License cleanup: add SPDX GPL-2.0 license identifier to files with no license
Many source files in the tree are missing licensing information, which
makes it harder for compliance tools to determine the correct license.
By default all files without license information are under the default
license of the kernel, which is GPL version 2.
Update the files which contain no license information with the 'GPL-2.0'
SPDX license identifier. The SPDX identifier is a legally binding
shorthand, which can be used instead of the full boiler plate text.
This patch is based on work done by Thomas Gleixner and Kate Stewart and
Philippe Ombredanne.
How this work was done:
Patches were generated and checked against linux-4.14-rc6 for a subset of
the use cases:
- file had no licensing information it it.
- file was a */uapi/* one with no licensing information in it,
- file was a */uapi/* one with existing licensing information,
Further patches will be generated in subsequent months to fix up cases
where non-standard license headers were used, and references to license
had to be inferred by heuristics based on keywords.
The analysis to determine which SPDX License Identifier to be applied to
a file was done in a spreadsheet of side by side results from of the
output of two independent scanners (ScanCode & Windriver) producing SPDX
tag:value files created by Philippe Ombredanne. Philippe prepared the
base worksheet, and did an initial spot review of a few 1000 files.
The 4.13 kernel was the starting point of the analysis with 60,537 files
assessed. Kate Stewart did a file by file comparison of the scanner
results in the spreadsheet to determine which SPDX license identifier(s)
to be applied to the file. She confirmed any determination that was not
immediately clear with lawyers working with the Linux Foundation.
Criteria used to select files for SPDX license identifier tagging was:
- Files considered eligible had to be source code files.
- Make and config files were included as candidates if they contained >5
lines of source
- File already had some variant of a license header in it (even if <5
lines).
All documentation files were explicitly excluded.
The following heuristics were used to determine which SPDX license
identifiers to apply.
- when both scanners couldn't find any license traces, file was
considered to have no license information in it, and the top level
COPYING file license applied.
For non */uapi/* files that summary was:
SPDX license identifier # files
---------------------------------------------------|-------
GPL-2.0 11139
and resulted in the first patch in this series.
If that file was a */uapi/* path one, it was "GPL-2.0 WITH
Linux-syscall-note" otherwise it was "GPL-2.0". Results of that was:
SPDX license identifier # files
---------------------------------------------------|-------
GPL-2.0 WITH Linux-syscall-note 930
and resulted in the second patch in this series.
- if a file had some form of licensing information in it, and was one
of the */uapi/* ones, it was denoted with the Linux-syscall-note if
any GPL family license was found in the file or had no licensing in
it (per prior point). Results summary:
SPDX license identifier # files
---------------------------------------------------|------
GPL-2.0 WITH Linux-syscall-note 270
GPL-2.0+ WITH Linux-syscall-note 169
((GPL-2.0 WITH Linux-syscall-note) OR BSD-2-Clause) 21
((GPL-2.0 WITH Linux-syscall-note) OR BSD-3-Clause) 17
LGPL-2.1+ WITH Linux-syscall-note 15
GPL-1.0+ WITH Linux-syscall-note 14
((GPL-2.0+ WITH Linux-syscall-note) OR BSD-3-Clause) 5
LGPL-2.0+ WITH Linux-syscall-note 4
LGPL-2.1 WITH Linux-syscall-note 3
((GPL-2.0 WITH Linux-syscall-note) OR MIT) 3
((GPL-2.0 WITH Linux-syscall-note) AND MIT) 1
and that resulted in the third patch in this series.
- when the two scanners agreed on the detected license(s), that became
the concluded license(s).
- when there was disagreement between the two scanners (one detected a
license but the other didn't, or they both detected different
licenses) a manual inspection of the file occurred.
- In most cases a manual inspection of the information in the file
resulted in a clear resolution of the license that should apply (and
which scanner probably needed to revisit its heuristics).
- When it was not immediately clear, the license identifier was
confirmed with lawyers working with the Linux Foundation.
- If there was any question as to the appropriate license identifier,
the file was flagged for further research and to be revisited later
in time.
In total, over 70 hours of logged manual review was done on the
spreadsheet to determine the SPDX license identifiers to apply to the
source files by Kate, Philippe, Thomas and, in some cases, confirmation
by lawyers working with the Linux Foundation.
Kate also obtained a third independent scan of the 4.13 code base from
FOSSology, and compared selected files where the other two scanners
disagreed against that SPDX file, to see if there was new insights. The
Windriver scanner is based on an older version of FOSSology in part, so
they are related.
Thomas did random spot checks in about 500 files from the spreadsheets
for the uapi headers and agreed with SPDX license identifier in the
files he inspected. For the non-uapi files Thomas did random spot checks
in about 15000 files.
In initial set of patches against 4.14-rc6, 3 files were found to have
copy/paste license identifier errors, and have been fixed to reflect the
correct identifier.
Additionally Philippe spent 10 hours this week doing a detailed manual
inspection and review of the 12,461 patched files from the initial patch
version early this week with:
- a full scancode scan run, collecting the matched texts, detected
license ids and scores
- reviewing anything where there was a license detected (about 500+
files) to ensure that the applied SPDX license was correct
- reviewing anything where there was no detection but the patch license
was not GPL-2.0 WITH Linux-syscall-note to ensure that the applied
SPDX license was correct
This produced a worksheet with 20 files needing minor correction. This
worksheet was then exported into 3 different .csv files for the
different types of files to be modified.
These .csv files were then reviewed by Greg. Thomas wrote a script to
parse the csv files and add the proper SPDX tag to the file, in the
format that the file expected. This script was further refined by Greg
based on the output to detect more types of files automatically and to
distinguish between header and source .c files (which need different
comment types.) Finally Greg ran the script using the .csv files to
generate the patches.
Reviewed-by: Kate Stewart <kstewart@linuxfoundation.org>
Reviewed-by: Philippe Ombredanne <pombredanne@nexb.com>
Reviewed-by: Thomas Gleixner <tglx@linutronix.de>
Signed-off-by: Greg Kroah-Hartman <gregkh@linuxfoundation.org>
2017-11-01 15:07:57 +01:00
|
|
|
// SPDX-License-Identifier: GPL-2.0
|
dql: Dynamic queue limits
Implementation of dynamic queue limits (dql). This is a libary which
allows a queue limit to be dynamically managed. The goal of dql is
to set the queue limit, number of objects to the queue, to be minimized
without allowing the queue to be starved.
dql would be used with a queue which has these properties:
1) Objects are queued up to some limit which can be expressed as a
count of objects.
2) Periodically a completion process executes which retires consumed
objects.
3) Starvation occurs when limit has been reached, all queued data has
actually been consumed but completion processing has not yet run,
so queuing new data is blocked.
4) Minimizing the amount of queued data is desirable.
A canonical example of such a queue would be a NIC HW transmit queue.
The queue limit is dynamic, it will increase or decrease over time
depending on the workload. The queue limit is recalculated each time
completion processing is done. Increases occur when the queue is
starved and can exponentially increase over successive intervals.
Decreases occur when more data is being maintained in the queue than
needed to prevent starvation. The number of extra objects, or "slack",
is measured over successive intervals, and to avoid hysteresis the
limit is only reduced by the miminum slack seen over a configurable
time period.
dql API provides routines to manage the queue:
- dql_init is called to intialize the dql structure
- dql_reset is called to reset dynamic values
- dql_queued called when objects are being enqueued
- dql_avail returns availability in the queue
- dql_completed is called when objects have be consumed in the queue
Configuration consists of:
- max_limit, maximum limit
- min_limit, minimum limit
- slack_hold_time, time to measure instances of slack before reducing
queue limit
Signed-off-by: Tom Herbert <therbert@google.com>
Acked-by: Eric Dumazet <eric.dumazet@gmail.com>
Signed-off-by: David S. Miller <davem@davemloft.net>
2011-11-28 17:32:35 +01:00
|
|
|
/*
|
|
|
|
* Dynamic byte queue limits. See include/linux/dynamic_queue_limits.h
|
|
|
|
*
|
|
|
|
* Copyright (c) 2011, Tom Herbert <therbert@google.com>
|
|
|
|
*/
|
|
|
|
#include <linux/types.h>
|
|
|
|
#include <linux/kernel.h>
|
2012-03-12 03:59:43 +01:00
|
|
|
#include <linux/jiffies.h>
|
dql: Dynamic queue limits
Implementation of dynamic queue limits (dql). This is a libary which
allows a queue limit to be dynamically managed. The goal of dql is
to set the queue limit, number of objects to the queue, to be minimized
without allowing the queue to be starved.
dql would be used with a queue which has these properties:
1) Objects are queued up to some limit which can be expressed as a
count of objects.
2) Periodically a completion process executes which retires consumed
objects.
3) Starvation occurs when limit has been reached, all queued data has
actually been consumed but completion processing has not yet run,
so queuing new data is blocked.
4) Minimizing the amount of queued data is desirable.
A canonical example of such a queue would be a NIC HW transmit queue.
The queue limit is dynamic, it will increase or decrease over time
depending on the workload. The queue limit is recalculated each time
completion processing is done. Increases occur when the queue is
starved and can exponentially increase over successive intervals.
Decreases occur when more data is being maintained in the queue than
needed to prevent starvation. The number of extra objects, or "slack",
is measured over successive intervals, and to avoid hysteresis the
limit is only reduced by the miminum slack seen over a configurable
time period.
dql API provides routines to manage the queue:
- dql_init is called to intialize the dql structure
- dql_reset is called to reset dynamic values
- dql_queued called when objects are being enqueued
- dql_avail returns availability in the queue
- dql_completed is called when objects have be consumed in the queue
Configuration consists of:
- max_limit, maximum limit
- min_limit, minimum limit
- slack_hold_time, time to measure instances of slack before reducing
queue limit
Signed-off-by: Tom Herbert <therbert@google.com>
Acked-by: Eric Dumazet <eric.dumazet@gmail.com>
Signed-off-by: David S. Miller <davem@davemloft.net>
2011-11-28 17:32:35 +01:00
|
|
|
#include <linux/dynamic_queue_limits.h>
|
2015-02-13 00:02:37 +01:00
|
|
|
#include <linux/compiler.h>
|
|
|
|
#include <linux/export.h>
|
dql: Dynamic queue limits
Implementation of dynamic queue limits (dql). This is a libary which
allows a queue limit to be dynamically managed. The goal of dql is
to set the queue limit, number of objects to the queue, to be minimized
without allowing the queue to be starved.
dql would be used with a queue which has these properties:
1) Objects are queued up to some limit which can be expressed as a
count of objects.
2) Periodically a completion process executes which retires consumed
objects.
3) Starvation occurs when limit has been reached, all queued data has
actually been consumed but completion processing has not yet run,
so queuing new data is blocked.
4) Minimizing the amount of queued data is desirable.
A canonical example of such a queue would be a NIC HW transmit queue.
The queue limit is dynamic, it will increase or decrease over time
depending on the workload. The queue limit is recalculated each time
completion processing is done. Increases occur when the queue is
starved and can exponentially increase over successive intervals.
Decreases occur when more data is being maintained in the queue than
needed to prevent starvation. The number of extra objects, or "slack",
is measured over successive intervals, and to avoid hysteresis the
limit is only reduced by the miminum slack seen over a configurable
time period.
dql API provides routines to manage the queue:
- dql_init is called to intialize the dql structure
- dql_reset is called to reset dynamic values
- dql_queued called when objects are being enqueued
- dql_avail returns availability in the queue
- dql_completed is called when objects have be consumed in the queue
Configuration consists of:
- max_limit, maximum limit
- min_limit, minimum limit
- slack_hold_time, time to measure instances of slack before reducing
queue limit
Signed-off-by: Tom Herbert <therbert@google.com>
Acked-by: Eric Dumazet <eric.dumazet@gmail.com>
Signed-off-by: David S. Miller <davem@davemloft.net>
2011-11-28 17:32:35 +01:00
|
|
|
|
2012-05-30 14:24:39 +02:00
|
|
|
#define POSDIFF(A, B) ((int)((A) - (B)) > 0 ? (A) - (B) : 0)
|
2012-05-30 14:25:19 +02:00
|
|
|
#define AFTER_EQ(A, B) ((int)((A) - (B)) >= 0)
|
dql: Dynamic queue limits
Implementation of dynamic queue limits (dql). This is a libary which
allows a queue limit to be dynamically managed. The goal of dql is
to set the queue limit, number of objects to the queue, to be minimized
without allowing the queue to be starved.
dql would be used with a queue which has these properties:
1) Objects are queued up to some limit which can be expressed as a
count of objects.
2) Periodically a completion process executes which retires consumed
objects.
3) Starvation occurs when limit has been reached, all queued data has
actually been consumed but completion processing has not yet run,
so queuing new data is blocked.
4) Minimizing the amount of queued data is desirable.
A canonical example of such a queue would be a NIC HW transmit queue.
The queue limit is dynamic, it will increase or decrease over time
depending on the workload. The queue limit is recalculated each time
completion processing is done. Increases occur when the queue is
starved and can exponentially increase over successive intervals.
Decreases occur when more data is being maintained in the queue than
needed to prevent starvation. The number of extra objects, or "slack",
is measured over successive intervals, and to avoid hysteresis the
limit is only reduced by the miminum slack seen over a configurable
time period.
dql API provides routines to manage the queue:
- dql_init is called to intialize the dql structure
- dql_reset is called to reset dynamic values
- dql_queued called when objects are being enqueued
- dql_avail returns availability in the queue
- dql_completed is called when objects have be consumed in the queue
Configuration consists of:
- max_limit, maximum limit
- min_limit, minimum limit
- slack_hold_time, time to measure instances of slack before reducing
queue limit
Signed-off-by: Tom Herbert <therbert@google.com>
Acked-by: Eric Dumazet <eric.dumazet@gmail.com>
Signed-off-by: David S. Miller <davem@davemloft.net>
2011-11-28 17:32:35 +01:00
|
|
|
|
|
|
|
/* Records completed count and recalculates the queue limit */
|
|
|
|
void dql_completed(struct dql *dql, unsigned int count)
|
|
|
|
{
|
|
|
|
unsigned int inprogress, prev_inprogress, limit;
|
2012-05-30 14:25:37 +02:00
|
|
|
unsigned int ovlimit, completed, num_queued;
|
2012-05-30 14:25:19 +02:00
|
|
|
bool all_prev_completed;
|
dql: Dynamic queue limits
Implementation of dynamic queue limits (dql). This is a libary which
allows a queue limit to be dynamically managed. The goal of dql is
to set the queue limit, number of objects to the queue, to be minimized
without allowing the queue to be starved.
dql would be used with a queue which has these properties:
1) Objects are queued up to some limit which can be expressed as a
count of objects.
2) Periodically a completion process executes which retires consumed
objects.
3) Starvation occurs when limit has been reached, all queued data has
actually been consumed but completion processing has not yet run,
so queuing new data is blocked.
4) Minimizing the amount of queued data is desirable.
A canonical example of such a queue would be a NIC HW transmit queue.
The queue limit is dynamic, it will increase or decrease over time
depending on the workload. The queue limit is recalculated each time
completion processing is done. Increases occur when the queue is
starved and can exponentially increase over successive intervals.
Decreases occur when more data is being maintained in the queue than
needed to prevent starvation. The number of extra objects, or "slack",
is measured over successive intervals, and to avoid hysteresis the
limit is only reduced by the miminum slack seen over a configurable
time period.
dql API provides routines to manage the queue:
- dql_init is called to intialize the dql structure
- dql_reset is called to reset dynamic values
- dql_queued called when objects are being enqueued
- dql_avail returns availability in the queue
- dql_completed is called when objects have be consumed in the queue
Configuration consists of:
- max_limit, maximum limit
- min_limit, minimum limit
- slack_hold_time, time to measure instances of slack before reducing
queue limit
Signed-off-by: Tom Herbert <therbert@google.com>
Acked-by: Eric Dumazet <eric.dumazet@gmail.com>
Signed-off-by: David S. Miller <davem@davemloft.net>
2011-11-28 17:32:35 +01:00
|
|
|
|
locking/atomics: COCCINELLE/treewide: Convert trivial ACCESS_ONCE() patterns to READ_ONCE()/WRITE_ONCE()
Please do not apply this to mainline directly, instead please re-run the
coccinelle script shown below and apply its output.
For several reasons, it is desirable to use {READ,WRITE}_ONCE() in
preference to ACCESS_ONCE(), and new code is expected to use one of the
former. So far, there's been no reason to change most existing uses of
ACCESS_ONCE(), as these aren't harmful, and changing them results in
churn.
However, for some features, the read/write distinction is critical to
correct operation. To distinguish these cases, separate read/write
accessors must be used. This patch migrates (most) remaining
ACCESS_ONCE() instances to {READ,WRITE}_ONCE(), using the following
coccinelle script:
----
// Convert trivial ACCESS_ONCE() uses to equivalent READ_ONCE() and
// WRITE_ONCE()
// $ make coccicheck COCCI=/home/mark/once.cocci SPFLAGS="--include-headers" MODE=patch
virtual patch
@ depends on patch @
expression E1, E2;
@@
- ACCESS_ONCE(E1) = E2
+ WRITE_ONCE(E1, E2)
@ depends on patch @
expression E;
@@
- ACCESS_ONCE(E)
+ READ_ONCE(E)
----
Signed-off-by: Mark Rutland <mark.rutland@arm.com>
Signed-off-by: Paul E. McKenney <paulmck@linux.vnet.ibm.com>
Cc: Linus Torvalds <torvalds@linux-foundation.org>
Cc: Peter Zijlstra <peterz@infradead.org>
Cc: Thomas Gleixner <tglx@linutronix.de>
Cc: davem@davemloft.net
Cc: linux-arch@vger.kernel.org
Cc: mpe@ellerman.id.au
Cc: shuah@kernel.org
Cc: snitzer@redhat.com
Cc: thor.thayer@linux.intel.com
Cc: tj@kernel.org
Cc: viro@zeniv.linux.org.uk
Cc: will.deacon@arm.com
Link: http://lkml.kernel.org/r/1508792849-3115-19-git-send-email-paulmck@linux.vnet.ibm.com
Signed-off-by: Ingo Molnar <mingo@kernel.org>
2017-10-23 23:07:29 +02:00
|
|
|
num_queued = READ_ONCE(dql->num_queued);
|
2012-05-30 14:25:37 +02:00
|
|
|
|
dql: Dynamic queue limits
Implementation of dynamic queue limits (dql). This is a libary which
allows a queue limit to be dynamically managed. The goal of dql is
to set the queue limit, number of objects to the queue, to be minimized
without allowing the queue to be starved.
dql would be used with a queue which has these properties:
1) Objects are queued up to some limit which can be expressed as a
count of objects.
2) Periodically a completion process executes which retires consumed
objects.
3) Starvation occurs when limit has been reached, all queued data has
actually been consumed but completion processing has not yet run,
so queuing new data is blocked.
4) Minimizing the amount of queued data is desirable.
A canonical example of such a queue would be a NIC HW transmit queue.
The queue limit is dynamic, it will increase or decrease over time
depending on the workload. The queue limit is recalculated each time
completion processing is done. Increases occur when the queue is
starved and can exponentially increase over successive intervals.
Decreases occur when more data is being maintained in the queue than
needed to prevent starvation. The number of extra objects, or "slack",
is measured over successive intervals, and to avoid hysteresis the
limit is only reduced by the miminum slack seen over a configurable
time period.
dql API provides routines to manage the queue:
- dql_init is called to intialize the dql structure
- dql_reset is called to reset dynamic values
- dql_queued called when objects are being enqueued
- dql_avail returns availability in the queue
- dql_completed is called when objects have be consumed in the queue
Configuration consists of:
- max_limit, maximum limit
- min_limit, minimum limit
- slack_hold_time, time to measure instances of slack before reducing
queue limit
Signed-off-by: Tom Herbert <therbert@google.com>
Acked-by: Eric Dumazet <eric.dumazet@gmail.com>
Signed-off-by: David S. Miller <davem@davemloft.net>
2011-11-28 17:32:35 +01:00
|
|
|
/* Can't complete more than what's in queue */
|
2012-05-30 14:25:37 +02:00
|
|
|
BUG_ON(count > num_queued - dql->num_completed);
|
dql: Dynamic queue limits
Implementation of dynamic queue limits (dql). This is a libary which
allows a queue limit to be dynamically managed. The goal of dql is
to set the queue limit, number of objects to the queue, to be minimized
without allowing the queue to be starved.
dql would be used with a queue which has these properties:
1) Objects are queued up to some limit which can be expressed as a
count of objects.
2) Periodically a completion process executes which retires consumed
objects.
3) Starvation occurs when limit has been reached, all queued data has
actually been consumed but completion processing has not yet run,
so queuing new data is blocked.
4) Minimizing the amount of queued data is desirable.
A canonical example of such a queue would be a NIC HW transmit queue.
The queue limit is dynamic, it will increase or decrease over time
depending on the workload. The queue limit is recalculated each time
completion processing is done. Increases occur when the queue is
starved and can exponentially increase over successive intervals.
Decreases occur when more data is being maintained in the queue than
needed to prevent starvation. The number of extra objects, or "slack",
is measured over successive intervals, and to avoid hysteresis the
limit is only reduced by the miminum slack seen over a configurable
time period.
dql API provides routines to manage the queue:
- dql_init is called to intialize the dql structure
- dql_reset is called to reset dynamic values
- dql_queued called when objects are being enqueued
- dql_avail returns availability in the queue
- dql_completed is called when objects have be consumed in the queue
Configuration consists of:
- max_limit, maximum limit
- min_limit, minimum limit
- slack_hold_time, time to measure instances of slack before reducing
queue limit
Signed-off-by: Tom Herbert <therbert@google.com>
Acked-by: Eric Dumazet <eric.dumazet@gmail.com>
Signed-off-by: David S. Miller <davem@davemloft.net>
2011-11-28 17:32:35 +01:00
|
|
|
|
|
|
|
completed = dql->num_completed + count;
|
|
|
|
limit = dql->limit;
|
2012-05-30 14:25:37 +02:00
|
|
|
ovlimit = POSDIFF(num_queued - dql->num_completed, limit);
|
|
|
|
inprogress = num_queued - completed;
|
dql: Dynamic queue limits
Implementation of dynamic queue limits (dql). This is a libary which
allows a queue limit to be dynamically managed. The goal of dql is
to set the queue limit, number of objects to the queue, to be minimized
without allowing the queue to be starved.
dql would be used with a queue which has these properties:
1) Objects are queued up to some limit which can be expressed as a
count of objects.
2) Periodically a completion process executes which retires consumed
objects.
3) Starvation occurs when limit has been reached, all queued data has
actually been consumed but completion processing has not yet run,
so queuing new data is blocked.
4) Minimizing the amount of queued data is desirable.
A canonical example of such a queue would be a NIC HW transmit queue.
The queue limit is dynamic, it will increase or decrease over time
depending on the workload. The queue limit is recalculated each time
completion processing is done. Increases occur when the queue is
starved and can exponentially increase over successive intervals.
Decreases occur when more data is being maintained in the queue than
needed to prevent starvation. The number of extra objects, or "slack",
is measured over successive intervals, and to avoid hysteresis the
limit is only reduced by the miminum slack seen over a configurable
time period.
dql API provides routines to manage the queue:
- dql_init is called to intialize the dql structure
- dql_reset is called to reset dynamic values
- dql_queued called when objects are being enqueued
- dql_avail returns availability in the queue
- dql_completed is called when objects have be consumed in the queue
Configuration consists of:
- max_limit, maximum limit
- min_limit, minimum limit
- slack_hold_time, time to measure instances of slack before reducing
queue limit
Signed-off-by: Tom Herbert <therbert@google.com>
Acked-by: Eric Dumazet <eric.dumazet@gmail.com>
Signed-off-by: David S. Miller <davem@davemloft.net>
2011-11-28 17:32:35 +01:00
|
|
|
prev_inprogress = dql->prev_num_queued - dql->num_completed;
|
2012-05-30 14:25:19 +02:00
|
|
|
all_prev_completed = AFTER_EQ(completed, dql->prev_num_queued);
|
dql: Dynamic queue limits
Implementation of dynamic queue limits (dql). This is a libary which
allows a queue limit to be dynamically managed. The goal of dql is
to set the queue limit, number of objects to the queue, to be minimized
without allowing the queue to be starved.
dql would be used with a queue which has these properties:
1) Objects are queued up to some limit which can be expressed as a
count of objects.
2) Periodically a completion process executes which retires consumed
objects.
3) Starvation occurs when limit has been reached, all queued data has
actually been consumed but completion processing has not yet run,
so queuing new data is blocked.
4) Minimizing the amount of queued data is desirable.
A canonical example of such a queue would be a NIC HW transmit queue.
The queue limit is dynamic, it will increase or decrease over time
depending on the workload. The queue limit is recalculated each time
completion processing is done. Increases occur when the queue is
starved and can exponentially increase over successive intervals.
Decreases occur when more data is being maintained in the queue than
needed to prevent starvation. The number of extra objects, or "slack",
is measured over successive intervals, and to avoid hysteresis the
limit is only reduced by the miminum slack seen over a configurable
time period.
dql API provides routines to manage the queue:
- dql_init is called to intialize the dql structure
- dql_reset is called to reset dynamic values
- dql_queued called when objects are being enqueued
- dql_avail returns availability in the queue
- dql_completed is called when objects have be consumed in the queue
Configuration consists of:
- max_limit, maximum limit
- min_limit, minimum limit
- slack_hold_time, time to measure instances of slack before reducing
queue limit
Signed-off-by: Tom Herbert <therbert@google.com>
Acked-by: Eric Dumazet <eric.dumazet@gmail.com>
Signed-off-by: David S. Miller <davem@davemloft.net>
2011-11-28 17:32:35 +01:00
|
|
|
|
|
|
|
if ((ovlimit && !inprogress) ||
|
|
|
|
(dql->prev_ovlimit && all_prev_completed)) {
|
|
|
|
/*
|
|
|
|
* Queue considered starved if:
|
|
|
|
* - The queue was over-limit in the last interval,
|
|
|
|
* and there is no more data in the queue.
|
|
|
|
* OR
|
|
|
|
* - The queue was over-limit in the previous interval and
|
|
|
|
* when enqueuing it was possible that all queued data
|
|
|
|
* had been consumed. This covers the case when queue
|
|
|
|
* may have becomes starved between completion processing
|
|
|
|
* running and next time enqueue was scheduled.
|
|
|
|
*
|
|
|
|
* When queue is starved increase the limit by the amount
|
|
|
|
* of bytes both sent and completed in the last interval,
|
|
|
|
* plus any previous over-limit.
|
|
|
|
*/
|
|
|
|
limit += POSDIFF(completed, dql->prev_num_queued) +
|
|
|
|
dql->prev_ovlimit;
|
|
|
|
dql->slack_start_time = jiffies;
|
|
|
|
dql->lowest_slack = UINT_MAX;
|
|
|
|
} else if (inprogress && prev_inprogress && !all_prev_completed) {
|
|
|
|
/*
|
|
|
|
* Queue was not starved, check if the limit can be decreased.
|
|
|
|
* A decrease is only considered if the queue has been busy in
|
|
|
|
* the whole interval (the check above).
|
|
|
|
*
|
|
|
|
* If there is slack, the amount of execess data queued above
|
|
|
|
* the the amount needed to prevent starvation, the queue limit
|
|
|
|
* can be decreased. To avoid hysteresis we consider the
|
|
|
|
* minimum amount of slack found over several iterations of the
|
|
|
|
* completion routine.
|
|
|
|
*/
|
|
|
|
unsigned int slack, slack_last_objs;
|
|
|
|
|
|
|
|
/*
|
|
|
|
* Slack is the maximum of
|
|
|
|
* - The queue limit plus previous over-limit minus twice
|
|
|
|
* the number of objects completed. Note that two times
|
|
|
|
* number of completed bytes is a basis for an upper bound
|
|
|
|
* of the limit.
|
|
|
|
* - Portion of objects in the last queuing operation that
|
|
|
|
* was not part of non-zero previous over-limit. That is
|
|
|
|
* "round down" by non-overlimit portion of the last
|
|
|
|
* queueing operation.
|
|
|
|
*/
|
|
|
|
slack = POSDIFF(limit + dql->prev_ovlimit,
|
|
|
|
2 * (completed - dql->num_completed));
|
|
|
|
slack_last_objs = dql->prev_ovlimit ?
|
|
|
|
POSDIFF(dql->prev_last_obj_cnt, dql->prev_ovlimit) : 0;
|
|
|
|
|
|
|
|
slack = max(slack, slack_last_objs);
|
|
|
|
|
|
|
|
if (slack < dql->lowest_slack)
|
|
|
|
dql->lowest_slack = slack;
|
|
|
|
|
|
|
|
if (time_after(jiffies,
|
|
|
|
dql->slack_start_time + dql->slack_hold_time)) {
|
|
|
|
limit = POSDIFF(limit, dql->lowest_slack);
|
|
|
|
dql->slack_start_time = jiffies;
|
|
|
|
dql->lowest_slack = UINT_MAX;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
/* Enforce bounds on limit */
|
|
|
|
limit = clamp(limit, dql->min_limit, dql->max_limit);
|
|
|
|
|
|
|
|
if (limit != dql->limit) {
|
|
|
|
dql->limit = limit;
|
|
|
|
ovlimit = 0;
|
|
|
|
}
|
|
|
|
|
|
|
|
dql->adj_limit = limit + completed;
|
|
|
|
dql->prev_ovlimit = ovlimit;
|
|
|
|
dql->prev_last_obj_cnt = dql->last_obj_cnt;
|
|
|
|
dql->num_completed = completed;
|
2012-05-30 14:25:37 +02:00
|
|
|
dql->prev_num_queued = num_queued;
|
dql: Dynamic queue limits
Implementation of dynamic queue limits (dql). This is a libary which
allows a queue limit to be dynamically managed. The goal of dql is
to set the queue limit, number of objects to the queue, to be minimized
without allowing the queue to be starved.
dql would be used with a queue which has these properties:
1) Objects are queued up to some limit which can be expressed as a
count of objects.
2) Periodically a completion process executes which retires consumed
objects.
3) Starvation occurs when limit has been reached, all queued data has
actually been consumed but completion processing has not yet run,
so queuing new data is blocked.
4) Minimizing the amount of queued data is desirable.
A canonical example of such a queue would be a NIC HW transmit queue.
The queue limit is dynamic, it will increase or decrease over time
depending on the workload. The queue limit is recalculated each time
completion processing is done. Increases occur when the queue is
starved and can exponentially increase over successive intervals.
Decreases occur when more data is being maintained in the queue than
needed to prevent starvation. The number of extra objects, or "slack",
is measured over successive intervals, and to avoid hysteresis the
limit is only reduced by the miminum slack seen over a configurable
time period.
dql API provides routines to manage the queue:
- dql_init is called to intialize the dql structure
- dql_reset is called to reset dynamic values
- dql_queued called when objects are being enqueued
- dql_avail returns availability in the queue
- dql_completed is called when objects have be consumed in the queue
Configuration consists of:
- max_limit, maximum limit
- min_limit, minimum limit
- slack_hold_time, time to measure instances of slack before reducing
queue limit
Signed-off-by: Tom Herbert <therbert@google.com>
Acked-by: Eric Dumazet <eric.dumazet@gmail.com>
Signed-off-by: David S. Miller <davem@davemloft.net>
2011-11-28 17:32:35 +01:00
|
|
|
}
|
|
|
|
EXPORT_SYMBOL(dql_completed);
|
|
|
|
|
|
|
|
void dql_reset(struct dql *dql)
|
|
|
|
{
|
|
|
|
/* Reset all dynamic values */
|
|
|
|
dql->limit = 0;
|
|
|
|
dql->num_queued = 0;
|
|
|
|
dql->num_completed = 0;
|
|
|
|
dql->last_obj_cnt = 0;
|
|
|
|
dql->prev_num_queued = 0;
|
|
|
|
dql->prev_last_obj_cnt = 0;
|
|
|
|
dql->prev_ovlimit = 0;
|
|
|
|
dql->lowest_slack = UINT_MAX;
|
|
|
|
dql->slack_start_time = jiffies;
|
|
|
|
}
|
|
|
|
EXPORT_SYMBOL(dql_reset);
|
|
|
|
|
2017-10-18 02:16:52 +02:00
|
|
|
void dql_init(struct dql *dql, unsigned int hold_time)
|
dql: Dynamic queue limits
Implementation of dynamic queue limits (dql). This is a libary which
allows a queue limit to be dynamically managed. The goal of dql is
to set the queue limit, number of objects to the queue, to be minimized
without allowing the queue to be starved.
dql would be used with a queue which has these properties:
1) Objects are queued up to some limit which can be expressed as a
count of objects.
2) Periodically a completion process executes which retires consumed
objects.
3) Starvation occurs when limit has been reached, all queued data has
actually been consumed but completion processing has not yet run,
so queuing new data is blocked.
4) Minimizing the amount of queued data is desirable.
A canonical example of such a queue would be a NIC HW transmit queue.
The queue limit is dynamic, it will increase or decrease over time
depending on the workload. The queue limit is recalculated each time
completion processing is done. Increases occur when the queue is
starved and can exponentially increase over successive intervals.
Decreases occur when more data is being maintained in the queue than
needed to prevent starvation. The number of extra objects, or "slack",
is measured over successive intervals, and to avoid hysteresis the
limit is only reduced by the miminum slack seen over a configurable
time period.
dql API provides routines to manage the queue:
- dql_init is called to intialize the dql structure
- dql_reset is called to reset dynamic values
- dql_queued called when objects are being enqueued
- dql_avail returns availability in the queue
- dql_completed is called when objects have be consumed in the queue
Configuration consists of:
- max_limit, maximum limit
- min_limit, minimum limit
- slack_hold_time, time to measure instances of slack before reducing
queue limit
Signed-off-by: Tom Herbert <therbert@google.com>
Acked-by: Eric Dumazet <eric.dumazet@gmail.com>
Signed-off-by: David S. Miller <davem@davemloft.net>
2011-11-28 17:32:35 +01:00
|
|
|
{
|
|
|
|
dql->max_limit = DQL_MAX_LIMIT;
|
|
|
|
dql->min_limit = 0;
|
|
|
|
dql->slack_hold_time = hold_time;
|
|
|
|
dql_reset(dql);
|
|
|
|
}
|
|
|
|
EXPORT_SYMBOL(dql_init);
|