MOTIVATION
----------
Existing `perf sched` is quite exhaustive and provides lot of insights
into scheduler behavior but it quickly becomes impractical to use for
long running or scheduler intensive workload. For ex, `perf sched record`
has ~7.77% overhead on hackbench (with 25 groups each running 700K loops
on a 2-socket 128 Cores 256 Threads 3rd Generation EPYC Server), and it
generates huge 56G perf.data for which perf takes ~137 mins to prepare
and write it to disk [1].
Unlike `perf sched record`, which hooks onto set of scheduler tracepoints
and generates samples on a tracepoint hit, `perf sched stats record` takes
snapshot of the /proc/schedstat file before and after the workload, i.e.
there is almost zero interference on workload run. Also, it takes very
minimal time to parse /proc/schedstat, convert it into perf samples and
save those samples into perf.data file. Result perf.data file is much
smaller. So, overall `perf sched stats record` is much more light weight
compare to `perf sched record`.
We, internally at AMD, have been using this (a variant of this, known as
"sched-scoreboard"[2]) and found it to be very useful to analyse impact
of any scheduler code changes[3][4].
Please note that, this is not a replacement of perf sched record/report.
The intended users of the new tool are scheduler developers, not regular
users.
USAGE
-----
# perf sched stats record
# perf sched stats report
Note: Although `perf sched stats` tool supports workload profiling syntax
(i.e. -- <workload> ), the recorded profile is still systemwide since the
/proc/schedstat is a systemwide file.
HOW TO INTERPRET THE REPORT
---------------------------
The `perf sched stats report` starts with total time profiling was active
in terms of jiffies:
----------------------------------------------------------------------------------------------------
Time elapsed (in jiffies) : 24537
----------------------------------------------------------------------------------------------------
Next is CPU scheduling statistics. These are simple diffs of
/proc/schedstat CPU lines along with description. The report also
prints % relative to base stat.
In the example below, schedule() left the CPU0 idle 98.19% of the time.
16.54% of total try_to_wake_up() was to wakeup local CPU. And, the total
waittime by tasks on CPU0 is 0.49% of the total runtime by tasks on the
same CPU.
----------------------------------------------------------------------------------------------------
CPU 0
----------------------------------------------------------------------------------------------------
sched_yield() count : 0
Legacy counter can be ignored : 0
schedule() called : 17138
schedule() left the processor idle : 16827 ( 98.19% )
try_to_wake_up() was called : 508
try_to_wake_up() was called to wake up the local cpu : 84 ( 16.54% )
total runtime by tasks on this processor (in jiffies) : 2408959243
total waittime by tasks on this processor (in jiffies) : 11731825 ( 0.49% )
total timeslices run on this cpu : 311
----------------------------------------------------------------------------------------------------
Next is load balancing statistics. For each of the sched domains
(eg: `SMT`, `MC`, `DIE`...), the scheduler computes statistics under
the following three categories:
1) Idle Load Balance: Load balancing performed on behalf of a long
idling CPU by some other CPU.
2) Busy Load Balance: Load balancing performed when the CPU was busy.
3) New Idle Balance : Load balancing performed when a CPU just became
idle.
Under each of these three categories, sched stats report provides
different load balancing statistics. Along with direct stats, the
report also contains derived metrics prefixed with *. Example:
----------------------------------------------------------------------------------------------------
CPU 0 DOMAIN SMT CPUS <0, 64>
----------------------------------------- <Category idle> ------------------------------------------
load_balance() count on cpu idle : 50 $ 490.74 $
load_balance() found balanced on cpu idle : 42 $ 584.21 $
load_balance() move task failed on cpu idle : 8 $ 3067.12 $
imbalance sum on cpu idle : 8
pull_task() count on cpu idle : 0
pull_task() when target task was cache-hot on cpu idle : 0
load_balance() failed to find busier queue on cpu idle : 0 $ 0.00 $
load_balance() failed to find busier group on cpu idle : 42 $ 584.21 $
*load_balance() success count on cpu idle : 0
*avg task pulled per successful lb attempt (cpu idle) : 0.00
----------------------------------------- <Category busy> ------------------------------------------
load_balance() count on cpu busy : 2 $ 12268.50 $
load_balance() found balanced on cpu busy : 2 $ 12268.50 $
load_balance() move task failed on cpu busy : 0 $ 0.00 $
imbalance sum on cpu busy : 0
pull_task() count on cpu busy : 0
pull_task() when target task was cache-hot on cpu busy : 0
load_balance() failed to find busier queue on cpu busy : 0 $ 0.00 $
load_balance() failed to find busier group on cpu busy : 1 $ 24537.00 $
*load_balance() success count on cpu busy : 0
*avg task pulled per successful lb attempt (cpu busy) : 0.00
---------------------------------------- <Category newidle> ----------------------------------------
load_balance() count on cpu newly idle : 427 $ 57.46 $
load_balance() found balanced on cpu newly idle : 382 $ 64.23 $
load_balance() move task failed on cpu newly idle : 45 $ 545.27 $
imbalance sum on cpu newly idle : 48
pull_task() count on cpu newly idle : 0
pull_task() when target task was cache-hot on cpu newly idle : 0
load_balance() failed to find busier queue on cpu newly idle : 0 $ 0.00 $
load_balance() failed to find busier group on cpu newly idle : 382 $ 64.23 $
*load_balance() success count on cpu newly idle : 0
*avg task pulled per successful lb attempt (cpu newly idle) : 0.00
----------------------------------------------------------------------------------------------------
Consider following line:
load_balance() found balanced on cpu newly idle : 382 $ 64.23 $
While profiling was active, the load-balancer found 382 times the load
needs to be balanced on a newly idle CPU 0. Following value encapsulated
inside $ is average jiffies between two events (24537 / 382 = 64.23).