sound/soc/codecs/wcd9310.c: expose additional controls

Signed-off-by: Paul Reioux <reioux@gmail.com>

Conflicts:
	sound/soc/codecs/wcd9310.c
intellidemand: tune for dual core operations

Signed-off-by: Paul Reioux <reioux@gmail.com>
sched: reinitialize rq->next_balance when a CPU is hot-added

Reinitialize rq->next_balance when a CPU is hot-added.  Otherwise,
scheduler domain rebalancing may be skipped if rq->next_balance was
set to a future time when the CPU was last active, and the
newly-re-added CPU is in idle_balance().  As a result, the
newly-re-added CPU will remain idle with no tasks scheduled until the
softlockup watchdog runs - potentially 4 seconds later.  This can
waste energy and reduce performance.

This behavior can be observed in some SoC kernels, which use CPU
hotplug to dynamically remove and add CPUs in response to load.  In
one case that triggered this behavior,

0. the system started with all cores enabled, running multi-threaded
   CPU-bound code;

1. the system entered some single-threaded code;

2. a CPU went idle and was hot-removed;

3. the system started executing a multi-threaded CPU-bound task;

4. the CPU from event 2 was re-added, to respond to the load.

The time interval between events 2 and 4 was approximately 300
milliseconds.

Of course, ideally CPU hotplug would not be used in this manner,
but this patch does appear to fix a real bug.

Nvidia folks: this patch is submitted as at least a partial fix for
bug 1243368 ("[sched] Load-balancing not happening correctly after
cores brought online")

Change-Id: Iabac21e110402bb581b7db40c42babc951d378d0
Signed-off-by: Paul Walmsley <pwalmsley@nvidia.com>
Cc: Peter Boonstoppel <pboonstoppel@nvidia.com>
Reviewed-on: http://git-master/r/208927
Reviewed-by: Automatic_Commit_Validation_User
Reviewed-by: Peter Zu <pzu@nvidia.com>
Reviewed-by: Peter Boonstoppel <pboonstoppel@nvidia.com>
GVS: Gerrit_Virtual_Submit
Tested-by: Peter Zu <pzu@nvidia.com>
Reviewed-by: Yu-Huan Hsu <yhsu@nvidia.com>
sched: remove redundant update_runtime notifier

migration_call() will do all the things that update_runtime() does.
So it seems update_runtime() is a redundant notifier, remove it.

Furthermore, there is potential risk that the current code will catch
BUG_ON at line 687 of rt.c when do cpu hotplug while there are realtime
threads running because of enable runtime twice.

Change-Id: I0fdad8d5a1cebb845d3f308b205dbd6517c3e4de
Cc: bitbucket@online.de
Signed-off-by: Neil Zhang <zhangwm@marvell.com>
Reviewed-on: http://git-master/r/215596
(cherry picked from commit 8f646de983f24361814d9a6ca679845fb2265807)
Reviewed-on: http://git-master/r/223067
Reviewed-by: Peter Boonstoppel <pboonstoppel@nvidia.com>
Tested-by: Peter Boonstoppel <pboonstoppel@nvidia.com>
Reviewed-by: Paul Walmsley <pwalmsley@nvidia.com>
Reviewed-by: Automatic_Commit_Validation_User
GVS: Gerrit_Virtual_Submit
Reviewed-by: Diwakar Tundlam <dtundlam@nvidia.com>
jiffies conversions: Use compile time constants when possible

Date	Fri, 04 Jan 2013 13:15:43 -0800

Do the multiplications and divisions at compile time
instead of runtime when the converted value is a constant.

Make the calculation functions static __always_inline to jiffies.h.

Add #defines with __builtin_constant_p to test and use the
static inline or the runtime functions as appropriate.

Prefix the old exported symbols/functions with __

Signed-off-by: Paul Reioux <reioux@gmail.com>
msm: move printk out of spin lock low_water_lock

cpu3 stuck in printk more time in spin lock low_water_lock cause cpu0
get spin lock fail and system crashed.

CRs-Fixed: 521570
Change-Id: I75356a4b4171ae2888ce6cce792f569b5ca8cdcf
Signed-off-by: Tingting Yang <tingting@codeaurora.org>
mutex: Make more scalable by doing less atomic operations

Date	Mon, 15 Apr 2013 10:37:57 -0400

In the __mutex_lock_common() function, an initial entry into
the lock slow path will cause two atomic_xchg instructions to be
issued. Together with the atomic decrement in the fast path, a total
of three atomic read-modify-write instructions will be issued in
rapid succession. This can cause a lot of cache bouncing when many
tasks are trying to acquire the mutex at the same time.

This patch will reduce the number of atomic_xchg instructions used by
checking the counter value first before issuing the instruction. The
atomic_read() function is just a simple memory read. The atomic_xchg()
function, on the other hand, can be up to 2 order of magnitude or even
more in cost when compared with atomic_read(). By using atomic_read()
to check the value first before calling atomic_xchg(), we can avoid a
lot of unnecessary cache coherency traffic. The only downside with this
change is that a task on the slow path will have a tiny bit
less chance of getting the mutex when competing with another task
in the fast path.

The same is true for the atomic_cmpxchg() function in the
mutex-spin-on-owner loop. So an atomic_read() is also performed before
calling atomic_cmpxchg().

The mutex locking and unlocking code for the x86 architecture can allow
any negative number to be used in the mutex count to indicate that some
tasks are waiting for the mutex. I am not so sure if that is the case
for the other architectures. So the default is to avoid atomic_xchg()
if the count has already been set to -1. For x86, the check is modified
to include all negative numbers to cover a larger case.

The following table shows the jobs per minutes (JPM) scalability data
on an 8-node 80-core Westmere box with a 3.7.10 kernel. The numactl
command is used to restrict the running of the high_systime workloads
to 1/2/4/8 nodes with hyperthreading on and off.

+-----------------+-----------+------------+----------+
|  Configuration  | Mean JPM  |  Mean JPM  | % Change |
|		  | w/o patch | with patch |	      |
+-----------------+-----------------------------------+
|		  |      User Range 1100 - 2000	      |
+-----------------+-----------------------------------+
| 8 nodes, HT on  |    36980   |   148590  | +301.8%  |
| 8 nodes, HT off |    42799   |   145011  | +238.8%  |
| 4 nodes, HT on  |    61318   |   118445  |  +51.1%  |
| 4 nodes, HT off |   158481   |   158592  |   +0.1%  |
| 2 nodes, HT on  |   180602   |   173967  |   -3.7%  |
| 2 nodes, HT off |   198409   |   198073  |   -0.2%  |
| 1 node , HT on  |   149042   |   147671  |   -0.9%  |
| 1 node , HT off |   126036   |   126533  |   +0.4%  |
+-----------------+-----------------------------------+
|		  |       User Range 200 - 1000	      |
+-----------------+-----------------------------------+
| 8 nodes, HT on  |   41525    |   122349  | +194.6%  |
| 8 nodes, HT off |   49866    |   124032  | +148.7%  |
| 4 nodes, HT on  |   66409    |   106984  |  +61.1%  |
| 4 nodes, HT off |  119880    |   130508  |   +8.9%  |
| 2 nodes, HT on  |  138003    |   133948  |   -2.9%  |
| 2 nodes, HT off |  132792    |   131997  |   -0.6%  |
| 1 node , HT on  |  116593    |   115859  |   -0.6%  |
| 1 node , HT off |  104499    |   104597  |   +0.1%  |
+-----------------+------------+-----------+----------+
At low user range 10-100, the JPM differences were within +/-1%. So
they are not that interesting.

AIM7 benchmark run has a pretty large run-to-run variance due to random
nature of the subtests executed. So a difference of less than +-5%
may not be really significant.

This patch improves high_systime workload performance at 4 nodes
and up by maintaining transaction rates without significant drop-off
at high node count.  The patch has practically no impact on 1 and 2
nodes system.

The table below shows the percentage time (as reported by perf
record -a -s -g) spent on the __mutex_lock_slowpath() function by
the high_systime workload at 1500 users for 2/4/8-node configurations
with hyperthreading off.

+---------------+-----------------+------------------+---------+
| Configuration | %Time w/o patch | %Time with patch | %Change |
+---------------+-----------------+------------------+---------+
|    8 nodes    |      65.34%     |      0.69%       |  -99%   |
|    4 nodes    |       8.70%	  |      1.02%	     |  -88%   |
|    2 nodes    |       0.41%     |      0.32%       |  -22%   |
+---------------+-----------------+------------------+---------+
It is obvious that the dramatic performance improvement at 8
nodes was due to the drastic cut in the time spent within the
__mutex_lock_slowpath() function.

The table below show the improvements in other AIM7 workloads (at 8
nodes, hyperthreading off).

+--------------+---------------+----------------+-----------------+
|   Workload   | mean % change | mean % change  | mean % change   |
|              | 10-100 users  | 200-1000 users | 1100-2000 users |
+--------------+---------------+----------------+-----------------+
| alltests     |     +0.6%     |   +104.2%      |   +185.9%       |
| five_sec     |     +1.9%     |     +0.9%      |     +0.9%       |
| fserver      |     +1.4%     |     -7.7%      |     +5.1%       |
| new_fserver  |     -0.5%     |     +3.2%      |     +3.1%       |
| shared       |    +13.1%     |   +146.1%      |   +181.5%       |
| short        |     +7.4%     |     +5.0%      |     +4.2%       |
+--------------+---------------+----------------+-----------------+
Signed-off-by: Waiman Long <Waiman.Long@hp.com>
Reviewed-by: Davidlohr Bueso <davidlohr.bueso@hp.com>
mutex: Queue mutex spinners with MCS lock to reduce cacheline contention

Date	Mon, 15 Apr 2013 10:37:58 -0400

The current mutex spinning code (with MUTEX_SPIN_ON_OWNER option turned
on) allow multiple tasks to spin on a single mutex concurrently. A
potential problem with the current approach is that when the mutex
becomes available, all the spinning tasks will try to acquire the
mutex more or less simultaneously. As a result, there will be a lot of
cacheline bouncing especially on systems with a large number of CPUs.

This patch tries to reduce this kind of contention by putting the
mutex spinners into a queue so that only the first one in the queue
will try to acquire the mutex. This will reduce contention and allow
all the tasks to move forward faster.

The queuing of mutex spinners is done using an MCS lock based
implementation which will further reduce contention on the mutex
cacheline than a similar ticket spinlock based implementation. This
patch will add a new field into the mutex data structure for holding
the MCS lock. This expands the mutex size by 8 bytes for 64-bit system
and 4 bytes for 32-bit system. This overhead will be avoid if the
MUTEX_SPIN_ON_OWNER option is turned off.

The following table shows the jobs per minute (JPM) scalability data
on an 8-node 80-core Westmere box with a 3.7.10 kernel. The numactl
command is used to restrict the running of the fserver workloads to
1/2/4/8 nodes with hyperthreading off.

+-----------------+-----------+-----------+-------------+----------+
|  Configuration  | Mean JPM  | Mean JPM  |  Mean JPM   | % Change |
|		  | w/o patch | patch 1   | patches 1&2 |  1->1&2  |
+-----------------+------------------------------------------------+
|		  |              User Range 1100 - 2000		   |
+-----------------+------------------------------------------------+
| 8 nodes, HT off |  227972   |  227237   |   305043    |  +34.2%  |
| 4 nodes, HT off |  393503   |  381558   |   394650    |   +3.4%  |
| 2 nodes, HT off |  334957   |  325240   |   338853    |   +4.2%  |
| 1 node , HT off |  198141   |  197972   |   198075    |   +0.1%  |
+-----------------+------------------------------------------------+
|		  |              User Range 200 - 1000		   |
+-----------------+------------------------------------------------+
| 8 nodes, HT off |  282325   |  312870   |   332185    |   +6.2%  |
| 4 nodes, HT off |  390698   |  378279   |   393419    |   +4.0%  |
| 2 nodes, HT off |  336986   |  326543   |   340260    |   +4.2%  |
| 1 node , HT off |  197588   |  197622   |   197582    |    0.0%  |
+-----------------+-----------+-----------+-------------+----------+
At low user range 10-100, the JPM differences were within +/-1%. So
they are not that interesting.

The fserver workload uses mutex spinning extensively. With just
the mutex change in the first patch, there is no noticeable change
in performance.  Rather, there is a slight drop in performance. This
mutex spinning patch more than recovers the lost performance and show
a significant increase of +30% at high user load with the full 8 nodes.
Similar improvements were also seen in a 3.8 kernel.

The table below shows the %time spent by different kernel functions
as reported by perf when running the fserver workload at 1500 users
with all 8 nodes.

+-----------------------+-----------+---------+-------------+
|        Function       |  % time   | % time  |   % time    |
|                       | w/o patch | patch 1 | patches 1&2 |
+-----------------------+-----------+---------+-------------+
| __read_lock_failed    |  34.96%   | 34.91%  |   29.14%    |
| __write_lock_failed   |  10.14%   | 10.68%  |    7.51%    |
| mutex_spin_on_owner   |   3.62%   |  3.42%  |    2.33%    |
| mspin_lock            |    N/A    |   N/A   |    9.90%    |
| __mutex_lock_slowpath |   1.46%   |  0.81%  |    0.14%    |
| _raw_spin_lock        |   2.25%   |  2.50%  |    1.10%    |
+-----------------------+-----------+---------+-------------+
The fserver workload for an 8-node system is dominated by the
contention in the read/write lock. Mutex contention also plays a
role. With the first patch only, mutex contention is down (as shown by
the __mutex_lock_slowpath figure) which help a little bit. We saw only
a few percents improvement with that.

By applying patch 2 as well, the single mutex_spin_on_owner figure is
now split out into an additional mspin_lock figure. The time increases
from 3.42% to 11.23%. It shows a great reduction in contention among
the spinners leading to a 30% improvement. The time ratio 9.9/2.33=4.3
indicates that there are on average 4+ spinners waiting in the spin_lock
loop for each spinner in the mutex_spin_on_owner loop. Contention in
other locking functions also go down by quite a lot.

The table below shows the performance change of both patches 1 & 2 over
patch 1 alone in other AIM7 workloads (at 8 nodes, hyperthreading off).

+--------------+---------------+----------------+-----------------+
|   Workload   | mean % change | mean % change  | mean % change   |
|              | 10-100 users  | 200-1000 users | 1100-2000 users |
+--------------+---------------+----------------+-----------------+
| alltests     |      0.0%     |     -0.8%      |     +0.6%       |
| five_sec     |     -0.3%     |     +0.8%      |     +0.8%       |
| high_systime |     +0.4%     |     +2.4%      |     +2.1%       |
| new_fserver  |     +0.1%     |    +14.1%      |    +34.2%       |
| shared       |     -0.5%     |     -0.3%      |     -0.4%       |
| short        |     -1.7%     |     -9.8%      |     -8.3%       |
+--------------+---------------+----------------+-----------------+
The short workload is the only one that shows a decline in performance
probably due to the spinner locking and queuing overhead.

Signed-off-by: Waiman Long <Waiman.Long@hp.com>
mutex: back out architecture specific check for negative mutex count

Date	Mon, 15 Apr 2013 10:37:59 -0400

If it is confirmed that all the supported architectures can allow a
negative mutex count without incorrect behavior, we can then back
out the architecture specific change and allow the mutex count to
go to any negative number. That should further reduce contention for
non-x86 architecture.

If this is not the case, this patch should be dropped.

Signed-off-by: Waiman Long <Waiman.Long@hp.com>
SCHEDULER: Autogroup patch group by current user android UID instead of task ID
block: cgroups, kconfig, build bits for BFQ-v6-3.4

Update Kconfig.iosched and do the related Makefile changes to include
kernel configuration options for BFQ. Also add the bfqio controller
to the cgroups subsystem.

Signed-off-by: Paolo Valente <paolo.valente@unimore.it>
Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com>

Signed-off-by: Paul Reioux <reioux@gmail.com>
block: introduce the BFQ-v6 I/O sched for 3.4

Add the BFQ-v6 I/O scheduler to 3.4.
The general structure is borrowed from CFQ, as much code. A (bfq_)queue is
associated to each task doing I/O on a device, and each time a scheduling
decision has to be made a queue is selected and served until it expires.

    - Slices are given in the service domain: tasks are assigned budgets,
      measured in number of sectors. Once got the disk, a task must
      however consume its assigned budget within a configurable maximum time
      (by default, the maximum possible value of the budgets is automatically
      computed to comply with this timeout). This allows the desired latency
      vs "throughput boosting" tradeoff to be set.

    - Budgets are scheduled according to a variant of WF2Q+, implemented
      using an augmented rb-tree to take eligibility into account while
      preserving an O(log N) overall complexity.

    - A low-latency tunable is provided; if enabled, both interactive and soft
      real-time applications are guaranteed very low latency.

    - Latency guarantees are preserved also in presence of NCQ.

    - Also with flash-based devices, a high throughput is achieved while
      still preserving latency guarantees.

    - A useful feature borrowed from CFQ: static fallback queue for OOM.

    - Differently from CFQ, BFQ uses a unified mechanism (Early Queue Merge,
      EQM) to get a sequential read pattern, and hence a high throughput,
      with any set of processes performing interleaved I/O. EQM also
      preserves low latency. The code for detecting whether two queues have
      to be merged is a slightly modified version of the CFQ code for
      detecting whether two queues belong to cooperating processes and whether
      the service of a queue should be preempted to boost the throughput.

    - BFQ supports full hierarchical scheduling, exporting a cgroups
      interface.  Each node has a full scheduler, so each group can
      be assigned its own ioprio (mapped to a weight, see next point)
      and an ioprio_class.

    - If the cgroups interface is used, weights can be explictly assigned,
      otherwise ioprio values are mapped to weights using the relation
      weight = IOPRIO_BE_NR - ioprio.

    - ioprio classes are served in strict priority order, i.e., lower
      priority queues are not served as long as there are higher priority
      queues.  Among queues in the same class the bandwidth is distributed
      in proportion to the weight of each queue. A very thin extra bandwidth
      is however guaranteed to the Idle class, to prevent it from starving.

Signed-off-by: Paolo Valente <paolo.valente@unimore.it>
Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com>