block.c: allocate boot (MMC) partitions on probe
module.c: kernel: make an exception in module loading to load proprietary modules

credits to gokhanmoral
module.c: kernel: make an exception in module loading to load proprietary modules
block: ROW & blk-core
block: prepare I/O context code for BFQ-v6r2 for 3.0
block: prepare I/O context code for BFQ-v6r2 for 3.0 v2
block: cgroups, kconfig, build bits for BFQ-v6r2-3.0
block: introduce the BFQ-v6r2 I/O sched for 3.0

Add the BFQ-v6r2 I/O scheduler to 3.0.
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: Paolo Valente <paolo.valente@unimore.it>
Signed-off-by: Arianna Avanzini <avanzini.arianna@gmail.com>
block, bfq: add Early Queue Merge (EQM) to BFQ-v6r2 for 3.0.0

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>