cpufreq: intelliactive: initial coding and introduction!

intelliactive is based on Latest Google Interactive cpufreq governor from
Google.  The original Interactive provides smooth UI operations but suffers
slight battery drain due to its aggressive policies.  Intelliactive is an
improvement built on top of it.

It has the following enhancements added:
1. self-boost capability from input drivers (no need for PowerHAL assist)
2. two phase scheduling (idle/busy phases to prevent from jumping directly to
   max freq
3. Checks for offline cpus and short circuits some unnecessary checks to
   improve code execution paths
4. removed trace calls

Signed-off-by: shivamk11 <shivamk11@gmail.com>
Remove useless modules

Signed-off-by: shivamk11 <shivamk11@gmail.com>
block: SIO

Signed-off-by: shivamk11 <shivamk11@gmail.com>
Lock initial TCP window size to 64k (Improves network ping and output)

Signed-off-by: shivamk11 <shivamk11@gmail.com>
Remove '+' symbol from kernel version string

Signed-off-by: shivamk11 <shivamk11@gmail.com>
block: cgroups, kconfig, build bits for BFQ-v6r2 for 3.4

Update Kconfig.iosched to include kernel configuration options
for BFQ. Add a Kconfig option and do the related Makefile changes
to compile the scheduler. Also let the cgroups subsystem know about
the BFQ I/O controller.

Signed-off-by: shivamk11 <shivamk11@gmail.com>
block: introduce the BFQ-v6r2 I/O sched for 3.4

Add the BFQ-v6r2 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.

    - Useful features borrowed from CFQ: cooperating-queues merging (with
      some additional optimizations with respect to the original CFQ version),
      static fallback queue for OOM.

    - 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: shivamk11 <shivamk11@gmail.com>
block, bfq: add Early Queue Merge (EQM) to BFQ-v6r2 for 3.4.0

A set of processes may happen  to  perform interleaved reads, i.e., requests
whose union would give rise to a  sequential read  pattern.  There   are two
typical  cases: in the first  case,   processes  read  fixed-size  chunks of
data at a fixed distance from each other, while in the second case processes
may read variable-size chunks at  variable distances. The latter case occurs
for  example with  KVM, which  splits the  I/O generated  by the  guest into
multiple chunks,  and lets these chunks  be served by a  pool of cooperating
processes,  iteratively  assigning  the  next  chunk of  I/O  to  the  first
available  process. CFQ  uses actual  queue merging  for the  first type  of
processes, whereas it  uses preemption to get a sequential  read pattern out
of the read requests  performed by the second type of  processes. In the end
it uses  two different  mechanisms to  achieve the  same goal:  boosting the
throughput with interleaved I/O.

This patch introduces  Early Queue Merge (EQM), a unified mechanism to get a
sequential  read pattern  with both  types of  processes. The  main idea  is
checking newly arrived requests against the next request of the active queue
both in case of actual request insert and in case of request merge. By doing
so, both the types of processes can be handled by just merging their queues.
EQM is  then simpler and  more compact than the  pair of mechanisms  used in
CFQ.

Finally, EQM  also preserves the  typical low-latency properties of  BFQ, by
properly restoring the weight-raising state of  a queue when it gets back to
a non-merged state.

Signed-off-by: Mauro Andreolini <mauro.andreolini@unimore.it>
Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com>
Reviewed-by: Paolo Valente <paolo.valente@unimore.it>
block: bfq: Squashed update from BFQ-v6r2 to BFQ-v7r1

Change-Id: I7498f1f60253b0631a0ce36e7c20d6ec4e1df8f5
block: bfq: Squashed update from BFQ-v7r1 to BFQ-v7r2

Change-Id: I90a2156ae874fed703aafa22b721f59a0db40c51
block: bfq: Squashed update from BFQ-v7r2 to BFQ-v7r3

Change-Id: Id0ef3399d83bf4fd407eff64e695a7a3ec059646
block: bfq: Squashed update from BFQ-v7r3 to BFQ-v7r4

Change-Id: I0b88bf402da4c7f4d9363132e14c1b86fcc5d21c
block: bfq: Squashed update from BFQ-v7r4 to BFQ-v7r5

Change-Id: I749ef141246db7020cec0b10d980ec854a572603
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>
block: fiops add some trace information

Add some trace information, which is helpful when I do debugging.

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