);
u32 active = READ_ONCE(child->active);
u32 inuse = READ_ONCE(child->inuse);
/* we can race with deactivations and either may read as zero */
if (!active_sum || !inuse_sum)
continue;
active_sum = max(active, active_sum);
hwa = hwa * active / active_sum; /* max 16bits * 10000 */
inuse_sum = max(inuse, inuse_sum);
hwi = hwi * inuse / inuse_sum; /* max 16bits * 10000 */
}
iocg->hweight_active = max_t(u32, hwa, 1);
iocg->hweight_inuse = max_t(u32, hwi, 1);
iocg->hweight_gen = ioc_gen;
out:
if (hw_activep)
*hw_activep = iocg->hweight_active;
if (hw_inusep)
*hw_inusep = iocg->hweight_inuse;
}
static void weight_updated(struct ioc_gq *iocg)
{
struct ioc *ioc = iocg->ioc;
struct blkcg_gq *blkg = iocg_to_blkg(iocg);
struct ioc_cgrp *iocc = blkcg_to_iocc(blkg->blkcg);
u32 weight;
lockdep_assert_held(&ioc->lock);
weight = iocg->cfg_weight ?: iocc->dfl_weight;
if (weight != iocg->weight && iocg->active)
propagate_active_weight(iocg, weight,
DIV64_U64_ROUND_UP(iocg->inuse * weight, iocg->weight));
iocg->weight = weight;
}
static bool iocg_activate(struct ioc_gq *iocg, struct ioc_now *now)
{
struct ioc *ioc = iocg->ioc;
u64 last_period, cur_period, max_period_delta;
u64 vtime, vmargin, vmin;
int i;
/*
* If seem to be already active, just update the stamp to tell the
* timer that we're still active. We don't mind occassional races.
*/
if (!list_empty(&iocg->active_list)) {
ioc_now(ioc, now);
cur_period = atomic64_read(&ioc->cur_period);
if (atomic64_read(&iocg->active_period) != cur_period)
atomic64_set(&iocg->active_period, cur_period);
return true;
}
/* racy check on internal node IOs, treat as root level IOs */
if (iocg->child_active_sum)
return false;
spin_lock_irq(&ioc->lock);
ioc_now(ioc, now);
/* update period */
cur_period = atomic64_read(&ioc->cur_period);
last_period = atomic64_read(&iocg->active_period);
atomic64_set(&iocg->active_period, cur_period);
/* already activated or breaking leaf-only constraint? */
if (!list_empty(&iocg->active_list))
goto succeed_unlock;
for (i = iocg->level - 1; i > 0; i--)
if (!list_empty(&iocg->ancestors[i]->active_list))
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
goto fail_unlock;
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
if (iocg->child_active_sum)
goto fail_unlock;
/*
* vtime may wrap when vrate is raised substantially due to
* underestimated IO costs. Look at the period and ignore its
* vtime if the iocg has been idle for too long. Also, cap the
* budget it can start with to the margin.
*/
max_period_delta = DIV64_U64_ROUND_UP(VTIME_VALID_DUR, ioc->period_us);
vtime = atomic64_read(&iocg->vtime);
vmargin = ioc->margin_us * now->vrate;
vmin = now->vnow - vmargin;
if (last_period + max_period_delta < cur_period ||
time_before64(vtime, vmin)) {
atomic64_add(vmin - vtime, &iocg->vtime);
atomic64_add(vmin - vtime, &iocg->done_vtime);
vtime = vmin;
}
/*
* Activate, propagate weight and start period timer if not
* running. Reset hweight_gen to avoid accidental match from
* wrapping.
*/
iocg->hweight_gen = atomic_read(&ioc->hweight_gen) - 1;
list_add(&iocg->active_list, &ioc->active_iocgs);
propagate_active_weight(iocg, iocg->weight,
iocg->last_inuse ?: iocg->weight);
TRACE_IOCG_PATH(iocg_activate, iocg, now,
last_period, cur_period, vtime);
iocg->last_vtime = vtime;
if (ioc->running == IOC_IDLE) {
ioc->running = IOC_RUNNING;
ioc_start_period(ioc, now);
}
succeed_unlock:
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
spin_unlock_irq(&ioc->lock);
return true;
fail_unlock:
spin_unlock_irq(&ioc->lock);
return false;
}
static int iocg_wake_fn(struct wait_queue_entry *wq_entry, unsigned mode,
int flags, void *key)
{
struct iocg_wait *wait = container_of(wq_entry, struct iocg_wait, wait);
struct iocg_wake_ctx *ctx = (struct iocg_wake_ctx *)key;
u64 cost = abs_cost_to_cost(wait->abs_cost, ctx->hw_inuse);
ctx->vbudget -= cost;
if (ctx->vbudget < 0)
return -1;
iocg_commit_bio(ctx->iocg, wait->bio, cost);
/*
* autoremove_wake_function() removes the wait entry only when it
* actually changed the task state. We want the wait always
* removed. Remove explicitly and use default_wake_function().
*/
list_del_init(&wq_entry->entry);
wait->committed = true;
default_wake_function(wq_entry, mode, flags, key);
return 0;
}
static void iocg_kick_waitq(struct ioc_gq *iocg, struct ioc_now *now)
{
struct ioc *ioc = iocg->ioc;
struct iocg_wake_ctx ctx = { .iocg = iocg };
u64 margin_ns = (u64)(ioc->period_us *
WAITQ_TIMER_MARGIN_PCT / 100) * NSEC_PER_USEC;
blk-iocost: Account force-charged overage in absolute vtime Currently, when a bio needs to be force-charged and there isn't enough budget, vtime is simply pushed into the future. This means that the cost of the whole bio is scaled using the current hweight and then charged immediately. Until the global vtime advances beyond this future vtime, the cgroup won't be allowed to issue normal IOs. This is incorrect and can lead to, for example, exploding vrate or extended stalls if vrate range is constrained. Consider the following scenario. 1. A cgroup with a very low hweight runs out of budget. 2. A storm of swap-out happens on it. All of them are scaled according to the current low hweight and charged to vtime pushing it to a far future. 3. All other cgroups go idle and now the above cgroup has access to the whole device. However, because vtime is already wound using the past low hweight, what its current hweight is doesn't matter until global vtime catches up to the local vtime. 4. As a result, either vrate gets ramped up extremely or the IOs stall while the underlying device is idle. This is because the hweight the overage is calculated at is different from the hweight that it's being paid at. Fix it by remembering the overage in absoulte vtime and continuously paying with the actual budget according to the current hweight at each period. Note that non-forced bios which wait already remembers the cost in absolute vtime. This brings forced-bio accounting in line. Signed-off-by: Tejun Heo <tj@kernel.org> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-09-04 22:45:52 +03:00
u64 abs_vdebt, vdebt, vshortage, expires, oexpires;
s64 vbudget;
u32 hw_inuse;
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
lockdep_assert_held(&iocg->waitq.lock);
blk-iocost: Account force-charged overage in absolute vtime Currently, when a bio needs to be force-charged and there isn't enough budget, vtime is simply pushed into the future. This means that the cost of the whole bio is scaled using the current hweight and then charged immediately. Until the global vtime advances beyond this future vtime, the cgroup won't be allowed to issue normal IOs. This is incorrect and can lead to, for example, exploding vrate or extended stalls if vrate range is constrained. Consider the following scenario. 1. A cgroup with a very low hweight runs out of budget. 2. A storm of swap-out happens on it. All of them are scaled according to the current low hweight and charged to vtime pushing it to a far future. 3. All other cgroups go idle and now the above cgroup has access to the whole device. However, because vtime is already wound using the past low hweight, what its current hweight is doesn't matter until global vtime catches up to the local vtime. 4. As a result, either vrate gets ramped up extremely or the IOs stall while the underlying device is idle. This is because the hweight the overage is calculated at is different from the hweight that it's being paid at. Fix it by remembering the overage in absoulte vtime and continuously paying with the actual budget according to the current hweight at each period. Note that non-forced bios which wait already remembers the cost in absolute vtime. This brings forced-bio accounting in line. Signed-off-by: Tejun Heo <tj@kernel.org> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-09-04 22:45:52 +03:00
current_hweight(iocg, NULL, &hw_inuse);
vbudget = now->vnow - atomic64_read(&iocg->vtime);
/* pay off debt */
abs_vdebt = atomic64_read(&iocg->abs_vdebt);
vdebt = abs_cost_to_cost(abs_vdebt, hw_inuse);
if (vdebt && vbudget > 0) {
u64 delta = min_t(u64, vbudget, vdebt);
u64 abs_delta = min(cost_to_abs_cost(delta, hw_inuse),
abs_vdebt);
atomic64_add(delta, &iocg->vtime);
atomic64_add(delta, &iocg->done_vtime);
atomic64_sub(abs_delta, &iocg->abs_vdebt);
if (WARN_ON_ONCE(atomic64_read(&iocg->abs_vdebt) < 0))
atomic64_set(&iocg->abs_vdebt, 0);
}
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
/*
* Wake up the ones which are due and see how much vtime we'll need
* for the next one.
*/
blk-iocost: Account force-charged overage in absolute vtime Currently, when a bio needs to be force-charged and there isn't enough budget, vtime is simply pushed into the future. This means that the cost of the whole bio is scaled using the current hweight and then charged immediately. Until the global vtime advances beyond this future vtime, the cgroup won't be allowed to issue normal IOs. This is incorrect and can lead to, for example, exploding vrate or extended stalls if vrate range is constrained. Consider the following scenario. 1. A cgroup with a very low hweight runs out of budget. 2. A storm of swap-out happens on it. All of them are scaled according to the current low hweight and charged to vtime pushing it to a far future. 3. All other cgroups go idle and now the above cgroup has access to the whole device. However, because vtime is already wound using the past low hweight, what its current hweight is doesn't matter until global vtime catches up to the local vtime. 4. As a result, either vrate gets ramped up extremely or the IOs stall while the underlying device is idle. This is because the hweight the overage is calculated at is different from the hweight that it's being paid at. Fix it by remembering the overage in absoulte vtime and continuously paying with the actual budget according to the current hweight at each period. Note that non-forced bios which wait already remembers the cost in absolute vtime. This brings forced-bio accounting in line. Signed-off-by: Tejun Heo <tj@kernel.org> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-09-04 22:45:52 +03:00
ctx.hw_inuse = hw_inuse;
ctx.vbudget = vbudget - vdebt;
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
__wake_up_locked_key(&iocg->waitq, TASK_NORMAL, &ctx);
if (!waitqueue_active(&iocg->waitq))
return;
if (WARN_ON_ONCE(ctx.vbudget >= 0))
return;
/* determine next wakeup, add a quarter margin to guarantee chunking */
vshortage = -ctx.vbudget;
expires = now->now_ns +
DIV64_U64_ROUND_UP(vshortage, now->vrate) * NSEC_PER_USEC;
expires += margin_ns / 4;
/* if already active and close enough, don't bother */
oexpires = ktime_to_ns(hrtimer_get_softexpires(&iocg->waitq_timer));
if (hrtimer_is_queued(&iocg->waitq_timer) &&
abs(oexpires - expires) <= margin_ns / 4)
return;
hrtimer_start_range_ns(&iocg->waitq_timer, ns_to_ktime(expires),
margin_ns / 4, HRTIMER_MODE_ABS);
}
static enum hrtimer_restart iocg_waitq_timer_fn(struct hrtimer *timer)
{
struct ioc_gq *iocg = container_of(timer, struct ioc_gq, waitq_timer);
struct ioc_now now;
unsigned long flags;
ioc_now(iocg->ioc, &now);
spin_lock_irqsave(&iocg->waitq.lock, flags);
iocg_kick_waitq(iocg, &now);
spin_unlock_irqrestore(&iocg->waitq.lock, flags);
return HRTIMER_NORESTART;
}
static bool iocg_kick_delay(struct ioc_gq *iocg, struct ioc_now *now, u64 cost)
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
{
struct ioc *ioc = iocg->ioc;
struct blkcg_gq *blkg = iocg_to_blkg(iocg);
u64 vtime = atomic64_read(&iocg->vtime);
u64 vmargin = ioc->margin_us * now->vrate;
u64 margin_ns = ioc->margin_us * NSEC_PER_USEC;
u64 expires, oexpires;
blk-iocost: Account force-charged overage in absolute vtime Currently, when a bio needs to be force-charged and there isn't enough budget, vtime is simply pushed into the future. This means that the cost of the whole bio is scaled using the current hweight and then charged immediately. Until the global vtime advances beyond this future vtime, the cgroup won't be allowed to issue normal IOs. This is incorrect and can lead to, for example, exploding vrate or extended stalls if vrate range is constrained. Consider the following scenario. 1. A cgroup with a very low hweight runs out of budget. 2. A storm of swap-out happens on it. All of them are scaled according to the current low hweight and charged to vtime pushing it to a far future. 3. All other cgroups go idle and now the above cgroup has access to the whole device. However, because vtime is already wound using the past low hweight, what its current hweight is doesn't matter until global vtime catches up to the local vtime. 4. As a result, either vrate gets ramped up extremely or the IOs stall while the underlying device is idle. This is because the hweight the overage is calculated at is different from the hweight that it's being paid at. Fix it by remembering the overage in absoulte vtime and continuously paying with the actual budget according to the current hweight at each period. Note that non-forced bios which wait already remembers the cost in absolute vtime. This brings forced-bio accounting in line. Signed-off-by: Tejun Heo <tj@kernel.org> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-09-04 22:45:52 +03:00
u32 hw_inuse;
/* debt-adjust vtime */
current_hweight(iocg, NULL, &hw_inuse);
vtime += abs_cost_to_cost(atomic64_read(&iocg->abs_vdebt), hw_inuse);
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
/* clear or maintain depending on the overage */
if (time_before_eq64(vtime, now->vnow)) {
blkcg_clear_delay(blkg);
return false;
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
}
if (!atomic_read(&blkg->use_delay) &&
time_before_eq64(vtime, now->vnow + vmargin))
return false;
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
/* use delay */
if (cost) {
u64 cost_ns = DIV64_U64_ROUND_UP(cost * NSEC_PER_USEC,
now->vrate);
blkcg_add_delay(blkg, now->now_ns, cost_ns);
}
blkcg_use_delay(blkg);
expires = now->now_ns + DIV64_U64_ROUND_UP(vtime - now->vnow,
now->vrate) * NSEC_PER_USEC;
/* if already active and close enough, don't bother */
oexpires = ktime_to_ns(hrtimer_get_softexpires(&iocg->delay_timer));
if (hrtimer_is_queued(&iocg->delay_timer) &&
abs(oexpires - expires) <= margin_ns / 4)
return true;
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
hrtimer_start_range_ns(&iocg->delay_timer, ns_to_ktime(expires),
margin_ns / 4, HRTIMER_MODE_ABS);
return true;
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
}
static enum hrtimer_restart iocg_delay_timer_fn(struct hrtimer *timer)
{
struct ioc_gq *iocg = container_of(timer, struct ioc_gq, delay_timer);
struct ioc_now now;
ioc_now(iocg->ioc, &now);
iocg_kick_delay(iocg, &now, 0);
return HRTIMER_NORESTART;
}
static void ioc_lat_stat(struct ioc *ioc, u32 *missed_ppm_ar, u32 *rq_wait_pct_p)
{
u32 nr_met[2] = { };
u32 nr_missed[2] = { };
u64 rq_wait_ns = 0;
int cpu, rw;
for_each_online_cpu(cpu) {
struct ioc_pcpu_stat *stat = per_cpu_ptr(ioc->pcpu_stat, cpu);
u64 this_rq_wait_ns;
for (rw = READ; rw <= WRITE; rw++) {
u32 this_met = READ_ONCE(stat->missed[rw].nr_met);
u32 this_missed = READ_ONCE(stat->missed[rw].nr_missed);
nr_met[rw] += this_met - stat->missed[rw].last_met;
nr_missed[rw] += this_missed - stat->missed[rw].last_missed;
stat->missed[rw].last_met = this_met;
stat->missed[rw].last_missed = this_missed;
}
this_rq_wait_ns = READ_ONCE(stat->rq_wait_ns);
rq_wait_ns += this_rq_wait_ns - stat->last_rq_wait_ns;
stat->last_rq_wait_ns = this_rq_wait_ns;
}
for (rw = READ; rw <= WRITE; rw++) {
if (nr_met[rw] + nr_missed[rw])
missed_ppm_ar[rw] =
DIV64_U64_ROUND_UP((u64)nr_missed[rw] * MILLION,
nr_met[rw] + nr_missed[rw]);
else
missed_ppm_ar[rw] = 0;
}
*rq_wait_pct_p = div64_u64(rq_wait_ns * 100,
ioc->period_us * NSEC_PER_USEC);
}
/* was iocg idle this period? */
static bool iocg_is_idle(struct ioc_gq *iocg)
{
struct ioc *ioc = iocg->ioc;
/* did something get issued this period? */
if (atomic64_read(&iocg->active_period) ==
atomic64_read(&ioc->cur_period))
return false;
/* is something in flight? */
if (atomic64_read(&iocg->done_vtime) < atomic64_read(&iocg->vtime))
return false;
return true;
}
/* returns usage with margin added if surplus is large enough */
static u32 surplus_adjusted_hweight_inuse(u32 usage, u32 hw_inuse)
{
/* add margin */
usage = DIV_ROUND_UP(usage * SURPLUS_SCALE_PCT, 100);
usage += SURPLUS_SCALE_ABS;
/* don't bother if the surplus is too small */
if (usage + SURPLUS_MIN_ADJ_DELTA > hw_inuse)
return 0;
return usage;
}
static void ioc_timer_fn(struct timer_list *timer)
{
struct ioc *ioc = container_of(timer, struct ioc, timer);
struct ioc_gq *iocg, *tiocg;
struct ioc_now now;
int nr_surpluses = 0, nr_shortages = 0, nr_lagging = 0;
u32 ppm_rthr = MILLION - ioc->params.qos[QOS_RPPM];
u32 ppm_wthr = MILLION - ioc->params.qos[QOS_WPPM];
u32 missed_ppm[2], rq_wait_pct;
u64 period_vtime;
int prev_busy_level, i;
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
/* how were the latencies during the period? */
ioc_lat_stat(ioc, missed_ppm, &rq_wait_pct);
/* take care of active iocgs */
spin_lock_irq(&ioc->lock);
ioc_now(ioc, &now);
period_vtime = now.vnow - ioc->period_at_vtime;
if (WARN_ON_ONCE(!period_vtime)) {
spin_unlock_irq(&ioc->lock);
return;
}
/*
* Waiters determine the sleep durations based on the vrate they
* saw at the time of sleep. If vrate has increased, some waiters
* could be sleeping for too long. Wake up tardy waiters which
* should have woken up in the last period and expire idle iocgs.
*/
list_for_each_entry_safe(iocg, tiocg, &ioc->active_iocgs, active_list) {
blk-iocost: Account force-charged overage in absolute vtime Currently, when a bio needs to be force-charged and there isn't enough budget, vtime is simply pushed into the future. This means that the cost of the whole bio is scaled using the current hweight and then charged immediately. Until the global vtime advances beyond this future vtime, the cgroup won't be allowed to issue normal IOs. This is incorrect and can lead to, for example, exploding vrate or extended stalls if vrate range is constrained. Consider the following scenario. 1. A cgroup with a very low hweight runs out of budget. 2. A storm of swap-out happens on it. All of them are scaled according to the current low hweight and charged to vtime pushing it to a far future. 3. All other cgroups go idle and now the above cgroup has access to the whole device. However, because vtime is already wound using the past low hweight, what its current hweight is doesn't matter until global vtime catches up to the local vtime. 4. As a result, either vrate gets ramped up extremely or the IOs stall while the underlying device is idle. This is because the hweight the overage is calculated at is different from the hweight that it's being paid at. Fix it by remembering the overage in absoulte vtime and continuously paying with the actual budget according to the current hweight at each period. Note that non-forced bios which wait already remembers the cost in absolute vtime. This brings forced-bio accounting in line. Signed-off-by: Tejun Heo <tj@kernel.org> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-09-04 22:45:52 +03:00
if (!waitqueue_active(&iocg->waitq) &&
!atomic64_read(&iocg->abs_vdebt) && !iocg_is_idle(iocg))
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
continue;
spin_lock(&iocg->waitq.lock);
blk-iocost: Account force-charged overage in absolute vtime Currently, when a bio needs to be force-charged and there isn't enough budget, vtime is simply pushed into the future. This means that the cost of the whole bio is scaled using the current hweight and then charged immediately. Until the global vtime advances beyond this future vtime, the cgroup won't be allowed to issue normal IOs. This is incorrect and can lead to, for example, exploding vrate or extended stalls if vrate range is constrained. Consider the following scenario. 1. A cgroup with a very low hweight runs out of budget. 2. A storm of swap-out happens on it. All of them are scaled according to the current low hweight and charged to vtime pushing it to a far future. 3. All other cgroups go idle and now the above cgroup has access to the whole device. However, because vtime is already wound using the past low hweight, what its current hweight is doesn't matter until global vtime catches up to the local vtime. 4. As a result, either vrate gets ramped up extremely or the IOs stall while the underlying device is idle. This is because the hweight the overage is calculated at is different from the hweight that it's being paid at. Fix it by remembering the overage in absoulte vtime and continuously paying with the actual budget according to the current hweight at each period. Note that non-forced bios which wait already remembers the cost in absolute vtime. This brings forced-bio accounting in line. Signed-off-by: Tejun Heo <tj@kernel.org> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-09-04 22:45:52 +03:00
if (waitqueue_active(&iocg->waitq) ||
atomic64_read(&iocg->abs_vdebt)) {
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
/* might be oversleeping vtime / hweight changes, kick */
iocg_kick_waitq(iocg, &now);
iocg_kick_delay(iocg, &now, 0);
} else if (iocg_is_idle(iocg)) {
/* no waiter and idle, deactivate */
iocg->last_inuse = iocg->inuse;
__propagate_active_weight(iocg, 0, 0);
list_del_init(&iocg->active_list);
}
spin_unlock(&iocg->waitq.lock);
}
commit_active_weights(ioc);
/* calc usages and see whether some weights need to be moved around */
list_for_each_entry(iocg, &ioc->active_iocgs, active_list) {
u64 vdone, vtime, vusage, vmargin, vmin;
u32 hw_active, hw_inuse, usage;
/*
* Collect unused and wind vtime closer to vnow to prevent
* iocgs from accumulating a large amount of budget.
*/
vdone = atomic64_read(&iocg->done_vtime);
vtime = atomic64_read(&iocg->vtime);
current_hweight(iocg, &hw_active, &hw_inuse);
/*
* Latency QoS detection doesn't account for IOs which are
* in-flight for longer than a period. Detect them by
* comparing vdone against period start. If lagging behind
* IOs from past periods, don't increase vrate.
*/
if ((ppm_rthr != MILLION || ppm_wthr != MILLION) &&
!atomic_read(&iocg_to_blkg(iocg)->use_delay) &&
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
time_after64(vtime, vdone) &&
time_after64(vtime, now.vnow -
MAX_LAGGING_PERIODS * period_vtime) &&
time_before64(vdone, now.vnow - period_vtime))
nr_lagging++;
if (waitqueue_active(&iocg->waitq))
vusage = now.vnow - iocg->last_vtime;
else if (time_before64(iocg->last_vtime, vtime))
vusage = vtime - iocg->last_vtime;
else
vusage = 0;
iocg->last_vtime += vusage;
/*
* Factor in in-flight vtime into vusage to avoid
* high-latency completions appearing as idle. This should
* be done after the above ->last_time adjustment.
*/
vusage = max(vusage, vtime - vdone);
/* calculate hweight based usage ratio and record */
if (vusage) {
usage = DIV64_U64_ROUND_UP(vusage * hw_inuse,
period_vtime);
iocg->usage_idx = (iocg->usage_idx + 1) % NR_USAGE_SLOTS;
iocg->usages[iocg->usage_idx] = usage;
} else {
usage = 0;
}
/* see whether there's surplus vtime */
vmargin = ioc->margin_us * now.vrate;
vmin = now.vnow - vmargin;
iocg->has_surplus = false;
if (!waitqueue_active(&iocg->waitq) &&
time_before64(vtime, vmin)) {
u64 delta = vmin - vtime;
/* throw away surplus vtime */
atomic64_add(delta, &iocg->vtime);
atomic64_add(delta, &iocg->done_vtime);
iocg->last_vtime += delta;
/* if usage is sufficiently low, maybe it can donate */
if (surplus_adjusted_hweight_inuse(usage, hw_inuse)) {
iocg->has_surplus = true;
nr_surpluses++;
}
} else if (hw_inuse < hw_active) {
u32 new_hwi, new_inuse;
/* was donating but might need to take back some */
if (waitqueue_active(&iocg->waitq)) {
new_hwi = hw_active;
} else {
new_hwi = max(hw_inuse,
usage * SURPLUS_SCALE_PCT / 100 +
SURPLUS_SCALE_ABS);
}
new_inuse = div64_u64((u64)iocg->inuse * new_hwi,
hw_inuse);
new_inuse = clamp_t(u32, new_inuse, 1, iocg->active);
if (new_inuse > iocg->inuse) {
TRACE_IOCG_PATH(inuse_takeback, iocg, &now,
iocg->inuse, new_inuse,
hw_inuse, new_hwi);
__propagate_active_weight(iocg, iocg->weight,
new_inuse);
}
} else {
/* genuninely out of vtime */
nr_shortages++;
}
}
if (!nr_shortages || !nr_surpluses)
goto skip_surplus_transfers;
/* there are both shortages and surpluses, transfer surpluses */
list_for_each_entry(iocg, &ioc->active_iocgs, active_list) {
u32 usage, hw_active, hw_inuse, new_hwi, new_inuse;
int nr_valid = 0;
if (!iocg->has_surplus)
continue;
/* base the decision on max historical usage */
for (i = 0, usage = 0; i < NR_USAGE_SLOTS; i++) {
if (iocg->usages[i]) {
usage = max(usage, iocg->usages[i]);
nr_valid++;
}
}
if (nr_valid < MIN_VALID_USAGES)
continue;
current_hweight(iocg, &hw_active, &hw_inuse);
new_hwi = surplus_adjusted_hweight_inuse(usage, hw_inuse);
if (!new_hwi)
continue;
new_inuse = DIV64_U64_ROUND_UP((u64)iocg->inuse * new_hwi,
hw_inuse);
if (new_inuse < iocg->inuse) {
TRACE_IOCG_PATH(inuse_giveaway, iocg, &now,
iocg->inuse, new_inuse,
hw_inuse, new_hwi);
__propagate_active_weight(iocg, iocg->weight, new_inuse);
}
}
skip_surplus_transfers:
commit_active_weights(ioc);
/*
* If q is getting clogged or we're missing too much, we're issuing
* too much IO and should lower vtime rate. If we're not missing
* and experiencing shortages but not surpluses, we're too stingy
* and should increase vtime rate.
*/
prev_busy_level = ioc->busy_level;
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
if (rq_wait_pct > RQ_WAIT_BUSY_PCT ||
missed_ppm[READ] > ppm_rthr ||
missed_ppm[WRITE] > ppm_wthr) {
ioc->busy_level = max(ioc->busy_level, 0);
ioc->busy_level++;
} else if (rq_wait_pct <= RQ_WAIT_BUSY_PCT * UNBUSY_THR_PCT / 100 &&
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
missed_ppm[READ] <= ppm_rthr * UNBUSY_THR_PCT / 100 &&
missed_ppm[WRITE] <= ppm_wthr * UNBUSY_THR_PCT / 100) {
/* take action iff there is contention */
if (nr_shortages && !nr_lagging) {
ioc->busy_level = min(ioc->busy_level, 0);
/* redistribute surpluses first */
if (!nr_surpluses)
ioc->busy_level--;
}
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
} else {
ioc->busy_level = 0;
}
ioc->busy_level = clamp(ioc->busy_level, -1000, 1000);
if (ioc->busy_level > 0 || (ioc->busy_level < 0 && !nr_lagging)) {
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
u64 vrate = atomic64_read(&ioc->vtime_rate);
u64 vrate_min = ioc->vrate_min, vrate_max = ioc->vrate_max;
/* rq_wait signal is always reliable, ignore user vrate_min */
if (rq_wait_pct > RQ_WAIT_BUSY_PCT)
vrate_min = VRATE_MIN;
/*
* If vrate is out of bounds, apply clamp gradually as the
* bounds can change abruptly. Otherwise, apply busy_level
* based adjustment.
*/
if (vrate < vrate_min) {
vrate = div64_u64(vrate * (100 + VRATE_CLAMP_ADJ_PCT),
100);
vrate = min(vrate, vrate_min);
} else if (vrate > vrate_max) {
vrate = div64_u64(vrate * (100 - VRATE_CLAMP_ADJ_PCT),
100);
vrate = max(vrate, vrate_max);
} else {
int idx = min_t(int, abs(ioc->busy_level),
ARRAY_SIZE(vrate_adj_pct) - 1);
u32 adj_pct = vrate_adj_pct[idx];
if (ioc->busy_level > 0)
adj_pct = 100 - adj_pct;
else
adj_pct = 100 + adj_pct;
vrate = clamp(DIV64_U64_ROUND_UP(vrate * adj_pct, 100),
vrate_min, vrate_max);
}
trace_iocost_ioc_vrate_adj(ioc, vrate, &missed_ppm, rq_wait_pct,
nr_lagging, nr_shortages,
nr_surpluses);
atomic64_set(&ioc->vtime_rate, vrate);
ioc->inuse_margin_vtime = DIV64_U64_ROUND_UP(
ioc->period_us * vrate * INUSE_MARGIN_PCT, 100);
} else if (ioc->busy_level != prev_busy_level || nr_lagging) {
trace_iocost_ioc_vrate_adj(ioc, atomic64_read(&ioc->vtime_rate),
&missed_ppm, rq_wait_pct, nr_lagging,
nr_shortages, nr_surpluses);
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
}
ioc_refresh_params(ioc, false);
/*
* This period is done. Move onto the next one. If nothing's
* going on with the device, stop the timer.
*/
atomic64_inc(&ioc->cur_period);
if (ioc->running != IOC_STOP) {
if (!list_empty(&ioc->active_iocgs)) {
ioc_start_period(ioc, &now);
} else {
ioc->busy_level = 0;
ioc->running = IOC_IDLE;
}
}
spin_unlock_irq(&ioc->lock);
}
static void calc_vtime_cost_builtin(struct bio *bio, struct ioc_gq *iocg,
bool is_merge, u64 *costp)
{
struct ioc *ioc = iocg->ioc;
u64 coef_seqio, coef_randio, coef_page;
u64 pages = max_t(u64, bio_sectors(bio) >> IOC_SECT_TO_PAGE_SHIFT, 1);
u64 seek_pages = 0;
u64 cost = 0;
switch (bio_op(bio)) {
case REQ_OP_READ:
coef_seqio = ioc->params.lcoefs[LCOEF_RSEQIO];
coef_randio = ioc->params.lcoefs[LCOEF_RRANDIO];
coef_page = ioc->params.lcoefs[LCOEF_RPAGE];
break;
case REQ_OP_WRITE:
coef_seqio = ioc->params.lcoefs[LCOEF_WSEQIO];
coef_randio = ioc->params.lcoefs[LCOEF_WRANDIO];
coef_page = ioc->params.lcoefs[LCOEF_WPAGE];
break;
default:
goto out;
}
if (iocg->cursor) {
seek_pages = abs(bio->bi_iter.bi_sector - iocg->cursor);
seek_pages >>= IOC_SECT_TO_PAGE_SHIFT;
}
if (!is_merge) {
if (seek_pages > LCOEF_RANDIO_PAGES) {
cost += coef_randio;
} else {
cost += coef_seqio;
}
}
cost += pages * coef_page;
out:
*costp = cost;
}
static u64 calc_vtime_cost(struct bio *bio, struct ioc_gq *iocg, bool is_merge)
{
u64 cost;
calc_vtime_cost_builtin(bio, iocg, is_merge, &cost);
return cost;
}
static void ioc_rqos_throttle(struct rq_qos *rqos, struct bio *bio)
{
struct blkcg_gq *blkg = bio->bi_blkg;
struct ioc *ioc = rqos_to_ioc(rqos);
struct ioc_gq *iocg = blkg_to_iocg(blkg);
struct ioc_now now;
struct iocg_wait wait;
u32 hw_active, hw_inuse;
u64 abs_cost, cost, vtime;
/* bypass IOs if disabled or for root cgroup */
if (!ioc->enabled || !iocg->level)
return;
/* always activate so that even 0 cost IOs get protected to some level */
if (!iocg_activate(iocg, &now))
return;
/* calculate the absolute vtime cost */
abs_cost = calc_vtime_cost(bio, iocg, false);
if (!abs_cost)
return;
iocg->cursor = bio_end_sector(bio);
vtime = atomic64_read(&iocg->vtime);
current_hweight(iocg, &hw_active, &hw_inuse);
if (hw_inuse < hw_active &&
time_after_eq64(vtime + ioc->inuse_margin_vtime, now.vnow)) {
TRACE_IOCG_PATH(inuse_reset, iocg, &now,
iocg->inuse, iocg->weight, hw_inuse, hw_active);
spin_lock_irq(&ioc->lock);
propagate_active_weight(iocg, iocg->weight, iocg->weight);
spin_unlock_irq(&ioc->lock);
current_hweight(iocg, &hw_active, &hw_inuse);
}
cost = abs_cost_to_cost(abs_cost, hw_inuse);
/*
* If no one's waiting and within budget, issue right away. The
* tests are racy but the races aren't systemic - we only miss once
* in a while which is fine.
*/
if (!waitqueue_active(&iocg->waitq) &&
blk-iocost: Account force-charged overage in absolute vtime Currently, when a bio needs to be force-charged and there isn't enough budget, vtime is simply pushed into the future. This means that the cost of the whole bio is scaled using the current hweight and then charged immediately. Until the global vtime advances beyond this future vtime, the cgroup won't be allowed to issue normal IOs. This is incorrect and can lead to, for example, exploding vrate or extended stalls if vrate range is constrained. Consider the following scenario. 1. A cgroup with a very low hweight runs out of budget. 2. A storm of swap-out happens on it. All of them are scaled according to the current low hweight and charged to vtime pushing it to a far future. 3. All other cgroups go idle and now the above cgroup has access to the whole device. However, because vtime is already wound using the past low hweight, what its current hweight is doesn't matter until global vtime catches up to the local vtime. 4. As a result, either vrate gets ramped up extremely or the IOs stall while the underlying device is idle. This is because the hweight the overage is calculated at is different from the hweight that it's being paid at. Fix it by remembering the overage in absoulte vtime and continuously paying with the actual budget according to the current hweight at each period. Note that non-forced bios which wait already remembers the cost in absolute vtime. This brings forced-bio accounting in line. Signed-off-by: Tejun Heo <tj@kernel.org> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-09-04 22:45:52 +03:00
!atomic64_read(&iocg->abs_vdebt) &&
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
time_before_eq64(vtime + cost, now.vnow)) {
iocg_commit_bio(iocg, bio, cost);
return;
}
blk-iocost: Account force-charged overage in absolute vtime Currently, when a bio needs to be force-charged and there isn't enough budget, vtime is simply pushed into the future. This means that the cost of the whole bio is scaled using the current hweight and then charged immediately. Until the global vtime advances beyond this future vtime, the cgroup won't be allowed to issue normal IOs. This is incorrect and can lead to, for example, exploding vrate or extended stalls if vrate range is constrained. Consider the following scenario. 1. A cgroup with a very low hweight runs out of budget. 2. A storm of swap-out happens on it. All of them are scaled according to the current low hweight and charged to vtime pushing it to a far future. 3. All other cgroups go idle and now the above cgroup has access to the whole device. However, because vtime is already wound using the past low hweight, what its current hweight is doesn't matter until global vtime catches up to the local vtime. 4. As a result, either vrate gets ramped up extremely or the IOs stall while the underlying device is idle. This is because the hweight the overage is calculated at is different from the hweight that it's being paid at. Fix it by remembering the overage in absoulte vtime and continuously paying with the actual budget according to the current hweight at each period. Note that non-forced bios which wait already remembers the cost in absolute vtime. This brings forced-bio accounting in line. Signed-off-by: Tejun Heo <tj@kernel.org> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-09-04 22:45:52 +03:00
/*
* We're over budget. If @bio has to be issued regardless,
* remember the abs_cost instead of advancing vtime.
* iocg_kick_waitq() will pay off the debt before waking more IOs.
* This way, the debt is continuously paid off each period with the
* actual budget available to the cgroup. If we just wound vtime,
* we would incorrectly use the current hw_inuse for the entire
* amount which, for example, can lead to the cgroup staying
* blocked for a long time even with substantially raised hw_inuse.
*/
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
if (bio_issue_as_root_blkg(bio) || fatal_signal_pending(current)) {
blk-iocost: Account force-charged overage in absolute vtime Currently, when a bio needs to be force-charged and there isn't enough budget, vtime is simply pushed into the future. This means that the cost of the whole bio is scaled using the current hweight and then charged immediately. Until the global vtime advances beyond this future vtime, the cgroup won't be allowed to issue normal IOs. This is incorrect and can lead to, for example, exploding vrate or extended stalls if vrate range is constrained. Consider the following scenario. 1. A cgroup with a very low hweight runs out of budget. 2. A storm of swap-out happens on it. All of them are scaled according to the current low hweight and charged to vtime pushing it to a far future. 3. All other cgroups go idle and now the above cgroup has access to the whole device. However, because vtime is already wound using the past low hweight, what its current hweight is doesn't matter until global vtime catches up to the local vtime. 4. As a result, either vrate gets ramped up extremely or the IOs stall while the underlying device is idle. This is because the hweight the overage is calculated at is different from the hweight that it's being paid at. Fix it by remembering the overage in absoulte vtime and continuously paying with the actual budget according to the current hweight at each period. Note that non-forced bios which wait already remembers the cost in absolute vtime. This brings forced-bio accounting in line. Signed-off-by: Tejun Heo <tj@kernel.org> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-09-04 22:45:52 +03:00
atomic64_add(abs_cost, &iocg->abs_vdebt);
if (iocg_kick_delay(iocg, &now, cost))
blkcg_schedule_throttle(rqos->q,
(bio->bi_opf & REQ_SWAP) == REQ_SWAP);
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
return;
}
/*
* Append self to the waitq and schedule the wakeup timer if we're
* the first waiter. The timer duration is calculated based on the
* current vrate. vtime and hweight changes can make it too short
* or too long. Each wait entry records the absolute cost it's
* waiting for to allow re-evaluation using a custom wait entry.
*
* If too short, the timer simply reschedules itself. If too long,
* the period timer will notice and trigger wakeups.
*
* All waiters are on iocg->waitq and the wait states are
* synchronized using waitq.lock.
*/
spin_lock_irq(&iocg->waitq.lock);
/*
* We activated above but w/o any synchronization. Deactivation is
* synchronized with waitq.lock and we won't get deactivated as
* long as we're waiting, so we're good if we're activated here.
* In the unlikely case that we are deactivated, just issue the IO.
*/
if (unlikely(list_empty(&iocg->active_list))) {
spin_unlock_irq(&iocg->waitq.lock);
iocg_commit_bio(iocg, bio, cost);
return;
}
init_waitqueue_func_entry(&wait.wait, iocg_wake_fn);
wait.wait.private = current;
wait.bio = bio;
wait.abs_cost = abs_cost;
wait.committed = false; /* will be set true by waker */
__add_wait_queue_entry_tail(&iocg->waitq, &wait.wait);
iocg_kick_waitq(iocg, &now);
spin_unlock_irq(&iocg->waitq.lock);
while (true) {
set_current_state(TASK_UNINTERRUPTIBLE);
if (wait.committed)
break;
io_schedule();
}
/* waker already committed us, proceed */
finish_wait(&iocg->waitq, &wait.wait);
}
static void ioc_rqos_merge(struct rq_qos *rqos, struct request *rq,
struct bio *bio)
{
struct ioc_gq *iocg = blkg_to_iocg(bio->bi_blkg);
struct ioc *ioc = iocg->ioc;
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
sector_t bio_end = bio_end_sector(bio);
struct ioc_now now;
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
u32 hw_inuse;
u64 abs_cost, cost;
/* bypass if disabled or for root cgroup */
if (!ioc->enabled || !iocg->level)
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
return;
abs_cost = calc_vtime_cost(bio, iocg, true);
if (!abs_cost)
return;
ioc_now(ioc, &now);
current_hweight(iocg, NULL, &hw_inuse);
cost = abs_cost_to_cost(abs_cost, hw_inuse);
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
/* update cursor if backmerging into the request at the cursor */
if (blk_rq_pos(rq) < bio_end &&
blk_rq_pos(rq) + blk_rq_sectors(rq) == iocg->cursor)
iocg->cursor = bio_end;
/*
* Charge if there's enough vtime budget and the existing request
* has cost assigned. Otherwise, account it as debt. See debt
* handling in ioc_rqos_throttle() for details.
*/
if (rq->bio && rq->bio->bi_iocost_cost &&
time_before_eq64(atomic64_read(&iocg->vtime) + cost, now.vnow))
iocg_commit_bio(iocg, bio, cost);
else
atomic64_add(abs_cost, &iocg->abs_vdebt);
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
}
static void ioc_rqos_done_bio(struct rq_qos *rqos, struct bio *bio)
{
struct ioc_gq *iocg = blkg_to_iocg(bio->bi_blkg);
if (iocg && bio->bi_iocost_cost)
atomic64_add(bio->bi_iocost_cost, &iocg->done_vtime);
}
static void ioc_rqos_done(struct rq_qos *rqos, struct request *rq)
{
struct ioc *ioc = rqos_to_ioc(rqos);
u64 on_q_ns, rq_wait_ns;
int pidx, rw;
if (!ioc->enabled || !rq->alloc_time_ns || !rq->start_time_ns)
return;
switch (req_op(rq) & REQ_OP_MASK) {
case REQ_OP_READ:
pidx = QOS_RLAT;
rw = READ;
break;
case REQ_OP_WRITE:
pidx = QOS_WLAT;
rw = WRITE;
break;
default:
return;
}
on_q_ns = ktime_get_ns() - rq->alloc_time_ns;
rq_wait_ns = rq->start_time_ns - rq->alloc_time_ns;
if (on_q_ns <= ioc->params.qos[pidx] * NSEC_PER_USEC)
this_cpu_inc(ioc->pcpu_stat->missed[rw].nr_met);
else
this_cpu_inc(ioc->pcpu_stat->missed[rw].nr_missed);
this_cpu_add(ioc->pcpu_stat->rq_wait_ns, rq_wait_ns);
}
static void ioc_rqos_queue_depth_changed(struct rq_qos *rqos)
{
struct ioc *ioc = rqos_to_ioc(rqos);
spin_lock_irq(&ioc->lock);
ioc_refresh_params(ioc, false);
spin_unlock_irq(&ioc->lock);
}
static void ioc_rqos_exit(struct rq_qos *rqos)
{
struct ioc *ioc = rqos_to_ioc(rqos);
blkcg_deactivate_policy(rqos->q, &blkcg_policy_iocost);
spin_lock_irq(&ioc->lock);
ioc->running = IOC_STOP;
spin_unlock_irq(&ioc->lock);
del_timer_sync(&ioc->timer);
free_percpu(ioc->pcpu_stat);
kfree(ioc);
}
static struct rq_qos_ops ioc_rqos_ops = {
.throttle = ioc_rqos_throttle,
.merge = ioc_rqos_merge,
.done_bio = ioc_rqos_done_bio,
.done = ioc_rqos_done,
.queue_depth_changed = ioc_rqos_queue_depth_changed,
.exit = ioc_rqos_exit,
};
static int blk_iocost_init(struct request_queue *q)
{
struct ioc *ioc;
struct rq_qos *rqos;
int ret;
ioc = kzalloc(sizeof(*ioc), GFP_KERNEL);
if (!ioc)
return -ENOMEM;
ioc->pcpu_stat = alloc_percpu(struct ioc_pcpu_stat);
if (!ioc->pcpu_stat) {
kfree(ioc);
return -ENOMEM;
}
rqos = &ioc->rqos;
rqos->id = RQ_QOS_COST;
rqos->ops = &ioc_rqos_ops;
rqos->q = q;
spin_lock_init(&ioc->lock);
timer_setup(&ioc->timer, ioc_timer_fn, 0);
INIT_LIST_HEAD(&ioc->active_iocgs);
ioc->running = IOC_IDLE;
atomic64_set(&ioc->vtime_rate, VTIME_PER_USEC);
seqcount_init(&ioc->period_seqcount);
ioc->period_at = ktime_to_us(ktime_get());
atomic64_set(&ioc->cur_period, 0);
atomic_set(&ioc->hweight_gen, 0);
spin_lock_irq(&ioc->lock);
ioc->autop_idx = AUTOP_INVALID;
ioc_refresh_params(ioc, true);
spin_unlock_irq(&ioc->lock);
rq_qos_add(q, rqos);
ret = blkcg_activate_policy(q, &blkcg_policy_iocost);
if (ret) {
rq_qos_del(q, rqos);
free_percpu(ioc->pcpu_stat);
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
kfree(ioc);
return ret;
}
return 0;
}
static struct blkcg_policy_data *ioc_cpd_alloc(gfp_t gfp)
{
struct ioc_cgrp *iocc;
iocc = kzalloc(sizeof(struct ioc_cgrp), gfp);
if (!iocc)
return NULL;
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
iocc->dfl_weight = CGROUP_WEIGHT_DFL;
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
return &iocc->cpd;
}
static void ioc_cpd_free(struct blkcg_policy_data *cpd)
{
kfree(container_of(cpd, struct ioc_cgrp, cpd));
}
static struct blkg_policy_data *ioc_pd_alloc(gfp_t gfp, struct request_queue *q,
struct blkcg *blkcg)
{
int levels = blkcg->css.cgroup->level + 1;
struct ioc_gq *iocg;
iocg = kzalloc_node(sizeof(*iocg) + levels * sizeof(iocg->ancestors[0]),
gfp, q->node);
if (!iocg)
return NULL;
return &iocg->pd;
}
static void ioc_pd_init(struct blkg_policy_data *pd)
{
struct ioc_gq *iocg = pd_to_iocg(pd);
struct blkcg_gq *blkg = pd_to_blkg(&iocg->pd);
struct ioc *ioc = q_to_ioc(blkg->q);
struct ioc_now now;
struct blkcg_gq *tblkg;
unsigned long flags;
ioc_now(ioc, &now);
iocg->ioc = ioc;
atomic64_set(&iocg->vtime, now.vnow);
atomic64_set(&iocg->done_vtime, now.vnow);
blk-iocost: Account force-charged overage in absolute vtime Currently, when a bio needs to be force-charged and there isn't enough budget, vtime is simply pushed into the future. This means that the cost of the whole bio is scaled using the current hweight and then charged immediately. Until the global vtime advances beyond this future vtime, the cgroup won't be allowed to issue normal IOs. This is incorrect and can lead to, for example, exploding vrate or extended stalls if vrate range is constrained. Consider the following scenario. 1. A cgroup with a very low hweight runs out of budget. 2. A storm of swap-out happens on it. All of them are scaled according to the current low hweight and charged to vtime pushing it to a far future. 3. All other cgroups go idle and now the above cgroup has access to the whole device. However, because vtime is already wound using the past low hweight, what its current hweight is doesn't matter until global vtime catches up to the local vtime. 4. As a result, either vrate gets ramped up extremely or the IOs stall while the underlying device is idle. This is because the hweight the overage is calculated at is different from the hweight that it's being paid at. Fix it by remembering the overage in absoulte vtime and continuously paying with the actual budget according to the current hweight at each period. Note that non-forced bios which wait already remembers the cost in absolute vtime. This brings forced-bio accounting in line. Signed-off-by: Tejun Heo <tj@kernel.org> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-09-04 22:45:52 +03:00
atomic64_set(&iocg->abs_vdebt, 0);
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
atomic64_set(&iocg->active_period, atomic64_read(&ioc->cur_period));
INIT_LIST_HEAD(&iocg->active_list);
iocg->hweight_active = HWEIGHT_WHOLE;
iocg->hweight_inuse = HWEIGHT_WHOLE;
init_waitqueue_head(&iocg->waitq);
hrtimer_init(&iocg->waitq_timer, CLOCK_MONOTONIC, HRTIMER_MODE_ABS);
iocg->waitq_timer.function = iocg_waitq_timer_fn;
hrtimer_init(&iocg->delay_timer, CLOCK_MONOTONIC, HRTIMER_MODE_ABS);
iocg->delay_timer.function = iocg_delay_timer_fn;
iocg->level = blkg->blkcg->css.cgroup->level;
for (tblkg = blkg; tblkg; tblkg = tblkg->parent) {
struct ioc_gq *tiocg = blkg_to_iocg(tblkg);
iocg->ancestors[tiocg->level] = tiocg;
}
spin_lock_irqsave(&ioc->lock, flags);
weight_updated(iocg);
spin_unlock_irqrestore(&ioc->lock, flags);
}
static void ioc_pd_free(struct blkg_policy_data *pd)
{
struct ioc_gq *iocg = pd_to_iocg(pd);
struct ioc *ioc = iocg->ioc;
if (ioc) {
spin_lock(&ioc->lock);
if (!list_empty(&iocg->active_list)) {
propagate_active_weight(iocg, 0, 0);
list_del_init(&iocg->active_list);
}
spin_unlock(&ioc->lock);
2019-09-10 19:15:25 +03:00
hrtimer_cancel(&iocg->waitq_timer);
hrtimer_cancel(&iocg->delay_timer);
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
}
kfree(iocg);
}
static u64 ioc_weight_prfill(struct seq_file *sf, struct blkg_policy_data *pd,
int off)
{
const char *dname = blkg_dev_name(pd->blkg);
struct ioc_gq *iocg = pd_to_iocg(pd);
if (dname && iocg->cfg_weight)
seq_printf(sf, "%s %u\n", dname, iocg->cfg_weight);
return 0;
}
static int ioc_weight_show(struct seq_file *sf, void *v)
{
struct blkcg *blkcg = css_to_blkcg(seq_css(sf));
struct ioc_cgrp *iocc = blkcg_to_iocc(blkcg);
seq_printf(sf, "default %u\n", iocc->dfl_weight);
blkcg_print_blkgs(sf, blkcg, ioc_weight_prfill,
&blkcg_policy_iocost, seq_cft(sf)->private, false);
return 0;
}
static ssize_t ioc_weight_write(struct kernfs_open_file *of, char *buf,
size_t nbytes, loff_t off)
{
struct blkcg *blkcg = css_to_blkcg(of_css(of));
struct ioc_cgrp *iocc = blkcg_to_iocc(blkcg);
struct blkg_conf_ctx ctx;
struct ioc_gq *iocg;
u32 v;
int ret;
if (!strchr(buf, ':')) {
struct blkcg_gq *blkg;
if (!sscanf(buf, "default %u", &v) && !sscanf(buf, "%u", &v))
return -EINVAL;
if (v < CGROUP_WEIGHT_MIN || v > CGROUP_WEIGHT_MAX)
return -EINVAL;
spin_lock(&blkcg->lock);
iocc->dfl_weight = v;
hlist_for_each_entry(blkg, &blkcg->blkg_list, blkcg_node) {
struct ioc_gq *iocg = blkg_to_iocg(blkg);
if (iocg) {
spin_lock_irq(&iocg->ioc->lock);
weight_updated(iocg);
spin_unlock_irq(&iocg->ioc->lock);
}
}
spin_unlock(&blkcg->lock);
return nbytes;
}
ret = blkg_conf_prep(blkcg, &blkcg_policy_iocost, buf, &ctx);
if (ret)
return ret;
iocg = blkg_to_iocg(ctx.blkg);
if (!strncmp(ctx.body, "default", 7)) {
v = 0;
} else {
if (!sscanf(ctx.body, "%u", &v))
goto einval;
if (v < CGROUP_WEIGHT_MIN || v > CGROUP_WEIGHT_MAX)
goto einval;
}
spin_lock(&iocg->ioc->lock);
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
iocg->cfg_weight = v;
weight_updated(iocg);
spin_unlock(&iocg->ioc->lock);
blkcg: implement blk-iocost This patchset implements IO cost model based work-conserving proportional controller. While io.latency provides the capability to comprehensively prioritize and protect IOs depending on the cgroups, its protection is binary - the lowest latency target cgroup which is suffering is protected at the cost of all others. In many use cases including stacking multiple workload containers in a single system, it's necessary to distribute IO capacity with better granularity. One challenge of controlling IO resources is the lack of trivially observable cost metric. The most common metrics - bandwidth and iops - can be off by orders of magnitude depending on the device type and IO pattern. However, the cost isn't a complete mystery. Given several key attributes, we can make fairly reliable predictions on how expensive a given stream of IOs would be, at least compared to other IO patterns. The function which determines the cost of a given IO is the IO cost model for the device. This controller distributes IO capacity based on the costs estimated by such model. The more accurate the cost model the better but the controller adapts based on IO completion latency and as long as the relative costs across differents IO patterns are consistent and sensible, it'll adapt to the actual performance of the device. Currently, the only implemented cost model is a simple linear one with a few sets of default parameters for different classes of device. This covers most common devices reasonably well. All the infrastructure to tune and add different cost models is already in place and a later patch will also allow using bpf progs for cost models. Please see the top comment in blk-iocost.c and documentation for more details. v2: Rebased on top of RQ_ALLOC_TIME changes and folded in Rik's fix for a divide-by-zero bug in current_hweight() triggered by zero inuse_sum. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Andy Newell <newella@fb.com> Cc: Josef Bacik <jbacik@fb.com> Cc: Rik van Riel <riel@surriel.com> Signed-off-by: Jens Axboe <axboe@kernel.dk>
2019-08-29 01:05:58 +03:00
blkg_conf_finish(&ctx);
return nbytes;
einval:
blkg_conf_finish(&ctx);
return -EINVAL;
}
static u64 ioc_qos_prfill(struct seq_file *sf, struct blkg_policy_data *pd,
int off)
{
const char *dname = blkg_dev_name(pd->blkg);
struct ioc *ioc = pd_to_iocg(pd)->ioc;
if (!dname)
return 0;
seq_printf(sf, "%s enable=%d ctrl=%s rpct=%u.%02u rlat=%u wpct=%u.%02u wlat=%u min=%u.%02u max=%u.%02u\n",
dname, ioc->enabled, ioc->user_qos_params ? "user" : "auto",
ioc->params.qos[QOS_RPPM] / 10000,
ioc->params.qos[QOS_RPPM] % 10000 / 100,
ioc->params.qos[QOS_RLAT],
ioc->params.qos[QOS_WPPM] / 10000,
ioc->params.qos[QOS_WPPM] % 10000 / 100,
ioc->params.qos[QOS_WLAT],
ioc->params.qos[QOS_MIN] / 10000,
ioc->params.qos[QOS_MIN] % 10000 / 100,
ioc->params.qos[QOS_MAX] / 10000,
ioc->params.qos[QOS_MAX] % 10000 / 100);
return 0;
}
static int ioc_qos_show(struct seq_file *sf, void *v)
{
struct blkcg *blkcg = css_to_blkcg(seq_css(sf));
blkcg_print_blkgs(sf, blkcg, ioc_qos_prfill,
&blkcg_policy_iocost, seq_cft(sf)->private, false);
return 0;
}
static const match_table_t qos_ctrl_tokens = {
{ QOS_ENABLE, "enable=%u" },
{ QOS_CTRL, "ctrl=%s" },
{ NR_QOS_CTRL_PARAMS, NULL },
};
static const match_table_t qos_tokens = {
{ QOS_RPPM, "rpct=%s" },
{ QOS_RLAT, "rlat=%u" },
{ QOS_WPPM, "wpct=%s" },
{ QOS_WLAT, "wlat=%u" },
{ QOS_MIN, "min=%s" },
{ QOS_MAX, "max=%s" },
{ NR_QOS_PARAMS, NULL },
};
static ssize_t ioc_qos_write(struct kernfs_open_file *of, char *input,
size_t nbytes, loff_t off)
{
struct gendisk *disk;
struct ioc *ioc;
u32 qos[NR_QOS_PARAMS];
bool enable, user;
char *p;
int ret;
disk = blkcg_conf_get_disk(&input);
if (IS_ERR(disk))
return PTR_ERR(disk);
ioc = q_to_ioc(disk->queue);
if (!ioc) {
ret = blk_iocost_init(disk->queue);
if (ret)
goto err;
ioc = q_to_ioc(disk->queue);
}
spin_lock_irq(&ioc->lock);
memcpy(qos, ioc->params.qos, sizeof(qos));
enable = ioc->enabled;
user = ioc->user_qos_params;
spin_unlock_irq(&ioc->lock);
while ((p = strsep(&input, " \t\n"))) {
substring_t args[MAX_OPT_ARGS];
char buf[32];
int tok;
s64 v;
if (!*p)
continue;
switch (match_token(p, qos_ctrl_tokens, args)) {
case QOS_ENABLE:
match_u64(&args[0], &v);
enable = v;
continue;
case QOS_CTRL:
match_strlcpy(buf, &args[0], sizeof(buf));
if (!strcmp(buf, "auto"))
user = false;
else if (!strcmp(buf, "user"))
user = true;
else
goto einval;
continue;
}
tok = match_token(p, qos_tokens, args);
switch (tok) {
case QOS_RPPM:
case QOS_WPPM:
if (match_strlcpy(buf, &args[0], sizeof(buf)) >=
sizeof(buf))
goto einval;
if (cgroup_parse_float(buf, 2, &v))
goto einval;
if (v < 0 || v > 10000)
goto einval;
qos[tok] = v * 100;
break;
case QOS_RLAT:
case QOS_WLAT:
if (match_u64(&args[0], &v))
goto einval;
qos[tok] = v;
break;
case QOS_MIN:
case QOS_MAX:
if (match_strlcpy(buf, &args[0], sizeof(buf)) >=
sizeof(buf))
goto einval;
if (cgroup_parse_float(buf, 2, &v))
goto einval;
if (v < 0)
goto einval;
qos[tok] = clamp_t(s64, v * 100,
VRATE_MIN_PPM, VRATE_MAX_PPM);
break;
default:
goto einval;
}
user = true;
}
if (qos[QOS_MIN] > qos[QOS_MAX])
goto einval;
spin_lock_irq(&ioc->lock);
if (enable) {
blk_queue_flag_set(QUEUE_FLAG_RQ_ALLOC_TIME, ioc->rqos.q);
ioc->enabled = true;
} else {
blk_queue_flag_clear(QUEUE_FLAG_RQ_ALLOC_TIME, ioc->rqos.q);
ioc->enabled = false;
}
if (user) {
memcpy(ioc->params.qos, qos, sizeof(qos));
ioc->user_qos_params = true;
} else {
ioc->user_qos_params = false;
}
ioc_refresh_params(ioc, true);
spin_unlock_irq(&ioc->lock);
put_disk_and_module(disk);
return nbytes;
einval:
ret = -EINVAL;
err:
put_disk_and_module(disk);
return ret;
}
static u64 ioc_cost_model_prfill(struct seq_file *sf,
struct blkg_policy_data *pd, int off)
{
const char *dname = blkg_dev_name(pd->blkg);
struct ioc *ioc = pd_to_iocg(pd)->ioc;
u64 *u = ioc->params.i_lcoefs;
if (!dname)
return 0;
seq_printf(sf, "%s ctrl=%s model=linear "
"rbps=%llu rseqiops=%llu rrandiops=%llu "
"wbps=%llu wseqiops=%llu wrandiops=%llu\n",
dname, ioc->user_cost_model ? "user" : "auto",
u[I_LCOEF_RBPS], u[I_LCOEF_RSEQIOPS], u[I_LCOEF_RRANDIOPS],
u[I_LCOEF_WBPS], u[I_LCOEF_WSEQIOPS], u[I_LCOEF_WRANDIOPS]);
return 0;
}
static int ioc_cost_model_show(struct seq_file *sf, void *v)
{
struct blkcg *blkcg = css_to_blkcg(seq_css(sf));
blkcg_print_blkgs(sf, blkcg, ioc_cost_model_prfill,
&blkcg_policy_iocost, seq_cft(sf)->private, false);
return 0;
}
static const match_table_t cost_ctrl_tokens = {
{ COST_CTRL, "ctrl=%s" },
{ COST_MODEL, "model=%s" },
{ NR_COST_CTRL_PARAMS, NULL },
};
static const match_table_t i_lcoef_tokens = {
{ I_LCOEF_RBPS, "rbps=%u" },
{ I_LCOEF_RSEQIOPS, "rseqiops=%u" },
{ I_LCOEF_RRANDIOPS, "rrandiops=%u" },
{ I_LCOEF_WBPS, "wbps=%u" },
{ I_LCOEF_WSEQIOPS, "wseqiops=%u" },
{ I_LCOEF_WRANDIOPS, "wrandiops=%u" },
{ NR_I_LCOEFS, NULL },
};
static ssize_t ioc_cost_model_write(struct kernfs_open_file *of, char *input,
size_t nbytes, loff_t off)
{
struct gendisk *disk;
struct ioc *ioc;
u64 u[NR_I_LCOEFS];
bool user;
char *p;
int ret;
disk = blkcg_conf_get_disk(&input);
if (IS_ERR(disk))
return PTR_ERR(disk);
ioc = q_to_ioc(disk->queue);
if (!ioc) {
ret = blk_iocost_init(disk->queue);
if (ret)
goto err;
ioc = q_to_ioc(disk->queue);
}
spin_lock_irq(&ioc->lock);
memcpy(u, ioc->params.i_lcoefs, sizeof(u));
user = ioc->user_cost_model;
spin_unlock_irq(&ioc->lock);
while ((p = strsep(&input, " \t\n"))) {
substring_t args[MAX_OPT_ARGS];
char buf[32];
int tok;
u64 v;
if (!*p)
continue;
switch (match_token(p, cost_ctrl_tokens, args)) {
case COST_CTRL:
match_strlcpy(buf, &args[0], sizeof(buf));
if (!strcmp(buf, "auto"))
user = false;
else if (!strcmp(buf, "user"))
user = true;
else
goto einval;
continue;
case COST_MODEL:
match_strlcpy(buf, &args[0], sizeof(buf));
if (strcmp(buf, "linear"))
goto einval;
continue;
}
tok = match_token(p, i_lcoef_tokens, args);
if (tok == NR_I_LCOEFS)
goto einval;
if (match_u64(&args[0], &v))
goto einval;
u[tok] = v;
user = true;
}
spin_lock_irq(&ioc->lock);
if (user) {
memcpy(ioc->params.i_lcoefs, u, sizeof(u));
ioc->user_cost_model = true;
} else {
ioc->user_cost_model = false;
}
ioc_refresh_params(ioc, true);
spin_unlock_irq(&ioc->lock);
put_disk_and_module(disk);
return nbytes;
einval:
ret = -EINVAL;
err:
put_disk_and_module(disk);
return ret;
}
static struct cftype ioc_files[] = {
{
.name = "weight",
.flags = CFTYPE_NOT_ON_ROOT,
.seq_show = ioc_weight_show,
.write = ioc_weight_write,
},
{
.name = "cost.qos",
.flags = CFTYPE_ONLY_ON_ROOT,
.seq_show = ioc_qos_show,
.write = ioc_qos_write,
},
{
.name = "cost.model",
.flags = CFTYPE_ONLY_ON_ROOT,
.seq_show = ioc_cost_model_show,
.write = ioc_cost_model_write,
},
{}
};
static struct blkcg_policy blkcg_policy_iocost = {
.dfl_cftypes = ioc_files,
.cpd_alloc_fn = ioc_cpd_alloc,
.cpd_free_fn = ioc_cpd_free,
.pd_alloc_fn = ioc_pd_alloc,
.pd_init_fn = ioc_pd_init,
.pd_free_fn = ioc_pd_free,
};
static int __init ioc_init(void)
{
return blkcg_policy_register(&blkcg_policy_iocost);
}
static void __exit ioc_exit(void)
{
return blkcg_policy_unregister(&blkcg_policy_iocost);
}
module_init(ioc_init);
module_exit(ioc_exit);