USB force fast charging

-Use base from Chad Froebel <chadfroebel@gmail.com> so we continue to
use the same generic sysfs mechanism

-Referenced franco's git for drivers/usb/otg/msm_otg.c changes
https://github.com/franciscofranco/mako/commit/5a8a4c8e23c7e1df39c740b9ce1d5dda20b0ede3

Off by default

Turn on:
echo 1 > /sys/kernel/fast_charge/force_fast_charge

Turn off:
echo 0 > /sys/kernel/fast_charge/force_fast_charge

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

Conflicts:
	arch/arm/mach-msm/Kconfig

Change-Id: I2c9065b83d3d9560320934871e11137a27cdb926
Intellidemand governor
staging: prima: Disable debug

Signed-off-by: Stratos Karafotis <stratosk@semaphore.gr>
Signed-off-by: Francisco Franco <franciscofranco.1990@gmail.com>
gpu: Increase bus bandwidth for lowest GPU frequency.
Sweep2wake and Doubletap2wake for the Nexus 7 (flo)
sweep2wake/doubletap2wake adjustments
rework s2w and dt2w, now we're getting somewhere
Add shortsweep option
enable/disable magnetic on/off in sysfs
fix for app-mounted directories (thanks @mkasick)
Added optimized ARM RWSEM algorithm.
lib/string & lib/memcpy: use GNU implementation.

Signed-off-by: franciscofranco <franciscofranco.1990@gmail.com>
Signed-off-by: Francisco Franco <franciscofranco.1990@gmail.com>

Conflicts:
	arch/arm/lib/Makefile
lib/int_sqrt.c: optimize square root algorithm

Optimize the current version of the shift-and-subtract (hardware)
algorithm, described by John von Newmann[1] and Guy L Steele.

Iterating 1,000,000 times, perf shows for the current version:

 Performance counter stats for './sqrt-curr' (10 runs):

         27.170996 task-clock                #    0.979 CPUs utilized            ( +-  3.19% )
                 3 context-switches          #    0.103 K/sec                    ( +-  4.76% )
                 0 cpu-migrations            #    0.004 K/sec                    ( +-100.00% )
               104 page-faults               #    0.004 M/sec                    ( +-  0.16% )
        64,921,199 cycles                    #    2.389 GHz                      ( +-  0.03% )
        28,967,789 stalled-cycles-frontend   #   44.62% frontend cycles idle     ( +-  0.18% )
   <not supported> stalled-cycles-backend
       104,502,623 instructions              #    1.61  insns per cycle
                                             #    0.28  stalled cycles per insn  ( +-  0.00% )
        34,088,368 branches                  # 1254.587 M/sec                    ( +-  0.00% )
             4,901 branch-misses             #    0.01% of all branches          ( +-  1.32% )

       0.027763015 seconds time elapsed                                          ( +-  3.22% )

And for the new version:

Performance counter stats for './sqrt-new' (10 runs):

          0.496869 task-clock                #    0.519 CPUs utilized            ( +-  2.38% )
                 0 context-switches          #    0.000 K/sec
                 0 cpu-migrations            #    0.403 K/sec                    ( +-100.00% )
               104 page-faults               #    0.209 M/sec                    ( +-  0.15% )
           590,760 cycles                    #    1.189 GHz                      ( +-  2.35% )
           395,053 stalled-cycles-frontend   #   66.87% frontend cycles idle     ( +-  3.67% )
   <not supported> stalled-cycles-backend
           398,963 instructions              #    0.68  insns per cycle
                                             #    0.99  stalled cycles per insn  ( +-  0.39% )
            70,228 branches                  #  141.341 M/sec                    ( +-  0.36% )
             3,364 branch-misses             #    4.79% of all branches          ( +-  5.45% )

       0.000957440 seconds time elapsed                                          ( +-  2.42% )

Furthermore, this saves space in instruction text:

   text    data     bss     dec     hex filename
    111       0       0     111      6f lib/int_sqrt-baseline.o
     89       0       0      89      59 lib/int_sqrt.o

[1] http://en.wikipedia.org/wiki/First_Draft_of_a_Report_on_the_EDVAC

Signed-off-by: Davidlohr Bueso <davidlohr.bueso@hp.com>
Reviewed-by: Jonathan Gonzalez <jgonzlez@linets.cl>
Tested-by: Jonathan Gonzalez <jgonzlez@linets.cl>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
Signed-off-by: Francisco Franco <franciscofranco.1990@gmail.com>
krait: overclock up to 1728 MHz
block: fiops ioscheduler core

FIOPS (Fair IOPS) ioscheduler is IOPS based ioscheduler, so only targets
for drive without I/O seek. It's quite similar like CFQ, but the dispatch
decision is made according to IOPS instead of slice.

The algorithm is simple. Drive has a service tree, and each task lives in
the tree. The key into the tree is called vios (virtual I/O). Every request
has vios, which is calculated according to its ioprio, request size and so
on. Task's vios is the sum of vios of all requests it dispatches. FIOPS
always selects task with minimum vios in the service tree and let the task
dispatch request. The dispatched request's vios is then added to the task's
vios and the task is repositioned in the sevice tree.

Unlike CFQ, FIOPS doesn't have separate sync/async queues, because with I/O
less writeback, usually a task can only dispatch either sync or async requests.
Bias read or write request can still be done with read/write scale.

One issue is if workload iodepth is lower than drive queue_depth, IOPS
share of a task might not be strictly according to its priority, request
size and so on. In this case, the drive is in idle actually. Solving the
problem need make drive idle, so impact performance. I believe CFQ isn't
completely fair between tasks in such case too.

Signed-off-by: Shaohua Li <shaohua.li@intel.com>
block: fiops read/write request scale

read/write speed of Flash based storage usually is different. For example,
in my SSD maxium thoughput of read is about 3 times faster than that of
write. Add a scale to differenate read and write. Also add a tunable, so
user can assign different scale for read and write.

By default, the scale is 1:1, which means the scale is a noop.

Signed-off-by: Shaohua Li <shaohua.li@intel.com>
block: fiops sync/async scale

CFQ gives 2.5 times more share to sync workload. This matches CFQ.

Note this is different with the read/write scale. We have 3 types of
requests:
1. read
2. sync write
3. write
CFQ doesn't differentitate type 1 and 2, but request cost of 1 and 2
are usually different for flash based storage. So we have both sync/async
and read/write scale here.

Signed-off-by: Shaohua Li <shaohua.li@intel.com>
block: fiops add ioprio support

Add CFQ-like ioprio support. Priority A will get 20% more share than priority
A+1, which matches CFQ.

Signed-off-by: Shaohua Li <shaohua.li@intel.com>
block: fiops preserve vios key for deep queue depth workload

If the task has running request, even it's added into service tree newly,
we preserve its vios key, so it will not lost its share. This should work
for task driving big queue depth. For single depth task, there is no approach
to preserve its vios key.

Signed-off-by: Shaohua Li <shaohua.li@intel.com>
block: fiops bias sync workload

If there are async requests running, delay async workload. Otherwise
async workload (usually very deep iodepth) will use all queue iodepth
and later sync requests will get long delayed. The idea is from CFQ.

Signed-off-by: Shaohua Li <shaohua.li@intel.com>