This function is not used anywhere in the kernel.
Signed-off-by: NChristoph Hellwig <hch@lst.de>
Reviewed-by: NJohannes Thumshirn <jthumshirn@suse.de>
Signed-off-by: NJens Axboe <axboe@fb.com>

Both functions are entirely unused.
Signed-off-by: NChristoph Hellwig <hch@lst.de>
Reviewed-by: NJohannes Thumshirn <jthumshirn@suse.de>
Signed-off-by: NJens Axboe <axboe@fb.com>

This was just a proof of concept user for the SCSI OSD library, and
never had any real users.
Signed-off-by: NChristoph Hellwig <hch@lst.de>
Acked-by: NBoaz Harrosh <ooo@electrozaur.com>
Signed-off-by: NJens Axboe <axboe@fb.com>

When CFQ is used as an elevator, it disables writeback throttling
because they don't play well together. Later when a different elevator
is chosen for the device, writeback throttling doesn't get enabled
again as it should. Make sure CFQ enables writeback throttling (if it
should be enabled by default) when we switch from it to another IO
scheduler.
Signed-off-by: NJan Kara <jack@suse.cz>
Signed-off-by: NJens Axboe <axboe@fb.com>

The BFQ I/O scheduler features an optimal fair-queuing
(proportional-share) scheduling algorithm, enriched with several
mechanisms to boost throughput and reduce latency for interactive and
real-time applications. This makes BFQ a large and complex piece of
code. This commit addresses this issue by splitting BFQ into three
main, independent components, and by moving each component into a
separate source file:
1. Main algorithm: handles the interaction with the kernel, and
decides which requests to dispatch; it uses the following two further
components to achieve its goals.
2. Scheduling engine (Hierarchical B-WF2Q+ scheduling algorithm):
computes the schedule, using weights and budgets provided by the above
component.
3. cgroups support: handles group operations (creation, destruction,
move, ...).
Signed-off-by: NPaolo Valente <paolo.valente@linaro.org>
Signed-off-by: NJens Axboe <axboe@fb.com>

When a bfq queue is set in service and when it is merged, a reference
to the I/O context associated with the queue is taken. This reference
is then released when the queue is deselected from service or
split. More precisely, the release of the reference is postponed to
when the scheduler lock is released, to avoid nesting between the
scheduler and the I/O-context lock. In fact, such nesting would lead
to deadlocks, because of other code paths that take the same locks in
the opposite order. This postponing of I/O-context releases does
complicate code.

This commit addresses these issue by modifying involved operations in
such a way to not need to get the above I/O-context references any
more. Then it also removes any get and release of these references.
Signed-off-by: NPaolo Valente <paolo.valente@linaro.org>
Signed-off-by: NJens Axboe <axboe@fb.com>

Many popular I/O-intensive services or applications spawn or
reactivate many parallel threads/processes during short time
intervals. Examples are systemd during boot or git grep.  These
services or applications benefit mostly from a high throughput: the
quicker the I/O generated by their processes is cumulatively served,
the sooner the target job of these services or applications gets
completed. As a consequence, it is almost always counterproductive to
weight-raise any of the queues associated to the processes of these
services or applications: in most cases it would just lower the
throughput, mainly because weight-raising also implies device idling.

To address this issue, an I/O scheduler needs, first, to detect which
queues are associated with these services or applications. In this
respect, we have that, from the I/O-scheduler standpoint, these
services or applications cause bursts of activations, i.e.,
activations of different queues occurring shortly after each
other. However, a shorter burst of activations may be caused also by
the start of an application that does not consist in a lot of parallel
I/O-bound threads (see the comments on the function bfq_handle_burst
for details).

In view of these facts, this commit introduces:
1) an heuristic to detect (only) bursts of queue activations caused by
   services or applications consisting in many parallel I/O-bound
   threads;
2) the prevention of device idling and weight-raising for the queues
   belonging to these bursts.
Signed-off-by: NArianna Avanzini <avanzini.arianna@gmail.com>
Signed-off-by: NPaolo Valente <paolo.valente@linaro.org>
Signed-off-by: NJens Axboe <axboe@fb.com>

This patch is basically the counterpart, for NCQ-capable rotational
devices, of the previous patch. Exactly as the previous patch does on
flash-based devices and for any workload, this patch disables device
idling on rotational devices, but only for random I/O. In fact, only
with these queues disabling idling boosts the throughput on
NCQ-capable rotational devices. To not break service guarantees,
idling is disabled for NCQ-enabled rotational devices only when the
same symmetry conditions considered in the previous patches hold.
Signed-off-by: NPaolo Valente <paolo.valente@linaro.org>
Signed-off-by: NArianna Avanzini <avanzini.arianna@gmail.com>
Signed-off-by: NJens Axboe <axboe@fb.com>

This patch boosts the throughput on NCQ-capable flash-based devices,
while still preserving latency guarantees for interactive and soft
real-time applications. The throughput is boosted by just not idling
the device when the in-service queue remains empty, even if the queue
is sync and has a non-null idle window. This helps to keep the drive's
internal queue full, which is necessary to achieve maximum
performance. This solution to boost the throughput is a port of
commits a68bbddb and f7d7b7a7 for CFQ.

As already highlighted in a previous patch, allowing the device to
prefetch and internally reorder requests trivially causes loss of
control on the request service order, and hence on service guarantees.
Fortunately, as discussed in detail in the comments on the function
bfq_bfqq_may_idle(), if every process has to receive the same
fraction of the throughput, then the service order enforced by the
internal scheduler of a flash-based device is relatively close to that
enforced by BFQ. In particular, it is close enough to let service
guarantees be substantially preserved.

Things change in an asymmetric scenario, i.e., if not every process
has to receive the same fraction of the throughput. In this case, to
guarantee the desired throughput distribution, the device must be
prevented from prefetching requests. This is exactly what this patch
does in asymmetric scenarios.
Signed-off-by: NPaolo Valente <paolo.valente@linaro.org>
Signed-off-by: NArianna Avanzini <avanzini.arianna@gmail.com>
Signed-off-by: NJens Axboe <axboe@fb.com>

A seeky queue (i..e, a queue containing random requests) is assigned a
very small device-idling slice, for throughput issues. Unfortunately,
given the process associated with a seeky queue, this behavior causes
the following problem: if the process, say P, performs sync I/O and
has a higher weight than some other processes doing I/O and associated
with non-seeky queues, then BFQ may fail to guarantee to P its
reserved share of the throughput. The reason is that idling is key
for providing service guarantees to processes doing sync I/O [1].

This commit addresses this issue by allowing the device-idling slice
to be reduced for a seeky queue only if the scenario happens to be
symmetric, i.e., if all the queues are to receive the same share of
the throughput.

[1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O
    Scheduler", Proceedings of the First Workshop on Mobile System
    Technologies (MST-2015), May 2015.
    http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdfSigned-off-by: NArianna Avanzini <avanzini.arianna@gmail.com>
Signed-off-by: NRiccardo Pizzetti <riccardo.pizzetti@gmail.com>
Signed-off-by: NSamuele Zecchini <samuele.zecchini92@gmail.com>
Signed-off-by: NPaolo Valente <paolo.valente@linaro.org>
Signed-off-by: NJens Axboe <axboe@fb.com>

A set of processes may happen to perform interleaved reads, i.e.,
read requests whose union would give rise to a sequential read pattern.
There are two typical cases: first, processes reading fixed-size chunks
of data at a fixed distance from each other; second, processes reading
variable-size chunks at variable distances. The latter case occurs for
example with QEMU, which splits the I/O generated by a guest into
multiple chunks, and lets these chunks be served by a pool of I/O
threads, iteratively assigning the next chunk of I/O to the first
available thread. CFQ denotes as 'cooperating' a set of processes that
are doing interleaved I/O, and when it detects cooperating processes,
it merges their queues to obtain a sequential I/O pattern from the union
of their I/O requests, and hence boost the throughput.

Unfortunately, in the following frequent case, the mechanism
implemented in CFQ for detecting cooperating processes and merging
their queues is not responsive enough to handle also the fluctuating
I/O pattern of the second type of processes. Suppose that one process
of the second type issues a request close to the next request to serve
of another process of the same type. At that time the two processes
would be considered as cooperating. But, if the request issued by the
first process is to be merged with some other already-queued request,
then, from the moment at which this request arrives, to the moment
when CFQ controls whether the two processes are cooperating, the two
processes are likely to be already doing I/O in distant zones of the
disk surface or device memory.

CFQ uses however preemption to get a sequential read pattern out of
the read requests performed by the second type of processes too.  As a
consequence, CFQ 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 to immediately check whether a newly-arrived request lets some
pair of processes become cooperating, both in the case of actual
request insertion and, to be responsive with the second type of
processes, in the case of request merge. Both types of processes are
then handled by just merging their queues.
Signed-off-by: NArianna Avanzini <avanzini.arianna@gmail.com>
Signed-off-by: NMauro Andreolini <mauro.andreolini@unimore.it>
Signed-off-by: NPaolo Valente <paolo.valente@linaro.org>
Signed-off-by: NJens Axboe <axboe@fb.com>

This patch introduces an heuristic that reduces latency when the
I/O-request pool is saturated. This goal is achieved by disabling
device idling, for non-weight-raised queues, when there are weight-
raised queues with pending or in-flight requests. In fact, as
explained in more detail in the comment on the function
bfq_bfqq_may_idle(), this reduces the rate at which processes
associated with non-weight-raised queues grab requests from the pool,
thereby increasing the probability that processes associated with
weight-raised queues get a request immediately (or at least soon) when
they need one. Along the same line, if there are weight-raised queues,
then this patch halves the service rate of async (write) requests for
non-weight-raised queues.
Signed-off-by: NPaolo Valente <paolo.valente@linaro.org>
Signed-off-by: NArianna Avanzini <avanzini.arianna@gmail.com>
Signed-off-by: NJens Axboe <axboe@fb.com>

I/O schedulers typically allow NCQ-capable drives to prefetch I/O
requests, as NCQ boosts the throughput exactly by prefetching and
internally reordering requests.

Unfortunately, as discussed in detail and shown experimentally in [1],
this may cause fairness and latency guarantees to be violated. The
main problem is that the internal scheduler of an NCQ-capable drive
may postpone the service of some unlucky (prefetched) requests as long
as it deems serving other requests more appropriate to boost the
throughput.

This patch addresses this issue by not disabling device idling for
weight-raised queues, even if the device supports NCQ. This allows BFQ
to start serving a new queue, and therefore allows the drive to
prefetch new requests, only after the idling timeout expires. At that
time, all the outstanding requests of the expired queue have been most
certainly served.

[1] P. Valente and M. Andreolini, "Improving Application
    Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of
    the 5th Annual International Systems and Storage Conference
    (SYSTOR '12), June 2012.
    Slightly extended version:
    http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite-
							results.pdf
Signed-off-by: NPaolo Valente <paolo.valente@linaro.org>
Signed-off-by: NArianna Avanzini <avanzini.arianna@gmail.com>
Signed-off-by: NJens Axboe <axboe@fb.com>

To guarantee a low latency also to the I/O requests issued by soft
real-time applications, this patch introduces a further heuristic,
which weight-raises (in the sense explained in the previous patch)
also the queues associated to applications deemed as soft real-time.

To be deemed as soft real-time, an application must meet two
requirements.  First, the application must not require an average
bandwidth higher than the approximate bandwidth required to playback
or record a compressed high-definition video. Second, the request
pattern of the application must be isochronous, i.e., after issuing a
request or a batch of requests, the application must stop issuing new
requests until all its pending requests have been completed. After
that, the application may issue a new batch, and so on.

As for the second requirement, it is critical to require also that,
after all the pending requests of the application have been completed,
an adequate minimum amount of time elapses before the application
starts issuing new requests. This prevents also greedy (i.e.,
I/O-bound) applications from being incorrectly deemed, occasionally,
as soft real-time. In fact, if *any amount of time* is fine, then even
a greedy application may, paradoxically, meet both the above
requirements, if: (1) the application performs random I/O and/or the
device is slow, and (2) the CPU load is high. The reason is the
following.  First, if condition (1) is true, then, during the service
of the application, the throughput may be low enough to let the
application meet the bandwidth requirement.  Second, if condition (2)
is true as well, then the application may occasionally behave in an
apparently isochronous way, because it may simply stop issuing
requests while the CPUs are busy serving other processes.

To address this issue, the heuristic leverages the simple fact that
greedy applications issue *all* their requests as quickly as they can,
whereas soft real-time applications spend some time processing data
after each batch of requests is completed. In particular, the
heuristic works as follows. First, according to the above isochrony
requirement, the heuristic checks whether an application may be soft
real-time, thereby giving to the application the opportunity to be
deemed as such, only when both the following two conditions happen to
hold: 1) the queue associated with the application has expired and is
empty, 2) there is no outstanding request of the application.

Suppose that both conditions hold at time, say, t_c and that the
application issues its next request at time, say, t_i. At time t_c the
heuristic computes the next time instant, called soft_rt_next_start in
the code, such that, only if t_i >= soft_rt_next_start, then both the
next conditions will hold when the application issues its next
request: 1) the application will meet the above bandwidth requirement,
2) a given minimum time interval, say Delta, will have elapsed from
time t_c (so as to filter out greedy application).

The current value of Delta is a little bit higher than the value that
we have found, experimentally, to be adequate on a real,
general-purpose machine. In particular we had to increase Delta to
make the filter quite precise also in slower, embedded systems, and in
KVM/QEMU virtual machines (details in the comments on the code).

If the application actually issues its next request after time
soft_rt_next_start, then its associated queue will be weight-raised
for a relatively short time interval. If, during this time interval,
the application proves again to meet the bandwidth and isochrony
requirements, then the end of the weight-raising period for the queue
is moved forward, and so on. Note that an application whose associated
queue never happens to be empty when it expires will never have the
opportunity to be deemed as soft real-time.
Signed-off-by: NPaolo Valente <paolo.valente@linaro.org>
Signed-off-by: NArianna Avanzini <avanzini.arianna@gmail.com>
Signed-off-by: NJens Axboe <axboe@fb.com>

This patch introduces a simple heuristic to load applications quickly,
and to perform the I/O requested by interactive applications just as
quickly. To this purpose, both a newly-created queue and a queue
associated with an interactive application (we explain in a moment how
BFQ decides whether the associated application is interactive),
receive the following two special treatments:

1) The weight of the queue is raised.

2) The queue unconditionally enjoys device idling when it empties; in
fact, if the requests of a queue are sync, then performing device
idling for the queue is a necessary condition to guarantee that the
queue receives a fraction of the throughput proportional to its weight
(see [1] for details).

For brevity, we call just weight-raising the combination of these
two preferential treatments. For a newly-created queue,
weight-raising starts immediately and lasts for a time interval that:
1) depends on the device speed and type (rotational or
non-rotational), and 2) is equal to the time needed to load (start up)
a large-size application on that device, with cold caches and with no
additional workload.

Finally, as for guaranteeing a fast execution to interactive,
I/O-related tasks (such as opening a file), consider that any
interactive application blocks and waits for user input both after
starting up and after executing some task. After a while, the user may
trigger new operations, after which the application stops again, and
so on. Accordingly, the low-latency heuristic weight-raises again a
queue in case it becomes backlogged after being idle for a
sufficiently long (configurable) time. The weight-raising then lasts
for the same time as for a just-created queue.

According to our experiments, the combination of this low-latency
heuristic and of the improvements described in the previous patch
allows BFQ to guarantee a high application responsiveness.

[1] P. Valente, A. Avanzini, "Evolution of the BFQ Storage I/O
    Scheduler", Proceedings of the First Workshop on Mobile System
    Technologies (MST-2015), May 2015.
    http://algogroup.unimore.it/people/paolo/disk_sched/mst-2015.pdfSigned-off-by: NPaolo Valente <paolo.valente@linaro.org>
Signed-off-by: NArianna Avanzini <avanzini.arianna@gmail.com>
Signed-off-by: NJens Axboe <axboe@fb.com>

This patch deals with two sources of unfairness, which can also cause
high latencies and throughput loss. The first source is related to
write requests. Write requests tend to starve read requests, basically
because, on one side, writes are slower than reads, whereas, on the
other side, storage devices confuse schedulers by deceptively
signaling the completion of write requests immediately after receiving
them. This patch addresses this issue by just throttling writes. In
particular, after a write request is dispatched for a queue, the
budget of the queue is decremented by the number of sectors to write,
multiplied by an (over)charge coefficient. The value of the
coefficient is the result of our tuning with different devices.

The second source of unfairness has to do with slowness detection:
when the in-service queue is expired, BFQ also controls whether the
queue has been "too slow", i.e., has consumed its last-assigned budget
at such a low rate that it would have been impossible to consume all
of this budget within the maximum time slice T_max (Subsec. 3.5 in
[1]). In this case, the queue is always (over)charged the whole
budget, to reduce its utilization of the device. Both this overcharge
and the slowness-detection criterion may cause unfairness.

First, always charging a full budget to a slow queue is too coarse. It
is much more accurate, and this patch lets BFQ do so, to charge an
amount of service 'equivalent' to the amount of time during which the
queue has been in service. As explained in more detail in the comments
on the code, this enables BFQ to provide time fairness among slow
queues.

Secondly, because of ZBR, a queue may be deemed as slow when its
associated process is performing I/O on the slowest zones of a
disk. However, unless the process is truly too slow, not reducing the
disk utilization of the queue is more profitable in terms of disk
throughput than the opposite. A similar problem is caused by logical
block mapping on non-rotational devices. For this reason, this patch
lets a queue be charged time, and not budget, only if the queue has
consumed less than 2/3 of its assigned budget. As an additional,
important benefit, this tolerance allows BFQ to preserve enough
elasticity to still perform bandwidth, and not time, distribution with
little unlucky or quasi-sequential processes.

Finally, for the same reasons as above, this patch makes slowness
detection itself much less harsh: a queue is deemed slow only if it
has consumed its budget at less than half of the peak rate.

[1] P. Valente and M. Andreolini, "Improving Application
    Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of
    the 5th Annual International Systems and Storage Conference
    (SYSTOR '12), June 2012.
    Slightly extended version:
    http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite-
							results.pdf
Signed-off-by: NPaolo Valente <paolo.valente@linaro.org>
Signed-off-by: NArianna Avanzini <avanzini.arianna@gmail.com>
Signed-off-by: NJens Axboe <axboe@fb.com>

Unless the maximum budget B_max that BFQ can assign to a queue is set
explicitly by the user, BFQ automatically updates B_max. In
particular, BFQ dynamically sets B_max to the number of sectors that
can be read, at the current estimated peak rate, during the maximum
time, T_max, allowed before a budget timeout occurs. In formulas, if
we denote as R_est the estimated peak rate, then B_max = T_max ∗
R_est. Hence, the higher R_est is with respect to the actual device
peak rate, the higher the probability that processes incur budget
timeouts unjustly is. Besides, a too high value of B_max unnecessarily
increases the deviation from an ideal, smooth service.

Unfortunately, it is not trivial to estimate the peak rate correctly:
because of the presence of sw and hw queues between the scheduler and
the device components that finally serve I/O requests, it is hard to
say exactly when a given dispatched request is served inside the
device, and for how long. As a consequence, it is hard to know
precisely at what rate a given set of requests is actually served by
the device.

On the opposite end, the dispatch time of any request is trivially
available, and, from this piece of information, the "dispatch rate"
of requests can be immediately computed. So, the idea in the next
function is to use what is known, namely request dispatch times
(plus, when useful, request completion times), to estimate what is
unknown, namely in-device request service rate.

The main issue is that, because of the above facts, the rate at
which a certain set of requests is dispatched over a certain time
interval can vary greatly with respect to the rate at which the
same requests are then served. But, since the size of any
intermediate queue is limited, and the service scheme is lossless
(no request is silently dropped), the following obvious convergence
property holds: the number of requests dispatched MUST become
closer and closer to the number of requests completed as the
observation interval grows. This is the key property used in
this new version of the peak-rate estimator.
Signed-off-by: NPaolo Valente <paolo.valente@linaro.org>
Signed-off-by: NArianna Avanzini <avanzini.arianna@gmail.com>
Signed-off-by: NJens Axboe <axboe@fb.com>

The feedback-loop algorithm used by BFQ to compute queue (process)
budgets is basically a set of three update rules, one for each of the
main reasons why a queue may be expired. If many processes suddenly
switch from sporadic I/O to greedy and sequential I/O, then these
rules are quite slow to assign large budgets to these processes, and
hence to achieve a high throughput. On the opposite side, BFQ assigns
the maximum possible budget B_max to a just-created queue. This allows
a high throughput to be achieved immediately if the associated process
is I/O-bound and performs sequential I/O from the beginning. But it
also increases the worst-case latency experienced by the first
requests issued by the process, because the larger the budget of a
queue waiting for service is, the later the queue will be served by
B-WF2Q+ (Subsec 3.3 in [1]). This is detrimental for an interactive or
soft real-time application.

To tackle these throughput and latency problems, on one hand this
patch changes the initial budget value to B_max/2. On the other hand,
it re-tunes the three rules, adopting a more aggressive,
multiplicative increase/linear decrease scheme. This scheme trades
latency for throughput more than before, and tends to assign large
budgets quickly to processes that are or become I/O-bound. For two of
the expiration reasons, the new version of the rules also contains
some more little improvements, briefly described below.

*No more backlog.* In this case, the budget was larger than the number
of sectors actually read/written by the process before it stopped
doing I/O. Hence, to reduce latency for the possible future I/O
requests of the process, the old rule simply set the next budget to
the number of sectors actually consumed by the process. However, if
there are still outstanding requests, then the process may have not
yet issued its next request just because it is still waiting for the
completion of some of the still outstanding ones. If this sub-case
holds true, then the new rule, instead of decreasing the budget,
doubles it, proactively, in the hope that: 1) a larger budget will fit
the actual needs of the process, and 2) the process is sequential and
hence a higher throughput will be achieved by serving the process
longer after granting it access to the device.

*Budget timeout*. The original rule set the new budget to the maximum
value B_max, to maximize throughput and let all processes experiencing
budget timeouts receive the same share of the device time. In our
experiments we verified that this sudden jump to B_max did not provide
sensible benefits; rather it increased the latency of processes
performing sporadic and short I/O. The new rule only doubles the
budget.

[1] P. Valente and M. Andreolini, "Improving Application
    Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of
    the 5th Annual International Systems and Storage Conference
    (SYSTOR '12), June 2012.
    Slightly extended version:
    http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite-
							results.pdf
Signed-off-by: NPaolo Valente <paolo.valente@linaro.org>
Signed-off-by: NArianna Avanzini <avanzini.arianna@gmail.com>
Signed-off-by: NJens Axboe <axboe@fb.com>

Add complete support for full hierarchical scheduling, with a cgroups
interface. Full hierarchical scheduling is implemented through the
'entity' abstraction: both bfq_queues, i.e., the internal BFQ queues
associated with processes, and groups are represented in general by
entities. Given the bfq_queues associated with the processes belonging
to a given group, the entities representing these queues are sons of
the entity representing the group. At higher levels, if a group, say
G, contains other groups, then the entity representing G is the parent
entity of the entities representing the groups in G.

Hierarchical scheduling is performed as follows: if the timestamps of
a leaf entity (i.e., of a bfq_queue) change, and such a change lets
the entity become the next-to-serve entity for its parent entity, then
the timestamps of the parent entity are recomputed as a function of
the budget of its new next-to-serve leaf entity. If the parent entity
belongs, in its turn, to a group, and its new timestamps let it become
the next-to-serve for its parent entity, then the timestamps of the
latter parent entity are recomputed as well, and so on. When a new
bfq_queue must be set in service, the reverse path is followed: the
next-to-serve highest-level entity is chosen, then its next-to-serve
child entity, and so on, until the next-to-serve leaf entity is
reached, and the bfq_queue that this entity represents is set in
service.

Writeback is accounted for on a per-group basis, i.e., for each group,
the async I/O requests of the processes of the group are enqueued in a
distinct bfq_queue, and the entity associated with this queue is a
child of the entity associated with the group.

Weights can be assigned explicitly to groups and processes through the
cgroups interface, differently from what happens, for single
processes, if the cgroups interface is not used (as explained in the
description of the previous patch). In particular, since each node has
a full scheduler, each group can be assigned its own weight.
Signed-off-by: NFabio Checconi <fchecconi@gmail.com>
Signed-off-by: NPaolo Valente <paolo.valente@linaro.org>
Signed-off-by: NArianna Avanzini <avanzini.arianna@gmail.com>
Signed-off-by: NJens Axboe <axboe@fb.com>

We tag as v0 the version of BFQ containing only BFQ's engine plus
hierarchical support. BFQ's engine is introduced by this commit, while
hierarchical support is added by next commit. We use the v0 tag to
distinguish this minimal version of BFQ from the versions containing
also the features and the improvements added by next commits. BFQ-v0
coincides with the version of BFQ submitted a few years ago [1], apart
from the introduction of preemption, described below.

BFQ is a proportional-share I/O scheduler, whose general structure,
plus a lot of code, are borrowed from CFQ.

- Each process doing I/O on a device is associated with a weight and a
  (bfq_)queue.

- BFQ grants exclusive access to the device, for a while, to one queue
  (process) at a time, and implements this service model by
  associating every queue with a budget, measured in number of
  sectors.

  - After a queue is granted access to the device, the budget of the
    queue is decremented, on each request dispatch, by the size of the
    request.

  - The in-service queue is expired, i.e., its service is suspended,
    only if one of the following events occurs: 1) the queue finishes
    its budget, 2) the queue empties, 3) a "budget timeout" fires.

    - The budget timeout prevents processes doing random I/O from
      holding the device for too long and dramatically reducing
      throughput.

    - Actually, as in CFQ, a queue associated with a process issuing
      sync requests may not be expired immediately when it empties. In
      contrast, BFQ may idle the device for a short time interval,
      giving the process the chance to go on being served if it issues
      a new request in time. Device idling typically boosts the
      throughput on rotational devices, if processes do synchronous
      and sequential I/O. In addition, under BFQ, device idling is
      also instrumental in guaranteeing the desired throughput
      fraction to processes issuing sync requests (see [2] for
      details).

      - With respect to idling for service guarantees, if several
        processes are competing for the device at the same time, but
        all processes (and groups, after the following commit) have
        the same weight, then BFQ guarantees the expected throughput
        distribution without ever idling the device. Throughput is
        thus as high as possible in this common scenario.

  - Queues are scheduled according to a variant of WF2Q+, named
    B-WF2Q+, and implemented using an augmented rb-tree to preserve an
    O(log N) overall complexity.  See [2] for more details. B-WF2Q+ is
    also ready for hierarchical scheduling. However, for a cleaner
    logical breakdown, the code that enables and completes
    hierarchical support is provided in the next commit, which focuses
    exactly on this feature.

  - B-WF2Q+ guarantees a tight deviation with respect to an ideal,
    perfectly fair, and smooth service. In particular, B-WF2Q+
    guarantees that each queue receives a fraction of the device
    throughput proportional to its weight, even if the throughput
    fluctuates, and regardless of: the device parameters, the current
    workload and the budgets assigned to the queue.

  - The last, budget-independence, property (although probably
    counterintuitive in the first place) is definitely beneficial, for
    the following reasons:

    - First, with any proportional-share scheduler, the maximum
      deviation with respect to an ideal service is proportional to
      the maximum budget (slice) assigned to queues. As a consequence,
      BFQ can keep this deviation tight not only because of the
      accurate service of B-WF2Q+, but also because BFQ *does not*
      need to assign a larger budget to a queue to let the queue
      receive a higher fraction of the device throughput.

    - Second, BFQ is free to choose, for every process (queue), the
      budget that best fits the needs of the process, or best
      leverages the I/O pattern of the process. In particular, BFQ
      updates queue budgets with a simple feedback-loop algorithm that
      allows a high throughput to be achieved, while still providing
      tight latency guarantees to time-sensitive applications. When
      the in-service queue expires, this algorithm computes the next
      budget of the queue so as to:

      - Let large budgets be eventually assigned to the queues
        associated with I/O-bound applications performing sequential
        I/O: in fact, the longer these applications are served once
        got access to the device, the higher the throughput is.

      - Let small budgets be eventually assigned to the queues
        associated with time-sensitive applications (which typically
        perform sporadic and short I/O), because, the smaller the
        budget assigned to a queue waiting for service is, the sooner
        B-WF2Q+ will serve that queue (Subsec 3.3 in [2]).

- Weights can be assigned to processes only indirectly, through I/O
  priorities, and according to the relation:
  weight = 10 * (IOPRIO_BE_NR - ioprio).
  The next patch provides, instead, a cgroups interface through which
  weights can be assigned explicitly.

- If several processes are competing for the device at the same time,
  but all processes and groups have the same weight, then BFQ
  guarantees the expected throughput distribution without ever idling
  the device. It uses preemption instead. Throughput is then much
  higher in this common scenario.

- 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.

- If the strict_guarantees parameter is set (default: unset), then BFQ
     - always performs idling when the in-service queue becomes empty;
     - forces the device to serve one I/O request at a time, by
       dispatching a new request only if there is no outstanding
       request.
  In the presence of differentiated weights or I/O-request sizes,
  both the above conditions are needed to guarantee that every
  queue receives its allotted share of the bandwidth (see
  Documentation/block/bfq-iosched.txt for more details). Setting
  strict_guarantees may evidently affect throughput.

[1] https://lkml.org/lkml/2008/4/1/234
    https://lkml.org/lkml/2008/11/11/148

[2] P. Valente and M. Andreolini, "Improving Application
    Responsiveness with the BFQ Disk I/O Scheduler", Proceedings of
    the 5th Annual International Systems and Storage Conference
    (SYSTOR '12), June 2012.
    Slightly extended version:
    http://algogroup.unimore.it/people/paolo/disk_sched/bfq-v1-suite-
							results.pdf
Signed-off-by: NFabio Checconi <fchecconi@gmail.com>
Signed-off-by: NPaolo Valente <paolo.valente@linaro.org>
Signed-off-by: NArianna Avanzini <avanzini.arianna@gmail.com>
Signed-off-by: NJens Axboe <axboe@fb.com>

NBD doesn't care about limiting the segment size, let the user push the
largest bio's they want.  This allows us to control the request size
solely through max_sectors_kb.
Signed-off-by: NJosef Bacik <jbacik@fb.com>
Reviewed-by: NMing Lei <ming.lei@redhat.com>
Signed-off-by: NJens Axboe <axboe@fb.com>

Merge branch 'stable/for-jens-4.12' of git://git.kernel.org/pub/scm/linux/kernel/git/konrad/xen into for-4.12/block

Konrad writes:

It has one fix - to emit an uevent whenever the size of the guest disk image
changes.

When a blkfront device is resized from dom0, emit a KOBJ_CHANGE uevent to
notify the guest about the change. This allows for custom udev rules, such
as automatically resizing a filesystem, when an event occurs.

With this patch you get these udev

KERNEL[577.206230] change   /devices/vbd-51728/block/xvdb (block)
UDEV  [577.226218] change   /devices/vbd-51728/block/xvdb (block)
Signed-off-by: NMarc Olson <marcolso@amazon.com>
Signed-off-by: NKonrad Rzeszutek Wilk <konrad.wilk@oracle.com>

For ease of management it would be nice for users to specify that the
device node for a nbd device is destroyed once it is disconnected and
there are no more users.  Add a client flag and enable this operation to
happen.
Signed-off-by: NJosef Bacik <jbacik@fb.com>
Signed-off-by: NJens Axboe <axboe@fb.com>

In order to support deleting the device on disconnect we need to
refcount the actual nbd_device struct.  So add the refcounting framework
and change how we free the normal devices at rmmod time so we can catch
reference leaks.
Signed-off-by: NJosef Bacik <jbacik@fb.com>
Signed-off-by: NJens Axboe <axboe@fb.com>

Allow users to query the status of existing nbd devices.  Right now this
only returns whether or not the device is connected, but could be
extended in the future to include more information.
Signed-off-by: NJosef Bacik <jbacik@fb.com>
Signed-off-by: NJens Axboe <axboe@fb.com>

Sometimes we like to upgrade our server without making all of our
clients freak out and reconnect.  This patch provides a way to specify a
dead connection timeout to allow us to pause all requests and wait for
new connections to be opened.  With this in place I can take down the
nbd server for less than the dead connection timeout time and bring it
back up and everything resumes gracefully.
Signed-off-by: NJosef Bacik <jbacik@fb.com>
Signed-off-by: NJens Axboe <axboe@fb.com>

When running a disconnect torture test I noticed that sometimes we would
crash with a negative ref count on our queue.  This was because we were
ending the same request twice.  Turns out we were racing with
NBD_CLEAR_SOCK clearing the requests as well as the teardown of the
device clearing the requests.  So instead make the ioctl only shutdown
the sockets and make it so that we only ever run nbd_clear_que from the
device teardown.
Signed-off-by: NJosef Bacik <jbacik@fb.com>
Signed-off-by: NJens Axboe <axboe@fb.com>

Provide a mechanism to notify userspace that there's been a link problem
on a NBD device.  This will allow userspace to re-establish a connection
and provide the new socket to the device without disrupting the device.
Signed-off-by: NJosef Bacik <jbacik@fb.com>
Signed-off-by: NJens Axboe <axboe@fb.com>

We want to be able to reconnect dead connections to existing block
devices, so add a reconfigure netlink command.  We will also allow users
to change their timeout on the fly, but everything else will require a
disconnect and reconnect.  You won't be able to add more connections
either, simply replace dead connections with new more lively
connections.
Signed-off-by: NJosef Bacik <jbacik@fb.com>
Signed-off-by: NJens Axboe <axboe@fb.com>

The existing ioctl interface for configuring NBD devices is a bit
cumbersome and hard to extend.  The other problem is we leave a
userspace app sitting in it's syscall until the device disconnects,
which is less than ideal.

This patch introduces a netlink interface for adding and disconnecting
nbd devices.  This has the benefits of being easily extendable without
breaking older userspace applications, and allows us to configure a nbd
device without leaving a userspace app sitting waiting for the device to
disconnect.

With this interface we also gain the ability to configure more devices
than are preallocated at insmod time.  We also have gained the ability
to not specify a particular device and be provided one for us so that
userspace doesn't need to find a free device to configure.
Signed-off-by: NJosef Bacik <jbacik@fb.com>
Signed-off-by: NJens Axboe <axboe@fb.com>

In preparation for the upcoming netlink interface we need to not rely on
already having the bdev for the NBD device we are doing operations on.
Instead of passing the bdev around, just use it in places where we know
we already have the bdev.
Signed-off-by: NJosef Bacik <jbacik@fb.com>
Signed-off-by: NJens Axboe <axboe@fb.com>

In order to properly refcount the various aspects of a NBD device we
need to separate out the configuration elements of the nbd device.  The
configuration of a NBD device has a different lifetime from the actual
device, so it doesn't make sense to bundle these two concepts.  Add a
config_refs to keep track of the configuration structure, that way we
can be sure that we never access it when we've torn down the device.
Add a new nbd_config structure to hold all of the transient
configuration information.  Finally create this when we open the device
so that it is in place when we start to configure the device.  This has
a nice side-effect of fixing a long standing problem where you could end
up with a half-configured nbd device that needed to be "disconnected" in
order to be usable again.  Now once we close our device the
configuration will be discarded.
Signed-off-by: NJosef Bacik <jbacik@fb.com>
Signed-off-by: NJens Axboe <axboe@fb.com>

Currently if we have multiple connections and one of them goes down we will tear
down the whole device.  However there's no reason we need to do this as we
could have other connections that are working fine.  Deal with this by keeping
track of the state of the different connections, and if we lose one we mark it
as dead and send all IO destined for that socket to one of the other healthy
sockets.  Any outstanding requests that were on the dead socket will timeout and
be re-submitted properly.
Signed-off-by: NJosef Bacik <jbacik@fb.com>
Signed-off-by: NJens Axboe <axboe@fb.com>

When adding a new socket we look it up and then try to add it to our
configuration.  If any of those steps fail we need to make sure we put
the socket so we don't leak them.
Signed-off-by: NJosef Bacik <jbacik@fb.com>
Signed-off-by: NJens Axboe <axboe@fb.com>

There were a bunch of places in pblk_lines_init() where we didn't set an
error code.  And in pblk_writer_init() we accidentally return 1 instead
of a correct error code, which would result in a Oops later.

Fixes: 11a5d6fdf919 ("lightnvm: physical block device (pblk) target")
Signed-off-by: NDan Carpenter <dan.carpenter@oracle.com>
Signed-off-by: NMatias Bjørling <matias@cnexlabs.com>
Signed-off-by: NJens Axboe <axboe@fb.com>

WARN_ON() takes a condition, not an error message.  I slightly tweaked
some conditions so hopefully it's more clear.
Signed-off-by: NDan Carpenter <dan.carpenter@oracle.com>
Signed-off-by: NMatias Bjørling <matias@cnexlabs.com>
Signed-off-by: NJens Axboe <axboe@fb.com>

These labels are reversed so we could end up dereferencing an error
pointer or leaking.

Fixes: 7f347ba6bb3a ("lightnvm: physical block device (pblk) target")
Signed-off-by: NDan Carpenter <dan.carpenter@oracle.com>
Signed-off-by: NMatias Bjørling <matias@cnexlabs.com>
Signed-off-by: NJens Axboe <axboe@fb.com>

This patch introduces pblk, a host-side translation layer for
Open-Channel SSDs to expose them like block devices. The translation
layer allows data placement decisions, and I/O scheduling to be
managed by the host, enabling users to optimize the SSD for their
specific workloads.

An open-channel SSD has a set of LUNs (parallel units) and a
collection of blocks. Each block can be read in any order, but
writes must be sequential. Writes may also fail, and if a block
requires it, must also be reset before new writes can be
applied.

To manage the constraints, pblk maintains a logical to
physical address (L2P) table,  write cache, garbage
collection logic, recovery scheme, and logic to rate-limit
user I/Os versus garbage collection I/Os.

The L2P table is fully-associative and manages sectors at a
4KB granularity. Pblk stores the L2P table in two places, in
the out-of-band area of the media and on the last page of a
line. In the cause of a power failure, pblk will perform a
scan to recover the L2P table.

The user data is organized into lines. A line is data
striped across blocks and LUNs. The lines enable the host to
reduce the amount of metadata to maintain besides the user
data and makes it easier to implement RAID or erasure coding
in the future.

pblk implements multi-tenant support and can be instantiated
multiple times on the same drive. Each instance owns a
portion of the SSD - both regarding I/O bandwidth and
capacity - providing I/O isolation for each case.

Finally, pblk also exposes a sysfs interface that allows
user-space to peek into the internals of pblk. The interface
is available at /dev/block/*/pblk/ where * is the block
device name exposed.

This work also contains contributions from:
  Matias Bjørling <matias@cnexlabs.com>
  Simon A. F. Lund <slund@cnexlabs.com>
  Young Tack Jin <youngtack.jin@gmail.com>
  Huaicheng Li <huaicheng@cs.uchicago.edu>
Signed-off-by: NJavier González <javier@cnexlabs.com>
Signed-off-by: NMatias Bjørling <matias@cnexlabs.com>
Signed-off-by: NJens Axboe <axboe@fb.com>

Convert sprintf calls to strlcpy in order to make possible buffer
overflow more obvious.
Signed-off-by: NJavier González <javier@cnexlabs.com>
Signed-off-by: NMatias Bjørling <matias@cnexlabs.com>
Signed-off-by: NJens Axboe <axboe@fb.com>