block, bfq: add description of weight-raising heuristics

A description of how weight raising works is missing in BFQ
sources. In addition, the code for handling weight raising is
scattered across a few functions. This makes it rather hard to
understand the mechanism and its rationale. This commits adds such a
description at the beginning of the main source file.

Signed-off-by: Paolo Valente <paolo.valente@linaro.org>
Signed-off-by: Jens Axboe <axboe@kernel.dk>

1 files changed, 56 insertions, 24 deletions

diff --git a/block/bfq-iosched.c b/block/bfq-iosched.c
index dd527bab57c2..e68d0a4159c4 100644
--- a/block/bfq-iosched.c
+++ b/block/bfq-iosched.c
@@ -49,9 +49,39 @@
  *
  * In particular, to provide these low-latency guarantees, BFQ
  * explicitly privileges the I/O of two classes of time-sensitive
- * applications: interactive and soft real-time. This feature enables
- * BFQ to provide applications in these classes with a very low
- * latency. Finally, BFQ also features additional heuristics for
+ * applications: interactive and soft real-time. In more detail, BFQ
+ * behaves this way if the low_latency parameter is set (default
+ * configuration). This feature enables BFQ to provide applications in
+ * these classes with a very low latency.
+ *
+ * To implement this feature, BFQ constantly tries to detect whether
+ * the I/O requests in a bfq_queue come from an interactive or a soft
+ * real-time application. For brevity, in these cases, the queue is
+ * said to be interactive or soft real-time. In both cases, BFQ
+ * privileges the service of the queue, over that of non-interactive
+ * and non-soft-real-time queues. This privileging is performed,
+ * mainly, by raising the weight of the queue. So, for brevity, we
+ * call just weight-raising periods the time periods during which a
+ * queue is privileged, because deemed interactive or soft real-time.
+ *
+ * The detection of soft real-time queues/applications is described in
+ * detail in the comments on the function
+ * bfq_bfqq_softrt_next_start. On the other hand, the detection of an
+ * interactive queue works as follows: a queue is deemed interactive
+ * if it is constantly non empty only for a limited time interval,
+ * after which it does become empty. The queue may be deemed
+ * interactive again (for a limited time), if it restarts being
+ * constantly non empty, provided that this happens only after the
+ * queue has remained empty for a given minimum idle time.
+ *
+ * By default, BFQ computes automatically the above maximum time
+ * interval, i.e., the time interval after which a constantly
+ * non-empty queue stops being deemed interactive. Since a queue is
+ * weight-raised while it is deemed interactive, this maximum time
+ * interval happens to coincide with the (maximum) duration of the
+ * weight-raising for interactive queues.
+ *
+ * Finally, BFQ also features additional heuristics for
  * preserving both a low latency and a high throughput on NCQ-capable,
  * rotational or flash-based devices, and to get the job done quickly
  * for applications consisting in many I/O-bound processes.
@@ -61,14 +91,14 @@
  * all low-latency heuristics for that device, by setting low_latency
  * to 0.
  *
- * BFQ is described in [1], where also a reference to the initial, more
- * theoretical paper on BFQ can be found. The interested reader can find
- * in the latter paper full details on the main algorithm, as well as
- * formulas of the guarantees and formal proofs of all the properties.
- * With respect to the version of BFQ presented in these papers, this
- * implementation adds a few more heuristics, such as the one that
- * guarantees a low latency to soft real-time applications, and a
- * hierarchical extension based on H-WF2Q+.
+ * BFQ is described in [1], where also a reference to the initial,
+ * more theoretical paper on BFQ can be found. The interested reader
+ * can find in the latter paper full details on the main algorithm, as
+ * well as formulas of the guarantees and formal proofs of all the
+ * properties.  With respect to the version of BFQ presented in these
+ * papers, this implementation adds a few more heuristics, such as the
+ * ones that guarantee a low latency to interactive and soft real-time
+ * applications, and a hierarchical extension based on H-WF2Q+.
  *
  * B-WF2Q+ is based on WF2Q+, which is described in [2], together with
  * H-WF2Q+, while the augmented tree used here to implement B-WF2Q+
@@ -218,21 +248,23 @@ static struct kmem_cache *bfq_pool;
 #define BFQ_RATE_SHIFT		16
 
 /*
- * By default, BFQ computes the duration of the weight raising for
- * interactive applications automatically, using the following formula:
- * duration = (R / r) * T, where r is the peak rate of the device, and
- * R and T are two reference parameters.
- * In particular, R is the peak rate of the reference device (see
- * below), and T is a reference time: given the systems that are
- * likely to be installed on the reference device according to its
- * speed class, T is about the maximum time needed, under BFQ and
+ * When configured for computing the duration of the weight-raising
+ * for interactive queues automatically (see the comments at the
+ * beginning of this file), BFQ does it using the following formula:
+ * duration = (R / r) * T,
+ * where r is the peak rate of the device, and R
+ * and T are two reference parameters.	In particular,
+ * R is the peak rate of the reference device (see below), and
+ * T is a reference time: given the systems that are likely
+ * to be installed on the reference device according to its speed
+ * class, T is about the maximum time needed, under BFQ and
  * while reading two files in parallel, to load typical large
  * applications on these systems (see the comments on
- * max_service_from_wr below, for more details on how T is obtained).
- * In practice, the slower/faster the device at hand is, the more/less
- * it takes to load applications with respect to the reference device.
- * Accordingly, the longer/shorter BFQ grants weight raising to
- * interactive applications.
+ * max_service_from_wr below, for more details on how T is
+ * obtained).  In practice, the slower/faster the device at hand is,
+ * the more/less it takes to load applications with respect to the
+ * reference device.  Accordingly, the longer/shorter BFQ grants
+ * weight raising to interactive applications.
  *
  * BFQ uses four different reference pairs (R, T), depending on:
  * . whether the device is rotational or non-rotational;