cpufreq: cpufreq_notify_utilization
scheduler: compute time-average nr_running per run-queue

Compute the time-average number of running tasks per run-queue for a
trailing window of a fixed time period. The detla add/sub to the
average value is weighted by the amount of time per nr_running value
relative to the total measurement period.

Change-Id: I4b1fa8fee82a549889560ceded4b94bdb811671d
Signed-off-by: Diwakar Tundlam <dtundlam@nvidia.com>
Reviewed-on: http://git-master/r/108070
Reviewed-by: Automatic_Commit_Validation_User
Reviewed-by: Ryan Wong <ryanw@nvidia.com>
Tested-by: Ryan Wong <ryanw@nvidia.com>
scheduler: Re-compute time-average nr_running on read
Re-compute time-average nr_running when it is read. This would
prevent reading stalled average value if there were no run-queue
changes for a long time. New average value is returned to the reader,
but not stored to avoid concurrent writes. Light-weight sequential
counter synchronization is used to assure data consistency for
re-computing average.

Change-Id: I08de26087414d6663633c723ddfcbf1099a01ce2
Signed-off-by: Alex Frid <afrid@nvidia.com>
Reviewed-on: http://git-master/r/108072
Reviewed-by: Automatic_Commit_Validation_User
Reviewed-by: Ryan Wong <ryanw@nvidia.com>
Tested-by: Ryan Wong <ryanw@nvidia.com>
cpufreq: Add cpu utilization statistics to aid decisions made by userspace.

https://android.googlesource.com/kernel/msm.git/+/ba17979cf589bb41c3faf265bffb8c2b3043ab17%5E!/

Understanding system load as seen by cpufreq can help userspace
algorithms make better decisions to improve system responsiveness.
One such example would be the MP decision algorithm which mines
various system info to make decisions on hotplugging in/out
the additional cores.

Signed-off-by: Anitha Anand <anithas@codeaurora.org>
(cherry picked from commit cbeef6aafc4964c4a6cfafd26b23eaccd40804b4)

Change-Id: I8a5fb95380af898076fe0e246fb21e3aa48b33b1
Signed-off-by: Shruthi Krishna <skrish@codeaurora.org>