€•ú[      Œsphinx.addnodes”Œdocument”“”)”}”(Œ	rawsource”Œ ”Œchildren”]”(Œtranslations”ŒLanguagesNode”“”)”}”(hhh]”(h Œpending_xref”“”)”}”(hhh]”Œdocutils.nodes”ŒText”“”ŒChinese (Simplified)”…””}”Œparent”hsbaŒ
attributes”}”(Œids”]”Œclasses”]”Œnames”]”Œdupnames”]”Œbackrefs”]”Œ	refdomain”Œstd”Œreftype”Œdoc”Œ	reftarget”Œ'/translations/zh_CN/scheduler/schedutil”Œmodname”NŒ	classname”NŒrefexplicit”ˆuŒtagname”hhhubh)”}”(hhh]”hŒChinese (Traditional)”…””}”hh2sbah}”(h]”h ]”h"]”h$]”h&]”Œ	refdomain”h)Œreftype”h+Œ	reftarget”Œ'/translations/zh_TW/scheduler/schedutil”Œmodname”NŒ	classname”NŒrefexplicit”ˆuh1hhhubh)”}”(hhh]”hŒItalian”…””}”hhFsbah}”(h]”h ]”h"]”h$]”h&]”Œ	refdomain”h)Œreftype”h+Œ	reftarget”Œ'/translations/it_IT/scheduler/schedutil”Œmodname”NŒ	classname”NŒrefexplicit”ˆuh1hhhubh)”}”(hhh]”hŒJapanese”…””}”hhZsbah}”(h]”h ]”h"]”h$]”h&]”Œ	refdomain”h)Œreftype”h+Œ	reftarget”Œ'/translations/ja_JP/scheduler/schedutil”Œmodname”NŒ	classname”NŒrefexplicit”ˆuh1hhhubh)”}”(hhh]”hŒKorean”…””}”hhnsbah}”(h]”h ]”h"]”h$]”h&]”Œ	refdomain”h)Œreftype”h+Œ	reftarget”Œ'/translations/ko_KR/scheduler/schedutil”Œmodname”NŒ	classname”NŒrefexplicit”ˆuh1hhhubh)”}”(hhh]”hŒSpanish”…””}”hh‚sbah}”(h]”h ]”h"]”h$]”h&]”Œ	refdomain”h)Œreftype”h+Œ	reftarget”Œ'/translations/sp_SP/scheduler/schedutil”Œmodname”NŒ	classname”NŒrefexplicit”ˆuh1hhhubeh}”(h]”h ]”h"]”h$]”h&]”Œcurrent_language”ŒEnglish”uh1h
hhŒ	_document”hŒsource”NŒline”NubhŒsection”“”)”}”(hhh]”(hŒtitle”“”)”}”(hŒ	Schedutil”h]”hŒ	Schedutil”…””}”(hh¨hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h¦hh£hžhhŸŒA/var/lib/git/docbuild/linux/Documentation/scheduler/schedutil.rst”h KubhŒnote”“”)”}”(hŒŠAll this assumes a linear relation between frequency and work capacity,
we know this is flawed, but it is the best workable approximation.”h]”hŒ	paragraph”“”)”}”(hŒŠAll this assumes a linear relation between frequency and work capacity,
we know this is flawed, but it is the best workable approximation.”h]”hŒŠAll this assumes a linear relation between frequency and work capacity,
we know this is flawed, but it is the best workable approximation.”…””}”(hh¿hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h½hŸh¶h Khh¹ubah}”(h]”h ]”h"]”h$]”h&]”uh1h·hh£hžhhŸh¶h Nubh¢)”}”(hhh]”(h§)”}”(hŒPELT (Per Entity Load Tracking)”h]”hŒPELT (Per Entity Load Tracking)”…””}”(hhÖhžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h¦hhÓhžhhŸh¶h Kubh¾)”}”(hXk  With PELT we track some metrics across the various scheduler entities, from
individual tasks to task-group slices to CPU runqueues. As the basis for this
we use an Exponentially Weighted Moving Average (EWMA), each period (1024us)
is decayed such that y^32 = 0.5. That is, the most recent 32ms contribute
half, while the rest of history contribute the other half.”h]”hXk  With PELT we track some metrics across the various scheduler entities, from
individual tasks to task-group slices to CPU runqueues. As the basis for this
we use an Exponentially Weighted Moving Average (EWMA), each period (1024us)
is decayed such that y^32 = 0.5. That is, the most recent 32ms contribute
half, while the rest of history contribute the other half.”…””}”(hhähžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h½hŸh¶h KhhÓhžhubh¾)”}”(hŒSpecifically:”h]”hŒSpecifically:”…””}”(hhòhžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h½hŸh¶h KhhÓhžhubhŒblock_quote”“”)”}”(hŒPewma_sum(u) := u_0 + u_1*y + u_2*y^2 + ...

ewma(u) = ewma_sum(u) / ewma_sum(1)
”h]”(h¾)”}”(hŒ*ewma_sum(u) := u_0 + u_1*y + u_2*y^2 + ...”h]”hŒ*ewma_sum(u) := u_0 + u_1*y + u_2*y^2 + ...”…””}”(hj  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h½hŸh¶h Khj  ubh¾)”}”(hŒ#ewma(u) = ewma_sum(u) / ewma_sum(1)”h]”hŒ#ewma(u) = ewma_sum(u) / ewma_sum(1)”…””}”(hj  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h½hŸh¶h Khj  ubeh}”(h]”h ]”h"]”h$]”h&]”uh1j   hŸh¶h KhhÓhžhubh¾)”}”(hŒîSince this is essentially a progression of an infinite geometric series, the
results are composable, that is ewma(A) + ewma(B) = ewma(A+B). This property
is key, since it gives the ability to recompose the averages when tasks move
around.”h]”hŒîSince this is essentially a progression of an infinite geometric series, the
results are composable, that is ewma(A) + ewma(B) = ewma(A+B). This property
is key, since it gives the ability to recompose the averages when tasks move
around.”…””}”(hj(  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h½hŸh¶h KhhÓhžhubh¾)”}”(hŒ¦Note that blocked tasks still contribute to the aggregates (task-group slices
and CPU runqueues), which reflects their expected contribution when they
resume running.”h]”hŒ¦Note that blocked tasks still contribute to the aggregates (task-group slices
and CPU runqueues), which reflects their expected contribution when they
resume running.”…””}”(hj6  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h½hŸh¶h KhhÓhžhubh¾)”}”(hX¼  Using this we track 2 key metrics: 'running' and 'runnable'. 'Running'
reflects the time an entity spends on the CPU, while 'runnable' reflects the
time an entity spends on the runqueue. When there is only a single task these
two metrics are the same, but once there is contention for the CPU 'running'
will decrease to reflect the fraction of time each task spends on the CPU
while 'runnable' will increase to reflect the amount of contention.”h]”hXÔ  Using this we track 2 key metrics: â€˜runningâ€™ and â€˜runnableâ€™. â€˜Runningâ€™
reflects the time an entity spends on the CPU, while â€˜runnableâ€™ reflects the
time an entity spends on the runqueue. When there is only a single task these
two metrics are the same, but once there is contention for the CPU â€˜runningâ€™
will decrease to reflect the fraction of time each task spends on the CPU
while â€˜runnableâ€™ will increase to reflect the amount of contention.”…””}”(hjD  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h½hŸh¶h K#hhÓhžhubh¾)”}”(hŒ(For more detail see: kernel/sched/pelt.c”h]”hŒ(For more detail see: kernel/sched/pelt.c”…””}”(hjR  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h½hŸh¶h K*hhÓhžhubeh}”(h]”Œpelt-per-entity-load-tracking”ah ]”h"]”Œpelt (per entity load tracking)”ah$]”h&]”uh1h¡hh£hžhhŸh¶h Kubh¢)”}”(hhh]”(h§)”}”(hŒFrequency / CPU Invariance”h]”hŒFrequency / CPU Invariance”…””}”(hjk  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h¦hjh  hžhhŸh¶h K.ubh¾)”}”(hX8  Because consuming the CPU for 50% at 1GHz is not the same as consuming the CPU
for 50% at 2GHz, nor is running 50% on a LITTLE CPU the same as running 50% on
a big CPU, we allow architectures to scale the time delta with two ratios, one
Dynamic Voltage and Frequency Scaling (DVFS) ratio and one microarch ratio.”h]”hX8  Because consuming the CPU for 50% at 1GHz is not the same as consuming the CPU
for 50% at 2GHz, nor is running 50% on a LITTLE CPU the same as running 50% on
a big CPU, we allow architectures to scale the time delta with two ratios, one
Dynamic Voltage and Frequency Scaling (DVFS) ratio and one microarch ratio.”…””}”(hjy  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h½hŸh¶h K0hjh  hžhubh¾)”}”(hŒeFor simple DVFS architectures (where software is in full control) we trivially
compute the ratio as::”h]”hŒdFor simple DVFS architectures (where software is in full control) we trivially
compute the ratio as:”…””}”(hj‡  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h½hŸh¶h K5hjh  hžhubhŒliteral_block”“”)”}”(hŒ/          f_cur
r_dvfs := -----
          f_max”h]”hŒ/          f_cur
r_dvfs := -----
          f_max”…””}”hj—  sbah}”(h]”h ]”h"]”h$]”h&]”Œ	xml:space”Œpreserve”uh1j•  hŸh¶h K8hjh  hžhubh¾)”}”(hŒ¶For more dynamic systems where the hardware is in control of DVFS we use
hardware counters (Intel APERF/MPERF, ARMv8.4-AMU) to provide us this ratio.
For Intel specifically, we use::”h]”hŒµFor more dynamic systems where the hardware is in control of DVFS we use
hardware counters (Intel APERF/MPERF, ARMv8.4-AMU) to provide us this ratio.
For Intel specifically, we use:”…””}”(hj§  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h½hŸh¶h K<hjh  hžhubj–  )”}”(hŒù         APERF
f_cur := ----- * P0
         MPERF

           4C-turbo;  if available and turbo enabled
f_max := { 1C-turbo;  if turbo enabled
           P0;        otherwise

                  f_cur
r_dvfs := min( 1, ----- )
                  f_max”h]”hŒù         APERF
f_cur := ----- * P0
         MPERF

           4C-turbo;  if available and turbo enabled
f_max := { 1C-turbo;  if turbo enabled
           P0;        otherwise

                  f_cur
r_dvfs := min( 1, ----- )
                  f_max”…””}”hjµ  sbah}”(h]”h ]”h"]”h$]”h&]”j¥  j¦  uh1j•  hŸh¶h K@hjh  hžhubh¾)”}”(hŒDWe pick 4C turbo over 1C turbo to make it slightly more sustainable.”h]”hŒDWe pick 4C turbo over 1C turbo to make it slightly more sustainable.”…””}”(hjÃ  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h½hŸh¶h KLhjh  hžhubh¾)”}”(hŒ‘r_cpu is determined as the ratio of highest performance level of the current
CPU vs the highest performance level of any other CPU in the system.”h]”hŒ‘r_cpu is determined as the ratio of highest performance level of the current
CPU vs the highest performance level of any other CPU in the system.”…””}”(hjÑ  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h½hŸh¶h KNhjh  hžhubj  )”}”(hŒr_tot = r_dvfs * r_cpu
”h]”h¾)”}”(hŒr_tot = r_dvfs * r_cpu”h]”hŒr_tot = r_dvfs * r_cpu”…””}”(hjã  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h½hŸh¶h KQhjß  ubah}”(h]”h ]”h"]”h$]”h&]”uh1j   hŸh¶h KQhjh  hžhubh¾)”}”(hŒ˜The result is that the above 'running' and 'runnable' metrics become invariant
of DVFS and CPU type. IOW. we can transfer and compare them between CPUs.”h]”hŒ The result is that the above â€˜runningâ€™ and â€˜runnableâ€™ metrics become invariant
of DVFS and CPU type. IOW. we can transfer and compare them between CPUs.”…””}”(hj÷  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h½hŸh¶h KShjh  hžhubh¾)”}”(hŒFor more detail see:”h]”hŒFor more detail see:”…””}”(hj  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h½hŸh¶h KVhjh  hžhubj  )”}”(hŒÊ- kernel/sched/pelt.h:update_rq_clock_pelt()
- arch/x86/kernel/smpboot.c:"APERF/MPERF frequency ratio computation."
- Documentation/scheduler/sched-capacity.rst:"1. CPU Capacity + 2. Task utilization"

”h]”hŒbullet_list”“”)”}”(hhh]”(hŒ	list_item”“”)”}”(hŒ*kernel/sched/pelt.h:update_rq_clock_pelt()”h]”h¾)”}”(hj   h]”hŒ*kernel/sched/pelt.h:update_rq_clock_pelt()”…””}”(hj"  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h½hŸh¶h KXhj  ubah}”(h]”h ]”h"]”h$]”h&]”uh1j  hj  ubj  )”}”(hŒDarch/x86/kernel/smpboot.c:"APERF/MPERF frequency ratio computation."”h]”h¾)”}”(hj7  h]”hŒHarch/x86/kernel/smpboot.c:â€APERF/MPERF frequency ratio computation.â€”…””}”(hj9  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h½hŸh¶h KYhj5  ubah}”(h]”h ]”h"]”h$]”h&]”uh1j  hj  ubj  )”}”(hŒTDocumentation/scheduler/sched-capacity.rst:"1. CPU Capacity + 2. Task utilization"

”h]”h¾)”}”(hŒRDocumentation/scheduler/sched-capacity.rst:"1. CPU Capacity + 2. Task utilization"”h]”hŒVDocumentation/scheduler/sched-capacity.rst:â€1. CPU Capacity + 2. Task utilizationâ€”…””}”(hjP  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h½hŸh¶h KZhjL  ubah}”(h]”h ]”h"]”h$]”h&]”uh1j  hj  ubeh}”(h]”h ]”h"]”h$]”h&]”Œbullet”Œ-”uh1j  hŸh¶h KXhj  ubah}”(h]”h ]”h"]”h$]”h&]”uh1j   hŸh¶h KXhjh  hžhubeh}”(h]”Œfrequency-cpu-invariance”ah ]”h"]”Œfrequency / cpu invariance”ah$]”h&]”uh1h¡hh£hžhhŸh¶h K.ubh¢)”}”(hhh]”(h§)”}”(hŒUTIL_EST”h]”hŒUTIL_EST”…””}”(hj}  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h¦hjz  hžhhŸh¶h K^ubh¾)”}”(hŒÅBecause periodic tasks have their averages decayed while they sleep, even
though when running their expected utilization will be the same, they suffer a
(DVFS) ramp-up after they are running again.”h]”hŒÅBecause periodic tasks have their averages decayed while they sleep, even
though when running their expected utilization will be the same, they suffer a
(DVFS) ramp-up after they are running again.”…””}”(hj‹  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h½hŸh¶h K`hjz  hžhubh¾)”}”(hŒâTo alleviate this (a default enabled option) UTIL_EST drives an Infinite
Impulse Response (IIR) EWMA with the 'running' value on dequeue -- when it is
highest. UTIL_EST filters to instantly increase and only decay on decrease.”h]”hŒæTo alleviate this (a default enabled option) UTIL_EST drives an Infinite
Impulse Response (IIR) EWMA with the â€˜runningâ€™ value on dequeue -- when it is
highest. UTIL_EST filters to instantly increase and only decay on decrease.”…””}”(hj™  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h½hŸh¶h Kdhjz  hžhubh¾)”}”(hŒAA further runqueue wide sum (of runnable tasks) is maintained of:”h]”hŒAA further runqueue wide sum (of runnable tasks) is maintained of:”…””}”(hj§  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h½hŸh¶h Khhjz  hžhubj  )”}”(hŒ5util_est := \Sum_t max( t_running, t_util_est_ewma )
”h]”h¾)”}”(hŒ4util_est := \Sum_t max( t_running, t_util_est_ewma )”h]”hŒ4util_est :=  Sum_t max( t_running, t_util_est_ewma )”…””}”(hj¹  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h½hŸh¶h Kjhjµ  ubah}”(h]”h ]”h"]”h$]”h&]”uh1j   hŸh¶h Kjhjz  hžhubh¾)”}”(hŒ;For more detail see: kernel/sched/fair.c:util_est_dequeue()”h]”hŒ;For more detail see: kernel/sched/fair.c:util_est_dequeue()”…””}”(hjÍ  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h½hŸh¶h Klhjz  hžhubeh}”(h]”Œutil-est”ah ]”h"]”Œutil_est”ah$]”h&]”uh1h¡hh£hžhhŸh¶h K^ubh¢)”}”(hhh]”(h§)”}”(hŒUCLAMP”h]”hŒUCLAMP”…””}”(hjæ  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h¦hjã  hžhhŸh¶h Kpubh¾)”}”(hŒ™It is possible to set effective u_min and u_max clamps on each CFS or RT task;
the runqueue keeps an max aggregate of these clamps for all running tasks.”h]”hŒ™It is possible to set effective u_min and u_max clamps on each CFS or RT task;
the runqueue keeps an max aggregate of these clamps for all running tasks.”…””}”(hjô  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h½hŸh¶h Krhjã  hžhubh¾)”}”(hŒ5For more detail see: include/uapi/linux/sched/types.h”h]”hŒ5For more detail see: include/uapi/linux/sched/types.h”…””}”(hj  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h½hŸh¶h Kuhjã  hžhubeh}”(h]”Œuclamp”ah ]”h"]”Œuclamp”ah$]”h&]”uh1h¡hh£hžhhŸh¶h Kpubh¢)”}”(hhh]”(h§)”}”(hŒSchedutil / DVFS”h]”hŒSchedutil / DVFS”…””}”(hj  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h¦hj  hžhhŸh¶h Kyubh¾)”}”(hŒEvery time the scheduler load tracking is updated (task wakeup, task
migration, time progression) we call out to schedutil to update the hardware
DVFS state.”h]”hŒEvery time the scheduler load tracking is updated (task wakeup, task
migration, time progression) we call out to schedutil to update the hardware
DVFS state.”…””}”(hj)  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h½hŸh¶h K{hj  hžhubh¾)”}”(hŒ´The basis is the CPU runqueue's 'running' metric, which per the above it is
the frequency invariant utilization estimate of the CPU. From this we compute
a desired frequency like::”h]”hŒ¹The basis is the CPU runqueueâ€™s â€˜runningâ€™ metric, which per the above it is
the frequency invariant utilization estimate of the CPU. From this we compute
a desired frequency like:”…””}”(hj7  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h½hŸh¶h Khj  hžhubj–  )”}”(hXZ             max( running, util_est );  if UTIL_EST
u_cfs := { running;                   otherwise

             clamp( u_cfs + u_rt , u_min, u_max );    if UCLAMP_TASK
u_clamp := { u_cfs + u_rt;                            otherwise

u := u_clamp + u_irq + u_dl;          [approx. see source for more detail]

f_des := min( f_max, 1.25 u * f_max )”h]”hXZ             max( running, util_est );  if UTIL_EST
u_cfs := { running;                   otherwise

             clamp( u_cfs + u_rt , u_min, u_max );    if UCLAMP_TASK
u_clamp := { u_cfs + u_rt;                            otherwise

u := u_clamp + u_irq + u_dl;          [approx. see source for more detail]

f_des := min( f_max, 1.25 u * f_max )”…””}”hjE  sbah}”(h]”h ]”h"]”h$]”h&]”j¥  j¦  uh1j•  hŸh¶h Kƒhj  hžhubh¾)”}”(hŒ[XXX IO-wait: when the update is due to a task wakeup from IO-completion we
boost 'u' above.”h]”hŒ_XXX IO-wait: when the update is due to a task wakeup from IO-completion we
boost â€˜uâ€™ above.”…””}”(hjS  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h½hŸh¶h Khj  hžhubh¾)”}”(hŒqThis frequency is then used to select a P-state/OPP or directly munged into a
CPPC style request to the hardware.”h]”hŒqThis frequency is then used to select a P-state/OPP or directly munged into a
CPPC style request to the hardware.”…””}”(hja  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h½hŸh¶h Khj  hžhubh¾)”}”(hŒoXXX: deadline tasks (Sporadic Task Model) allows us to calculate a hard f_min
required to satisfy the workload.”h]”hŒoXXX: deadline tasks (Sporadic Task Model) allows us to calculate a hard f_min
required to satisfy the workload.”…””}”(hjo  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h½hŸh¶h K“hj  hžhubh¾)”}”(hŒùBecause these callbacks are directly from the scheduler, the DVFS hardware
interaction should be 'fast' and non-blocking. Schedutil supports
rate-limiting DVFS requests for when hardware interaction is slow and
expensive, this reduces effectiveness.”h]”hŒýBecause these callbacks are directly from the scheduler, the DVFS hardware
interaction should be â€˜fastâ€™ and non-blocking. Schedutil supports
rate-limiting DVFS requests for when hardware interaction is slow and
expensive, this reduces effectiveness.”…””}”(hj}  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h½hŸh¶h K–hj  hžhubh¾)”}”(hŒ:For more information see: kernel/sched/cpufreq_schedutil.c”h]”hŒ:For more information see: kernel/sched/cpufreq_schedutil.c”…””}”(hj‹  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h½hŸh¶h K›hj  hžhubeh}”(h]”Œschedutil-dvfs”ah ]”h"]”Œschedutil / dvfs”ah$]”h&]”uh1h¡hh£hžhhŸh¶h Kyubh¢)”}”(hhh]”(h§)”}”(hŒNOTES”h]”hŒNOTES”…””}”(hj¤  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h¦hj¡  hžhhŸh¶h KŸubj  )”}”(hX\  - On low-load scenarios, where DVFS is most relevant, the 'running' numbers
  will closely reflect utilization.

- In saturated scenarios task movement will cause some transient dips,
  suppose we have a CPU saturated with 4 tasks, then when we migrate a task
  to an idle CPU, the old CPU will have a 'running' value of 0.75 while the
  new CPU will gain 0.25. This is inevitable and time progression will
  correct this. XXX do we still guarantee f_max due to no idle-time?

- Much of the above is about avoiding DVFS dips, and independent DVFS domains
  having to re-learn / ramp-up when load shifts.
”h]”j  )”}”(hhh]”(j  )”}”(hŒlOn low-load scenarios, where DVFS is most relevant, the 'running' numbers
will closely reflect utilization.
”h]”h¾)”}”(hŒkOn low-load scenarios, where DVFS is most relevant, the 'running' numbers
will closely reflect utilization.”h]”hŒoOn low-load scenarios, where DVFS is most relevant, the â€˜runningâ€™ numbers
will closely reflect utilization.”…””}”(hj½  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h½hŸh¶h K¡hj¹  ubah}”(h]”h ]”h"]”h$]”h&]”uh1j  hj¶  ubj  )”}”(hXa  In saturated scenarios task movement will cause some transient dips,
suppose we have a CPU saturated with 4 tasks, then when we migrate a task
to an idle CPU, the old CPU will have a 'running' value of 0.75 while the
new CPU will gain 0.25. This is inevitable and time progression will
correct this. XXX do we still guarantee f_max due to no idle-time?
”h]”h¾)”}”(hX`  In saturated scenarios task movement will cause some transient dips,
suppose we have a CPU saturated with 4 tasks, then when we migrate a task
to an idle CPU, the old CPU will have a 'running' value of 0.75 while the
new CPU will gain 0.25. This is inevitable and time progression will
correct this. XXX do we still guarantee f_max due to no idle-time?”h]”hXd  In saturated scenarios task movement will cause some transient dips,
suppose we have a CPU saturated with 4 tasks, then when we migrate a task
to an idle CPU, the old CPU will have a â€˜runningâ€™ value of 0.75 while the
new CPU will gain 0.25. This is inevitable and time progression will
correct this. XXX do we still guarantee f_max due to no idle-time?”…””}”(hjÕ  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h½hŸh¶h K¤hjÑ  ubah}”(h]”h ]”h"]”h$]”h&]”uh1j  hj¶  ubj  )”}”(hŒ{Much of the above is about avoiding DVFS dips, and independent DVFS domains
having to re-learn / ramp-up when load shifts.
”h]”h¾)”}”(hŒzMuch of the above is about avoiding DVFS dips, and independent DVFS domains
having to re-learn / ramp-up when load shifts.”h]”hŒzMuch of the above is about avoiding DVFS dips, and independent DVFS domains
having to re-learn / ramp-up when load shifts.”…””}”(hjí  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h½hŸh¶h Kªhjé  ubah}”(h]”h ]”h"]”h$]”h&]”uh1j  hj¶  ubeh}”(h]”h ]”h"]”h$]”h&]”jj  jk  uh1j  hŸh¶h K¡hj²  ubah}”(h]”h ]”h"]”h$]”h&]”uh1j   hŸh¶h K¡hj¡  hžhubeh}”(h]”Œnotes”ah ]”h"]”Œnotes”ah$]”h&]”uh1h¡hh£hžhhŸh¶h KŸubeh}”(h]”Œ	schedutil”ah ]”h"]”Œ	schedutil”ah$]”h&]”uh1h¡hhhžhhŸh¶h Kubeh}”(h]”h ]”h"]”h$]”h&]”Œsource”h¶uh1hŒcurrent_source”NŒcurrent_line”NŒsettings”Œdocutils.frontend”ŒValues”“”)”}”(h¦NŒ	generator”NŒ	datestamp”NŒsource_link”NŒ
source_url”NŒtoc_backlinks”Œentry”Œfootnote_backlinks”KŒsectnum_xform”KŒstrip_comments”NŒstrip_elements_with_classes”NŒstrip_classes”NŒreport_level”KŒ
halt_level”KŒexit_status_level”KŒdebug”NŒwarning_stream”NŒ	traceback”ˆŒinput_encoding”Œ	utf-8-sig”Œinput_encoding_error_handler”Œstrict”Œoutput_encoding”Œutf-8”Œoutput_encoding_error_handler”j@  Œerror_encoding”Œutf-8”Œerror_encoding_error_handler”Œbackslashreplace”Œlanguage_code”Œen”Œrecord_dependencies”NŒconfig”NŒ	id_prefix”hŒauto_id_prefix”Œid”Œdump_settings”NŒdump_internals”NŒdump_transforms”NŒdump_pseudo_xml”NŒexpose_internals”NŒstrict_visitor”NŒ_disable_config”NŒ_source”h¶Œ_destination”NŒ_config_files”]”Œ7/var/lib/git/docbuild/linux/Documentation/docutils.conf”aŒfile_insertion_enabled”ˆŒraw_enabled”KŒline_length_limit”M'Œpep_references”NŒpep_base_url”Œhttps://peps.python.org/”Œpep_file_url_template”Œpep-%04d”Œrfc_references”NŒrfc_base_url”Œ&https://datatracker.ietf.org/doc/html/”Œ	tab_width”KŒtrim_footnote_reference_space”‰Œsyntax_highlight”Œlong”Œsmart_quotes”ˆŒsmartquotes_locales”]”Œcharacter_level_inline_markup”‰Œdoctitle_xform”‰Œdocinfo_xform”KŒsectsubtitle_xform”‰Œimage_loading”Œlink”Œembed_stylesheet”‰Œcloak_email_addresses”ˆŒsection_self_link”‰Œenv”NubŒreporter”NŒindirect_targets”]”Œsubstitution_defs”}”Œsubstitution_names”}”Œrefnames”}”Œrefids”}”Œnameids”}”(j  j  je  jb  jw  jt  jà  jÝ  j  j  jž  j›  j  j  uŒ	nametypes”}”(j  ‰je  ‰jw  ‰jà  ‰j  ‰jž  ‰j  ‰uh}”(j  h£jb  hÓjt  jh  jÝ  jz  j  jã  j›  j  j  j¡  uŒfootnote_refs”}”Œcitation_refs”}”Œautofootnotes”]”Œautofootnote_refs”]”Œsymbol_footnotes”]”Œsymbol_footnote_refs”]”Œ	footnotes”]”Œ	citations”]”Œautofootnote_start”KŒsymbol_footnote_start”K Œ
id_counter”Œcollections”ŒCounter”“”}”…”R”Œparse_messages”]”Œtransform_messages”]”Œtransformer”NŒinclude_log”]”Œ
decoration”Nhžhub.