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author | SeongJae Park <sj@kernel.org> | 2021-11-05 21:46:18 +0100 |
---|---|---|
committer | Linus Torvalds <torvalds@linux-foundation.org> | 2021-11-06 21:30:44 +0100 |
commit | fda504fade7f124858d7022341dc46ff35b45274 (patch) | |
tree | 3a13d9a06cc7972676750c8c8d45065cf4583324 /mm/damon | |
parent | mm/damon/core: nullify pointer ctx->kdamond with a NULL (diff) | |
download | linux-fda504fade7f124858d7022341dc46ff35b45274.tar.xz linux-fda504fade7f124858d7022341dc46ff35b45274.zip |
mm/damon/core: account age of target regions
Patch series "Implement Data Access Monitoring-based Memory Operation Schemes".
Introduction
============
DAMON[1] can be used as a primitive for data access aware memory
management optimizations. For that, users who want such optimizations
should run DAMON, read the monitoring results, analyze it, plan a new
memory management scheme, and apply the new scheme by themselves. Such
efforts will be inevitable for some complicated optimizations.
However, in many other cases, the users would simply want the system to
apply a memory management action to a memory region of a specific size
having a specific access frequency for a specific time. For example,
"page out a memory region larger than 100 MiB keeping only rare accesses
more than 2 minutes", or "Do not use THP for a memory region larger than
2 MiB rarely accessed for more than 1 seconds".
To make the works easier and non-redundant, this patchset implements a
new feature of DAMON, which is called Data Access Monitoring-based
Operation Schemes (DAMOS). Using the feature, users can describe the
normal schemes in a simple way and ask DAMON to execute those on its
own.
[1] https://damonitor.github.io
Evaluations
===========
DAMOS is accurate and useful for memory management optimizations. An
experimental DAMON-based operation scheme for THP, 'ethp', removes
76.15% of THP memory overheads while preserving 51.25% of THP speedup.
Another experimental DAMON-based 'proactive reclamation' implementation,
'prcl', reduces 93.38% of residential sets and 23.63% of system memory
footprint while incurring only 1.22% runtime overhead in the best case
(parsec3/freqmine).
NOTE that the experimental THP optimization and proactive reclamation
are not for production but only for proof of concepts.
Please refer to the showcase web site's evaluation document[1] for
detailed evaluation setup and results.
[1] https://damonitor.github.io/doc/html/v34/vm/damon/eval.html
Long-term Support Trees
-----------------------
For people who want to test DAMON but using LTS kernels, there are
another couple of trees based on two latest LTS kernels respectively and
containing the 'damon/master' backports.
- For v5.4.y: https://git.kernel.org/sj/h/damon/for-v5.4.y
- For v5.10.y: https://git.kernel.org/sj/h/damon/for-v5.10.y
Sequence Of Patches
===================
The 1st patch accounts age of each region. The 2nd patch implements the
core of the DAMON-based operation schemes feature. The 3rd patch makes
the default monitoring primitives for virtual address spaces to support
the schemes. From this point, the kernel space users can use DAMOS.
The 4th patch exports the feature to the user space via the debugfs
interface. The 5th patch implements schemes statistics feature for
easier tuning of the schemes and runtime access pattern analysis, and
the 6th patch adds selftests for these changes. Finally, the 7th patch
documents this new feature.
This patch (of 7):
DAMON can be used for data access pattern aware memory management
optimizations. For that, users should run DAMON, read the monitoring
results, analyze it, plan a new memory management scheme, and apply the
new scheme by themselves. It would not be too hard, but still require
some level of effort. For complicated cases, this effort is inevitable.
That said, in many cases, users would simply want to apply an actions to
a memory region of a specific size having a specific access frequency
for a specific time. For example, "page out a memory region larger than
100 MiB but having a low access frequency more than 10 minutes", or "Use
THP for a memory region larger than 2 MiB having a high access frequency
for more than 2 seconds".
For such optimizations, users will need to first account the age of each
region themselves. To reduce such efforts, this implements a simple age
account of each region in DAMON. For each aggregation step, DAMON
compares the access frequency with that from last aggregation and reset
the age of the region if the change is significant. Else, the age is
incremented. Also, in case of the merge of regions, the region
size-weighted average of the ages is set as the age of merged new
region.
Link: https://lkml.kernel.org/r/20211001125604.29660-1-sj@kernel.org
Link: https://lkml.kernel.org/r/20211001125604.29660-2-sj@kernel.org
Signed-off-by: SeongJae Park <sj@kernel.org>
Cc: Jonathan Cameron <Jonathan.Cameron@huawei.com>
Cc: Amit Shah <amit@kernel.org>
Cc: Benjamin Herrenschmidt <benh@kernel.crashing.org>
Cc: Jonathan Corbet <corbet@lwn.net>
Cc: David Hildenbrand <david@redhat.com>
Cc: David Woodhouse <dwmw@amazon.com>
Cc: Marco Elver <elver@google.com>
Cc: Leonard Foerster <foersleo@amazon.de>
Cc: Greg Thelen <gthelen@google.com>
Cc: Markus Boehme <markubo@amazon.de>
Cc: David Rienjes <rientjes@google.com>
Cc: Shakeel Butt <shakeelb@google.com>
Cc: Shuah Khan <shuah@kernel.org>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
Diffstat (limited to 'mm/damon')
-rw-r--r-- | mm/damon/core.c | 13 |
1 files changed, 13 insertions, 0 deletions
diff --git a/mm/damon/core.c b/mm/damon/core.c index d993db50280c..3efbe80779db 100644 --- a/mm/damon/core.c +++ b/mm/damon/core.c @@ -45,6 +45,9 @@ struct damon_region *damon_new_region(unsigned long start, unsigned long end) region->nr_accesses = 0; INIT_LIST_HEAD(®ion->list); + region->age = 0; + region->last_nr_accesses = 0; + return region; } @@ -444,6 +447,7 @@ static void kdamond_reset_aggregated(struct damon_ctx *c) damon_for_each_region(r, t) { trace_damon_aggregated(t, r, damon_nr_regions(t)); + r->last_nr_accesses = r->nr_accesses; r->nr_accesses = 0; } } @@ -461,6 +465,7 @@ static void damon_merge_two_regions(struct damon_target *t, l->nr_accesses = (l->nr_accesses * sz_l + r->nr_accesses * sz_r) / (sz_l + sz_r); + l->age = (l->age * sz_l + r->age * sz_r) / (sz_l + sz_r); l->ar.end = r->ar.end; damon_destroy_region(r, t); } @@ -480,6 +485,11 @@ static void damon_merge_regions_of(struct damon_target *t, unsigned int thres, struct damon_region *r, *prev = NULL, *next; damon_for_each_region_safe(r, next, t) { + if (diff_of(r->nr_accesses, r->last_nr_accesses) > thres) + r->age = 0; + else + r->age++; + if (prev && prev->ar.end == r->ar.start && diff_of(prev->nr_accesses, r->nr_accesses) <= thres && sz_damon_region(prev) + sz_damon_region(r) <= sz_limit) @@ -527,6 +537,9 @@ static void damon_split_region_at(struct damon_ctx *ctx, r->ar.end = new->ar.start; + new->age = r->age; + new->last_nr_accesses = r->last_nr_accesses; + damon_insert_region(new, r, damon_next_region(r), t); } |