block: BFQ-v6r1 I/O sched for 3.4

BFQ is based on CFQ code, but it implements a more accurate scheduling policy. In brief, differently from CFQ, BFQ does not grant the disk to each process for a fixed time-slice, but until the process exhausts a previously assigned budget, measured in number of sectors. Budgets are scheduled with an internal budget scheduler, B-WF2Q+, a modified version of the WF2Q+ packet scheduler.
In more detail, in BFQ, as in CFQ, synchronous requests are collected in per-task queues, and asynchronous requests are collected in per-device (or, in case of hierarchical scheduling, per group) queues. When a new queue is created, it is assigned a budget, measured in number of sectors, to use when the queue itself is granted access to the disk. BFQ exclusively serves one queue at a time. When the underlying device driver asks for the next request to serve, BFQ selects the first request from the queue under service in C-LOOK order and returns it to the driver. The budget of the queue is decremented by the size of the request. As in CFQ, if a sync queue has no more requests to serve, but it has some budget left, the scheduler idles (i.e., it tells to the device driver that it has no requests to serve even if there are other backlogged queues) for a short period, waiting for a new request from the task associated to the queue. The queue under service goes on being served until one of the following conditions is met:

the idling timer expires while BFQ is idling to wait for the arrival of the next request from the task associated to the queue
the queue is spending too much time to consume its budget (budget timeout, see the timeout_* parameters below), or
the queue exhausts its budget, or
the queue is not sync and has no more requests to serve.
When the queue is deselected, it is assigned a new budget, computed as a function of which of the above events occurred. The next queue to serve is selected with B-WF2Q+, a modified version of the WF2Q+ packet scheduler. B-WF2Q+ schedules backlogged queues as a function of: their budgets, their weights and the service they have already received.

Working in the service domain and not in the time domain is what allows BFQ to distribute the disk throughput as desired, unconditionally and even if it fluctuates. In addition, the accurate service distribution of the internal B-WF2Q+ scheduler, guarantees tight delays with respect to the completion times that the requests would enjoy in an ideal perfectly-fair system.

The idea for reducing the latency for interactive and soft real-time processes (when low_latency is enabled) is just raising the weight of the associated queues. More details can be found here. An important point is that such an heuristics allows interactive and soft real-time queues to steal more throughput than their fair share to other queues. If the resulting loss of fairness is undesired (e.g., in a server system), it is certainly better to switch low_latency off.

When hierarchical scheduling is enabled, queues are collected in a tree of groups, and there is a distinct B-WFQ2+ scheduler on each non-leaf node. Leaf nodes are request queues as in the non-hierarchical case.

BFQ supports ioprio classes at each hierarchy level, enforcing a strict priority ordering among classes. This means that idle queues/groups are served only if there are no best effort queues/group in the same scheduler, and best effort queues/groups are served only if there are no real-time queues/groups.
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