From: SeongJae Park <[email protected]>
This RFC patchset introduces a new kernel module for practical monitoring of
data accesses, namely DAMON.
The patches are organized in the following sequence. The first and second
patch introduces the core logic and the raw level user interface of DAMON,
respectively. To provide a minimal reference to the raw level interfaces and
for more convenient test of the DAMON itself, the third patch implements an
user space wrapper tools for the DAMON. The fourth patch adds a document for
the DAMON, and finally the fifth patch provides DAMON's unit tests, which is
using the kunit framework.
The patches are based on the v5.4 plus the back-ported kunit, which retrieved
from v5.5-rc1. You can also clone the complete git tree by:
$ git clone git://github.com/sjp38/linux -b damon/rfc/v1
The web is also available:
https://github.com/sjp38/linux/releases/tag/damon/rfc/v1
----
DAMON is a kernel module that allows users to monitor the actual memory access
pattern of specific user-space processes. It aims to be 1) accurate enough to
be useful for performance-centric domains, and 2) sufficiently light-weight so
that it can be applied online.
For the goals, DAMON utilizes its two core mechanisms, called region-based
sampling and adaptive regions adjustment. The region-based sampling allows
users to make their own trade-off between the quality and the overhead of the
monitoring and set the upperbound of the monitoring overhead. Further, the
adaptive regions adjustment mechanism makes DAMON to maximize the quality and
minimize the overhead with its best efforts while preserving the users
configured trade-off.
Background
==========
For performance-centric analysis and optimizations of memory management schemes
(either that of kernel space or user space), the actual data access pattern of
the workloads is highly useful. The information need to be only reasonable
rather than strictly correct, because some level of incorrectness can be
handled in many performance-centric domains. It also need to be taken within
reasonably short time with only light-weight overhead.
Manually extracting such data is not easy and time consuming if the target
workload is huge and complex, even for the developers of the programs. There
are a range of tools and techniques developed for general memory access
investigations, and some of those could be partially used for this purpose.
However, most of those are not practical or unscalable, mainly because those
are designed with no consideration about the trade-off between the accuracy of
the output and the overhead.
The memory access instrumentation techniques which is applied to many tools
such as Intel PIN is essential for correctness required cases such as invalid
memory access bug detections. However, those usually incur high overhead which
is unacceptable for many of the performance-centric domains. Periodic access
checks based on H/W or S/W access counting features (e.g., the Accessed bits of
PTEs or the PG_Idle flags of pages) can dramatically decrease the overhead by
forgiving some of the quality, compared to the instrumentation based
techniques. The reduced quality is still reasonable for many of the domains,
but the overhead can arbitrarily increase as the size of the target workload
grows. Miniature-like static region based sampling can set the upperbound of
the overhead, but it will now decrease the quality of the output as the size of
the workload grows.
Related Works
=============
There are a number of researches[1,2,3,4,5,6] optimizing memory management
mechanisms based on the actual memory access patterns that shows impressive
results. However, most of those has no deep consideration about the monitoring
of the accesses itself. Some of those focused on the overhead of the
monitoring, but does not consider the accuracy scalability[6] or has additional
dependencies[7]. Indeed, one recent research[5] about the proactive
reclamation has also proposed[8] to the kernel community but the monitoring
overhead was considered a main problem.
[1] Subramanya R Dulloor, Amitabha Roy, Zheguang Zhao, Narayanan Sundaram,
Nadathur Satish, Rajesh Sankaran, Jeff Jackson, and Karsten Schwan. 2016.
Data tiering in heterogeneous memory systems. In Proceedings of the 11th
European Conference on Computer Systems (EuroSys). ACM, 15.
[2] Youngjin Kwon, Hangchen Yu, Simon Peter, Christopher J Rossbach, and Emmett
Witchel. 2016. Coordinated and efficient huge page management with ingens.
In 12th USENIX Symposium on Operating Systems Design and Implementation
(OSDI). 705–721.
[3] Harald Servat, Antonio J Peña, Germán Llort, Estanislao Mercadal,
HansChristian Hoppe, and Jesús Labarta. 2017. Automating the application
data placement in hybrid memory systems. In 2017 IEEE International
Conference on Cluster Computing (CLUSTER). IEEE, 126–136.
[4] Vlad Nitu, Boris Teabe, Alain Tchana, Canturk Isci, and Daniel Hagimont.
2018. Welcome to zombieland: practical and energy-efficient memory
disaggregation in a datacenter. In Proceedings of the 13th European
Conference on Computer Systems (EuroSys). ACM, 16.
[5] Andres Lagar-Cavilla, Junwhan Ahn, Suleiman Souhlal, Neha Agarwal, Radoslaw
Burny, Shakeel Butt, Jichuan Chang, Ashwin Chaugule, Nan Deng, Junaid
Shahid, Greg Thelen, Kamil Adam Yurtsever, Yu Zhao, and Parthasarathy
Ranganathan. 2019. Software-Defined Far Memory in Warehouse-Scale
Computers. In Proceedings of the 24th International Conference on
Architectural Support for Programming Languages and Operating Systems
(ASPLOS). ACM, New York, NY, USA, 317–330.
DOI:https://doi.org/10.1145/3297858.3304053
[6] Carl Waldspurger, Trausti Saemundsson, Irfan Ahmad, and Nohhyun Park.
2017. Cache Modeling and Optimization using Miniature Simulations. In 2017
USENIX Annual Technical Conference (ATC). USENIX Association, Santa
Clara, CA, 487–498.
https://www.usenix.org/conference/atc17/technical-sessions/
[7] Haojie Wang, Jidong Zhai, Xiongchao Tang, Bowen Yu, Xiaosong Ma, and
Wenguang Chen. 2018. Spindle: Informed Memory Access Monitoring. In 2018
USENIX Annual Technical Conference (ATC). USENIX Association, Boston, MA,
561–574. https://www.usenix.org/conference/atc18/presentation/wang-haojie
[8] Jonathan Corbet. 2019. Proactively reclaiming idle memory. (2019).
https://lwn.net/Articles/787611/.
Expected Use-cases
==================
A straightforward usecase of DAMON would be the program behavior analysis.
With the DAMON output, users can confirm whether the program is running as
intended or not. This will be useful for debuggings and tests of design
points.
The monitored results can also be useful for counting the dynamic working set
size of workloads. For the administration of memory overcommitted systems or
selection of the environments (e.g., containers providing different amount of
memory) for your workloads, this will be useful.
If you are a programmer, you can optimize your program by managing the memory
based on the actual data access pattern. For example, you can identify the
dynamic hotness of your data using DAMON and call ``mlock()`` to keep your hot
data in DRAM, or call ``madvise()`` with ``MADV_PAGEOUT`` to proactively
reclaim cold data. Even though your program is guaranteed to not encounter
memory pressure, you can still improve the performance by applying the DAMON
outputs for call of ``MADV_HUGEPAGE`` and ``MADV_NOHUGEPAGE``. More creative
optimizations would be possible. Our evaluations of DAMON includes a
straightforward optimization using the ``mlock()``. Please refer to the below
Evaluation section for more detail.
As DAMON incurs very low overhead, such optimizations can be applied not only
offline, but also online. Also, there is no reason to limit such optimizations
to the user space. Several parts of the kernel's memory management mechanisms
could be also optimized using DAMON. The reclamation, the THP (de)promotion
decisions, and the compaction would be such a candidates. Nevertheless,
current version of DAMON is not highly optimized for the online/in-kernel uses.
Mechanisms of DAMON
===================
Basic Access Check
------------------
DAMON basically reports what pages are how frequently accessed. The report is
passed to users in binary format via a ``result file`` which users can set it's
path. Note that the frequency is not an absolute number of accesses, but a
relative frequency among the pages of the target workloads.
Users can also control the resolution of the reports by setting two time
intervals, ``sampling interval`` and ``aggregation interval``. In detail,
DAMON checks access to each page per ``sampling interval``, aggregates the
results (counts the number of the accesses to each page), and reports the
aggregated results per ``aggregation interval``. For the access check of each
page, DAMON uses the Accessed bits of PTEs.
This is thus similar to the previously mentioned periodic access checks based
mechanisms, which overhead is increasing as the size of the target process
grows.
Region Based Sampling
---------------------
To avoid the unbounded increase of the overhead, DAMON groups a number of
adjacent pages that assumed to have same access frequencies into a region. As
long as the assumption (pages in a region have same access frequencies) is
kept, only one page in the region is required to be checked. Thus, for each
``sampling interval``, DAMON randomly picks one page in each region and clears
its Accessed bit. After one more ``sampling interval``, DAMON reads the
Accessed bit of the page and increases the access frequency of the region if
the bit has set meanwhile. Therefore, the monitoring overhead is controllable
by setting the number of regions. DAMON allows users to set the minimal and
maximum number of regions for the trade-off.
Except the assumption, this is almost same with the above-mentioned
miniature-like static region based sampling. In other words, this scheme
cannot preserve the quality of the output if the assumption is not guaranteed.
Adaptive Regions Adjustment
---------------------------
At the beginning of the monitoring, DAMON constructs the initial regions by
evenly splitting the memory mapped address space of the process into the
user-specified minimal number of regions. In this initial state, the
assumption is normally not kept and thus the quality could be low. To keep the
assumption as much as possible, DAMON adaptively merges and splits each region.
For each ``aggregation interval``, it compares the access frequencies of
adjacent regions and merges those if the frequency difference is small. Then,
after it reports and clears the aggregated access frequency of each region, it
splits each region into two regions if the total number of regions is smaller
than the half of the user-specified maximum number of regions.
In this way, DAMON provides its best-effort quality and minimal overhead while
keeping the bounds users set for their trade-off.
Applying Dynamic Memory Mappings
--------------------------------
Only a number of small parts in the super-huge virtual address space of the
processes is mapped to physical memory and accessed. Thus, tracking the
unmapped address regions is just wasteful. However, tracking every memory
mapping change might incur an overhead. For the reason, DAMON applies the
dynamic memory mapping changes to the tracking regions only for each of an
user-specified time interval (``regions update interval``).
Evaluations
===========
A prototype of DAMON has evaluated on an Intel Xeon E7-8837 machine using 20
benchmarks that picked from SPEC CPU 2006, NAS, Tensorflow Benchmark,
SPLASH-2X, and PARSEC 3 benchmark suite. Nonethless, this section provides
only summary of the results. For more detail, please refer to the slides used
for the introduction of DAMON at the Linux Plumbers Conference 2019[1] or the
MIDDLEWARE'19 industrial track paper[2].
Quality
-------
We first traced and visualized the data access pattern of each workload. We
were able to confirm that the visualized results are reasonably accurate by
manually comparing those with the source code of the workloads.
To see the usefulness of the monitoring, we optimized 9 memory intensive
workloads among them for memory pressure situations using the DAMON outputs.
In detail, we identified frequently accessed memory regions in each workload
based on the DAMON results and protected them with ``mlock()`` system calls.
The optimized versions consistently show speedup (2.55x in best case, 1.65x in
average) under memory pressure situation.
Overhead
--------
We also measured the overhead of DAMON. It was not only under the upperbound
we set, but was much lower (0.6 percent of the bound in best case, 13.288
percent of the bound in average). This reduction of the overhead is mainly
resulted from the adaptive regions adjustment. We also compared the overhead
with that of the straightforward periodic Accessed bit check-based monitoring,
which checks the access of every page frame. DAMON's overhead was much smaller
than the straightforward mechanism by 94,242.42x in best case, 3,159.61x in
average.
References
==========
Prototypes of DAMON have introduced by an LPC kernel summit track talk[1] and
two academic papers[2,3]. Please refer to those for more detailed information,
especially the evaluations.
[1] SeongJae Park, Tracing Data Access Pattern with Bounded Overhead and
Best-effort Accuracy. In The Linux Kernel Summit, September 2019.
https://linuxplumbersconf.org/event/4/contributions/548/
[2] SeongJae Park, Yunjae Lee, Heon Y. Yeom, Profiling Dynamic Data Access
Patterns with Controlled Overhead and Quality. In 20th ACM/IFIP
International Middleware Conference Industry, December 2019.
https://dl.acm.org/doi/10.1145/3366626.3368125
[3] SeongJae Park, Yunjae Lee, Yunhee Kim, Heon Y. Yeom, Profiling Dynamic Data
Access Patterns with Bounded Overhead and Accuracy. In IEEE International
Workshop on Foundations and Applications of Self- Systems (FAS 2019), June
2019.
SeongJae Park (5):
mm: Introduce Data Access MONitor (DAMON)
mm/damon: Add debugfs interface
mm/damon: Add minimal user-space tools
Documentation/admin-guide/mm: Add a document for DAMON
mm/damon: Add kunit tests
.../admin-guide/mm/data_access_monitor.rst | 235 +++
Documentation/admin-guide/mm/index.rst | 1 +
mm/Kconfig | 23 +
mm/Makefile | 1 +
mm/damon-test.h | 571 ++++++++
mm/damon.c | 1266 +++++++++++++++++
tools/damon/bin2txt.py | 64 +
tools/damon/damn | 36 +
tools/damon/heats.py | 358 +++++
tools/damon/nr_regions.py | 116 ++
tools/damon/record.py | 182 +++
tools/damon/report.py | 45 +
tools/damon/wss.py | 121 ++
13 files changed, 3019 insertions(+)
create mode 100644 Documentation/admin-guide/mm/data_access_monitor.rst
create mode 100644 mm/damon-test.h
create mode 100644 mm/damon.c
create mode 100644 tools/damon/bin2txt.py
create mode 100644 tools/damon/damn
create mode 100644 tools/damon/heats.py
create mode 100644 tools/damon/nr_regions.py
create mode 100644 tools/damon/record.py
create mode 100644 tools/damon/report.py
create mode 100644 tools/damon/wss.py
--
2.17.1
From: SeongJae Park <[email protected]>
This commit adds a shallow wrapper python script, ``/tools/damon/damn``
that provides more convenient interface for the user space. Note that
it is only aimed to be used for minimal reference of the DAMON's raw
interfaces and for debuggings of DAMON itself.
Quick Tutorial
--------------
To test DAMON on your system,
1. Ensure your kernel is built with CONFIG_DAMON turned on, and debugfs
is mounted at ``/sys/kernel/debug/``.
2. ``<your kernel source tree>/tools/damon/damn -h``
Signed-off-by: SeongJae Park <[email protected]>
---
tools/damon/bin2txt.py | 64 +++++++
tools/damon/damn | 36 ++++
tools/damon/heats.py | 358 ++++++++++++++++++++++++++++++++++++++
tools/damon/nr_regions.py | 116 ++++++++++++
tools/damon/record.py | 182 +++++++++++++++++++
tools/damon/report.py | 45 +++++
tools/damon/wss.py | 121 +++++++++++++
7 files changed, 922 insertions(+)
create mode 100644 tools/damon/bin2txt.py
create mode 100644 tools/damon/damn
create mode 100644 tools/damon/heats.py
create mode 100644 tools/damon/nr_regions.py
create mode 100644 tools/damon/record.py
create mode 100644 tools/damon/report.py
create mode 100644 tools/damon/wss.py
diff --git a/tools/damon/bin2txt.py b/tools/damon/bin2txt.py
new file mode 100644
index 000000000000..d5ffac60e02c
--- /dev/null
+++ b/tools/damon/bin2txt.py
@@ -0,0 +1,64 @@
+#!/usr/bin/env python3
+# SPDX-License-Identifier: GPL-2.0
+
+import argparse
+import os
+import struct
+import sys
+
+def parse_time(bindat):
+ "bindat should be 16 bytes"
+ sec = struct.unpack('l', bindat[0:8])[0]
+ nsec = struct.unpack('l', bindat[8:16])[0]
+ return sec * 1000000000 + nsec;
+
+def pr_region(f):
+ saddr = struct.unpack('L', f.read(8))[0]
+ eaddr = struct.unpack('L', f.read(8))[0]
+ nr_accesses = struct.unpack('I', f.read(4))[0]
+ print("%012x-%012x(%10d):\t%d" %
+ (saddr, eaddr, eaddr - saddr, nr_accesses))
+
+def pr_task_info(f):
+ pid = struct.unpack('L', f.read(8))[0]
+ print("pid: ", pid)
+ nr_regions = struct.unpack('I', f.read(4))[0]
+ print("nr_regions: ", nr_regions)
+ for r in range(nr_regions):
+ pr_region(f)
+
+def set_argparser(parser):
+ parser.add_argument('--input', '-i', type=str, metavar='<file>',
+ default='damon.data', help='input file name')
+
+def main(args=None):
+ if not args:
+ parser = argparse.ArgumentParser()
+ set_argparser(parser)
+ args = parser.parse_args()
+
+ file_path = args.input
+
+ if not os.path.isfile(file_path):
+ print('input file (%s) is not exist' % file_path)
+ exit(1)
+
+ with open(file_path, 'rb') as f:
+ start_time = None
+ while True:
+ timebin = f.read(16)
+ if len(timebin) != 16:
+ break
+ time = parse_time(timebin)
+ if not start_time:
+ start_time = time
+ print("start_time: ", start_time)
+ print("rel time: %16d" % (time - start_time))
+ nr_tasks = struct.unpack('I', f.read(4))[0]
+ print("nr_tasks: ", nr_tasks)
+ for t in range(nr_tasks):
+ pr_task_info(f)
+ print("")
+
+if __name__ == '__main__':
+ main()
diff --git a/tools/damon/damn b/tools/damon/damn
new file mode 100644
index 000000000000..0b8019db7f28
--- /dev/null
+++ b/tools/damon/damn
@@ -0,0 +1,36 @@
+#!/usr/bin/env python3
+# SPDX-License-Identifier: GPL-2.0
+
+import argparse
+
+import record
+import report
+
+class SubCmdHelpFormatter(argparse.RawDescriptionHelpFormatter):
+ def _format_action(self, action):
+ parts = super(argparse.RawDescriptionHelpFormatter,
+ self)._format_action(action)
+ # skip sub parsers help
+ if action.nargs == argparse.PARSER:
+ parts = '\n'.join(parts.split('\n')[1:])
+ return parts
+
+parser = argparse.ArgumentParser(formatter_class=SubCmdHelpFormatter)
+
+subparser = parser.add_subparsers(title='command', dest='command',
+ metavar='<command>')
+subparser.required = True
+
+parser_record = subparser.add_parser('record', help='record data accesses')
+record.set_argparser(parser_record)
+
+parser_report = subparser.add_parser('report',
+ help='report the recorded data accesses')
+report.set_argparser(parser_report)
+
+args = parser.parse_args()
+
+if args.command == 'record':
+ record.main(args)
+elif args.command == 'report':
+ report.main(args)
diff --git a/tools/damon/heats.py b/tools/damon/heats.py
new file mode 100644
index 000000000000..48e966c5ca02
--- /dev/null
+++ b/tools/damon/heats.py
@@ -0,0 +1,358 @@
+#!/usr/bin/env python3
+# SPDX-License-Identifier: GPL-2.0
+
+"""
+Transform binary trace data into human readable text that can be used for
+heatmap drawing, or directly plot the data in a heatmap format.
+
+Format of the text is:
+
+ <time> <space> <heat>
+ ...
+
+"""
+
+import argparse
+import os
+import struct
+import subprocess
+import sys
+import tempfile
+
+class HeatSample:
+ space_idx = None
+ sz_time_space = None
+ heat = None
+
+ def __init__(self, space_idx, sz_time_space, heat):
+ if sz_time_space < 0:
+ raise RuntimeError()
+ self.space_idx = space_idx
+ self.sz_time_space = sz_time_space
+ self.heat = heat
+
+ def total_heat(self):
+ return self.heat * self.sz_time_space
+
+ def merge(self, sample):
+ "sample must have a space idx that same to self"
+ heat_sum = self.total_heat() + sample.total_heat()
+ self.heat = heat_sum / (self.sz_time_space + sample.sz_time_space)
+ self.sz_time_space += sample.sz_time_space
+
+def pr_samples(samples, time_idx, time_unit, region_unit):
+ display_time = time_idx * time_unit
+ for idx, sample in enumerate(samples):
+ display_addr = idx * region_unit
+ if not sample:
+ print("%s\t%s\t%s" % (display_time, display_addr, 0.0))
+ continue
+ print("%s\t%s\t%s" % (display_time, display_addr, sample.total_heat() /
+ time_unit / region_unit))
+
+def to_idx(value, min_, unit):
+ return (value - min_) // unit
+
+def read_task_heats(f, pid, aunit, amin, amax):
+ pid_ = struct.unpack('L', f.read(8))[0]
+ nr_regions = struct.unpack('I', f.read(4))[0]
+ if pid_ != pid:
+ f.read(20 * nr_regions)
+ return None
+ samples = []
+ for i in range(nr_regions):
+ saddr = struct.unpack('L', f.read(8))[0]
+ eaddr = struct.unpack('L', f.read(8))[0]
+ eaddr = min(eaddr, amax - 1)
+ heat = struct.unpack('I', f.read(4))[0]
+
+ if eaddr <= amin:
+ continue
+ if saddr >= amax:
+ continue
+ saddr = max(amin, saddr)
+ eaddr = min(amax, eaddr)
+
+ sidx = to_idx(saddr, amin, aunit)
+ eidx = to_idx(eaddr - 1, amin, aunit)
+ for idx in range(sidx, eidx + 1):
+ sa = max(amin + idx * aunit, saddr)
+ ea = min(amin + (idx + 1) * aunit, eaddr)
+ sample = HeatSample(idx, (ea - sa), heat)
+ samples.append(sample)
+ return samples
+
+def parse_time(bindat):
+ sec = struct.unpack('l', bindat[0:8])[0]
+ nsec = struct.unpack('l', bindat[8:16])[0]
+ return sec * 1000000000 + nsec
+
+def apply_samples(target_samples, samples, start_time, end_time, aunit, amin):
+ for s in samples:
+ sample = HeatSample(s.space_idx,
+ s.sz_time_space * (end_time - start_time), s.heat)
+ idx = sample.space_idx
+ if not target_samples[idx]:
+ target_samples[idx] = sample
+ else:
+ target_samples[idx].merge(sample)
+
+def __pr_heats(f, pid, tunit, tmin, tmax, aunit, amin, amax):
+ heat_samples = [None] * ((amax - amin) // aunit)
+
+ start_time = 0
+ end_time = 0
+ last_flushed = -1
+ while True:
+ start_time = end_time
+ timebin = f.read(16)
+ if (len(timebin)) != 16:
+ break
+ end_time = parse_time(timebin)
+ nr_tasks = struct.unpack('I', f.read(4))[0]
+ samples_set = {}
+ for t in range(nr_tasks):
+ samples = read_task_heats(f, pid, aunit, amin, amax)
+ if samples:
+ samples_set[pid] = samples
+ if not pid in samples_set:
+ continue
+ if start_time >= tmax:
+ continue
+ if end_time <= tmin:
+ continue
+ start_time = max(start_time, tmin)
+ end_time = min(end_time, tmax)
+
+ sidx = to_idx(start_time, tmin, tunit)
+ eidx = to_idx(end_time - 1, tmin, tunit)
+ for idx in range(sidx, eidx + 1):
+ if idx != last_flushed:
+ pr_samples(heat_samples, idx, tunit, aunit)
+ heat_samples = [None] * ((amax - amin) // aunit)
+ last_flushed = idx
+ st = max(start_time, tmin + idx * tunit)
+ et = min(end_time, tmin + (idx + 1) * tunit)
+ apply_samples(heat_samples, samples_set[pid], st, et, aunit, amin)
+
+def pr_heats(args):
+ binfile = args.input
+ pid = args.pid
+ tres = args.tres
+ tmin = args.tmin
+ ares = args.ares
+ amin = args.amin
+
+ tunit = (args.tmax - tmin) // tres
+ aunit = (args.amax - amin) // ares
+
+ # Compensate the values so that those fit with the resolution
+ tmax = tmin + tunit * tres
+ amax = amin + aunit * ares
+
+ with open(binfile, 'rb') as f:
+ __pr_heats(f, pid, tunit, tmin, tmax, aunit, amin, amax)
+
+class GuideInfo:
+ pid = None
+ start_time = None
+ end_time = None
+ lowest_addr = None
+ highest_addr = None
+ gaps = None
+
+ def __init__(self, pid, start_time):
+ self.pid = pid
+ self.start_time = start_time
+ self.gaps = []
+
+ def regions(self):
+ regions = []
+ region = [self.lowest_addr]
+ for gap in self.gaps:
+ for idx, point in enumerate(gap):
+ if idx == 0:
+ region.append(point)
+ regions.append(region)
+ else:
+ region = [point]
+ region.append(self.highest_addr)
+ regions.append(region)
+ return regions
+
+ def total_space(self):
+ ret = 0
+ for r in self.regions():
+ ret += r[1] - r[0]
+ return ret
+
+ def __str__(self):
+ lines = ['pid:%d' % self.pid]
+ lines.append('time: %d-%d (%d)' % (self.start_time, self.end_time,
+ self.end_time - self.start_time))
+ for idx, region in enumerate(self.regions()):
+ lines.append('region\t%2d: %020d-%020d (%d)' %
+ (idx, region[0], region[1], region[1] - region[0]))
+ return '\n'.join(lines)
+
+def is_overlap(region1, region2):
+ if region1[1] < region2[0]:
+ return False
+ if region2[1] < region1[0]:
+ return False
+ return True
+
+def overlap_region_of(region1, region2):
+ return [max(region1[0], region2[0]), min(region1[1], region2[1])]
+
+def overlapping_regions(regions1, regions2):
+ overlap_regions = []
+ for r1 in regions1:
+ for r2 in regions2:
+ if is_overlap(r1, r2):
+ r1 = overlap_region_of(r1, r2)
+ if r1:
+ overlap_regions.append(r1)
+ return overlap_regions
+
+def get_guide_info(binfile):
+ "Read file, return the set of guide information objects of the data"
+ guides = {}
+ with open(binfile, 'rb') as f:
+ while True:
+ timebin = f.read(16)
+ if len(timebin) != 16:
+ break
+ monitor_time = parse_time(timebin)
+ nr_tasks = struct.unpack('I', f.read(4))[0]
+ for t in range(nr_tasks):
+ pid = struct.unpack('L', f.read(8))[0]
+ nr_regions = struct.unpack('I', f.read(4))[0]
+ if not pid in guides:
+ guides[pid] = GuideInfo(pid, monitor_time)
+ guide = guides[pid]
+ guide.end_time = monitor_time
+
+ last_addr = None
+ gaps = []
+ for r in range(nr_regions):
+ saddr = struct.unpack('L', f.read(8))[0]
+ eaddr = struct.unpack('L', f.read(8))[0]
+ f.read(4)
+
+ if not guide.lowest_addr or saddr < guide.lowest_addr:
+ guide.lowest_addr = saddr
+ if not guide.highest_addr or eaddr > guide.highest_addr:
+ guide.highest_addr = eaddr
+
+ if not last_addr:
+ last_addr = eaddr
+ continue
+ if last_addr != saddr:
+ gaps.append([last_addr, saddr])
+ last_addr = eaddr
+
+ if not guide.gaps:
+ guide.gaps = gaps
+ else:
+ guide.gaps = overlapping_regions(guide.gaps, gaps)
+ return sorted(list(guides.values()), key=lambda x: x.total_space(),
+ reverse=True)
+
+def pr_guide(binfile):
+ for guide in get_guide_info(binfile):
+ print(guide)
+
+def region_sort_key(region):
+ return region[1] - region[0]
+
+def set_missed_args(args):
+ if args.pid and args.tmin and args.tmax and args.amin and args.amax:
+ return
+ guides = get_guide_info(args.input)
+ guide = guides[0]
+ if not args.pid:
+ args.pid = guide.pid
+ for g in guides:
+ if g.pid == args.pid:
+ guide = g
+ break
+
+ if not args.tmin:
+ args.tmin = guide.start_time
+ if not args.tmax:
+ args.tmax = guide.end_time
+
+ if not args.amin or not args.amax:
+ region = sorted(guide.regions(), key=lambda x: x[1] - x[0],
+ reverse=True)[0]
+ args.amin = region[0]
+ args.amax = region[1]
+
+def plot_heatmap(data_file, output_file):
+ terminal = output_file.split('.')[-1]
+ if not terminal in ['pdf', 'jpeg', 'png', 'svg']:
+ os.remove(data_file)
+ print("Unsupported plot output type.")
+ exit(-1)
+
+ gnuplot_cmd = """
+ set term %s;
+ set output '%s';
+ set key off;
+ set xrange [0:];
+ set yrange [0:];
+ set xlabel 'Time (ns)';
+ set ylabel 'Virtual Address (bytes)';
+ plot '%s' using 1:2:3 with image;""" % (terminal, output_file, data_file)
+ subprocess.call(['gnuplot', '-e', gnuplot_cmd])
+ os.remove(data_file)
+
+def set_argparser(parser):
+ parser.add_argument('--input', '-i', type=str, metavar='<file>',
+ default='damon.data', help='input file name')
+ parser.add_argument('--pid', metavar='<pid>', type=int,
+ help='pid of target task')
+ parser.add_argument('--tres', metavar='<resolution>', type=int,
+ default=500, help='time resolution of the output')
+ parser.add_argument('--tmin', metavar='<time>', type=lambda x: int(x,0),
+ help='minimal time of the output')
+ parser.add_argument('--tmax', metavar='<time>', type=lambda x: int(x,0),
+ help='maximum time of the output')
+ parser.add_argument('--ares', metavar='<resolution>', type=int, default=500,
+ help='space address resolution of the output')
+ parser.add_argument('--amin', metavar='<address>', type=lambda x: int(x,0),
+ help='minimal space address of the output')
+ parser.add_argument('--amax', metavar='<address>', type=lambda x: int(x,0),
+ help='maximum space address of the output')
+ parser.add_argument('--guide', action='store_true',
+ help='print a guidance for the min/max/resolution settings')
+ parser.add_argument('--heatmap', metavar='<file>', type=str,
+ help='heatmap image file to create')
+
+def main(args=None):
+ if not args:
+ parser = argparse.ArgumentParser()
+ set_argparser(parser)
+ args = parser.parse_args()
+
+ if args.guide:
+ pr_guide(args.input)
+ else:
+ set_missed_args(args)
+ orig_stdout = sys.stdout
+ if args.heatmap:
+ tmp_path = tempfile.mkstemp()[1]
+ tmp_file = open(tmp_path, 'w')
+ sys.stdout = tmp_file
+
+ pr_heats(args)
+
+ if args.heatmap:
+ sys.stdout = orig_stdout
+ tmp_file.flush()
+ tmp_file.close()
+ plot_heatmap(tmp_path, args.heatmap)
+
+if __name__ == '__main__':
+ main()
diff --git a/tools/damon/nr_regions.py b/tools/damon/nr_regions.py
new file mode 100644
index 000000000000..7ed4cdda4eb7
--- /dev/null
+++ b/tools/damon/nr_regions.py
@@ -0,0 +1,116 @@
+#!/usr/bin/env python3
+# SPDX-License-Identifier: GPL-2.0
+
+"Print out distribution of the number of regions in the given record"
+
+import argparse
+import os
+import struct
+import subprocess
+import sys
+import tempfile
+
+def patterns(f):
+ wss = 0
+ nr_regions = struct.unpack('I', f.read(4))[0]
+
+ patterns = []
+ for r in range(nr_regions):
+ saddr = struct.unpack('L', f.read(8))[0]
+ eaddr = struct.unpack('L', f.read(8))[0]
+ nr_accesses = struct.unpack('I', f.read(4))[0]
+ patterns.append([eaddr - saddr, nr_accesses])
+ return patterns
+
+def plot_dist(data_file, output_file, xlabel):
+ terminal = output_file.split('.')[-1]
+ if not terminal in ['pdf', 'jpeg', 'png', 'svg']:
+ os.remove(data_file)
+ print("Unsupported plot output type.")
+ exit(-1)
+
+ gnuplot_cmd = """
+ set term %s;
+ set output '%s';
+ set key off;
+ set ylabel 'number of sampling regions';
+ set xlabel '%s';
+ plot '%s' with linespoints;""" % (terminal, output_file, xlabel, data_file)
+ subprocess.call(['gnuplot', '-e', gnuplot_cmd])
+ os.remove(data_file)
+
+def set_argparser(parser):
+ parser.add_argument('--input', '-i', type=str, metavar='<file>',
+ default='damon.data', help='input file name')
+ parser.add_argument('--range', '-r', type=int, nargs=3,
+ metavar=('<start>', '<stop>', '<step>'),
+ help='range of wss percentiles to print')
+ parser.add_argument('--sortby', '-s', choices=['time', 'size'],
+ help='the metric to be used for sorting the number of regions')
+ parser.add_argument('--plot', '-p', type=str, metavar='<file>',
+ help='plot the distribution to an image file')
+
+def main(args=None):
+ if not args:
+ parser = argparse.ArgumentParser()
+ set_argparser(parser)
+ args = parser.parse_args()
+
+ percentiles = [0, 25, 50, 75, 100]
+
+ file_path = args.input
+ if args.range:
+ percentiles = range(args.range[0], args.range[1], args.range[2])
+ wss_sort = True
+ if args.sortby == 'time':
+ wss_sort = False
+
+ pid_pattern_map = {}
+ with open(file_path, 'rb') as f:
+ start_time = None
+ while True:
+ timebin = f.read(16)
+ if len(timebin) != 16:
+ break
+ nr_tasks = struct.unpack('I', f.read(4))[0]
+ for t in range(nr_tasks):
+ pid = struct.unpack('L', f.read(8))[0]
+ if not pid_pattern_map:
+ pid_pattern_map[pid] = []
+ pid_pattern_map[pid].append(patterns(f))
+
+ orig_stdout = sys.stdout
+ if args.plot:
+ tmp_path = tempfile.mkstemp()[1]
+ tmp_file = open(tmp_path, 'w')
+ sys.stdout = tmp_file
+
+ print('# <percentile> <# regions>')
+ for pid in pid_pattern_map.keys():
+ snapshots = pid_pattern_map[pid][20:]
+ nr_regions_dist = []
+ for snapshot in snapshots:
+ nr_regions_dist.append(len(snapshot))
+ if wss_sort:
+ nr_regions_dist.sort(reverse=False)
+
+ print('# pid\t%s' % pid)
+ print('# avr:\t%d' % (sum(nr_regions_dist) / len(nr_regions_dist)))
+ for percentile in percentiles:
+ thres_idx = int(percentile / 100.0 * len(nr_regions_dist))
+ if thres_idx == len(nr_regions_dist):
+ thres_idx -= 1
+ threshold = nr_regions_dist[thres_idx]
+ print('%d\t%d' % (percentile, nr_regions_dist[thres_idx]))
+
+ if args.plot:
+ sys.stdout = orig_stdout
+ tmp_file.flush()
+ tmp_file.close()
+ xlabel = 'runtime (percent)'
+ if wss_sort:
+ xlabel = 'percentile'
+ plot_dist(tmp_path, args.plot, xlabel)
+
+if __name__ == '__main__':
+ main()
diff --git a/tools/damon/record.py b/tools/damon/record.py
new file mode 100644
index 000000000000..93a85722f601
--- /dev/null
+++ b/tools/damon/record.py
@@ -0,0 +1,182 @@
+#!/usr/bin/env python3
+# SPDX-License-Identifier: GPL-2.0
+
+"""
+Record data access patterns of the given processes.
+"""
+
+import argparse
+import copy
+import os
+import signal
+import subprocess
+import time
+
+DBGFS="/sys/kernel/debug/damon/"
+DBGFS_ATTRS = DBGFS + "attrs"
+DBGFS_PIDS = DBGFS + "pids"
+DBGFS_TRACING_ON = DBGFS + "monitor_on"
+
+orig_attrs = None
+
+def set_target_pid(pid):
+ return subprocess.call('echo %s > %s' % (pid, DBGFS_PIDS), shell=True,
+ executable='/bin/bash')
+
+def turn_damon(on_off):
+ return subprocess.call("echo %s > %s" % (on_off, DBGFS_TRACING_ON),
+ shell=True, executable="/bin/bash")
+
+def is_damon_running():
+ with open(DBGFS_TRACING_ON, 'r') as f:
+ return f.read().strip() == 'on'
+
+def do_trace(target, is_target_pid, attrs, old_attrs):
+ if os.path.isfile(attrs.rfile_path):
+ os.rename(attrs.rfile_path, attrs.rfile_path + '.old')
+
+ if attrs.apply():
+ print('attributes (%s) failed to be applied' % attrs)
+ cleanup_exit(old_attrs, -1)
+ print('# damon attrs: %s' % attrs)
+ if not is_target_pid:
+ p = subprocess.Popen(target, shell=True, executable='/bin/bash')
+ target = p.pid
+ if set_target_pid(target):
+ print('pid setting (%s) failed' % target)
+ cleanup_exit(old_attrs, -2)
+ if turn_damon('on'):
+ print('could not turn on damon' % target)
+ cleanup_exit(old_attrs, -3)
+ if not is_target_pid:
+ p.wait()
+ while True:
+ # damon will turn it off by itself if the target tasks are terminated.
+ if not is_damon_running():
+ break
+ time.sleep(1)
+
+ cleanup_exit(old_attrs, 0)
+
+class Attrs:
+ sample_interval = None
+ aggr_interval = None
+ regions_update_interval = None
+ min_nr_regions = None
+ max_nr_regions = None
+ rfile_path = None
+
+ def __init__(self, s, a, r, n, x, f):
+ self.sample_interval = s
+ self.aggr_interval = a
+ self.regions_update_interval = r
+ self.min_nr_regions = n
+ self.max_nr_regions = x
+ self.rfile_path = f
+
+ def __str__(self):
+ return "%s %s %s %s %s %s" % (self.sample_interval, self.aggr_interval,
+ self.regions_update_interval, self.min_nr_regions,
+ self.max_nr_regions, self.rfile_path)
+
+ def apply(self):
+ return subprocess.call('echo %s > %s' % (self, DBGFS_ATTRS),
+ shell=True, executable='/bin/bash')
+
+def current_attrs():
+ with open(DBGFS_ATTRS, 'r') as f:
+ attrs = f.read().split()
+ atnrs = [int(x) for x in attrs[0:5]]
+ attrs = atnrs + [attrs[5]]
+ return Attrs(*attrs)
+
+def cmd_args_to_attrs(args):
+ "Generate attributes based on current attributes and command arguments"
+ a = current_attrs()
+ if args.sample:
+ a.sample_interval = args.sample
+ if args.aggr:
+ a.aggr_interval = args.aggr
+ if args.updr:
+ a.regions_update_interval = args.updr
+ if args.minr:
+ a.min_nr_regions = args.minr
+ if args.maxr:
+ a.max_nr_regions = args.maxr
+ if args.out:
+ if not os.path.isabs(args.out):
+ args.out = os.path.join(os.getcwd(), args.out)
+ a.rfile_path = args.out
+ return a
+
+def cleanup_exit(orig_attrs, exit_code):
+ if is_damon_running():
+ if turn_damon('off'):
+ print('failed to turn damon off!')
+ if orig_attrs:
+ if orig_attrs.apply():
+ print('original attributes (%s) restoration failed!' % orig_attrs)
+ exit(exit_code)
+
+def sighandler(signum, frame):
+ print('\nsignal %s received' % signum)
+ cleanup_exit(orig_attrs, signum)
+
+def chk_prerequisites():
+ if os.geteuid() != 0:
+ print("Run as root")
+ exit(1)
+
+ if not os.path.isdir(DBGFS):
+ print("damon debugfs not exists.")
+ exit(1)
+
+ if not os.path.isfile(DBGFS_PIDS):
+ print("damon pids file (%s) not exists." % DBGFS_PIDS)
+ exit(1)
+
+def set_argparser(parser):
+ parser.add_argument('target', type=str, metavar='<target>',
+ help='the target command or the pid to record')
+ parser.add_argument('-s', '--sample', metavar='<interval>', type=int,
+ help='sampling interval')
+ parser.add_argument('-a', '--aggr', metavar='<interval>', type=int,
+ help='aggregate interval')
+ parser.add_argument('-u', '--updr', metavar='<interval>', type=int,
+ help='regions update interval')
+ parser.add_argument('-n', '--minr', metavar='<# regions>', type=int,
+ help='minimal number of regions')
+ parser.add_argument('-m', '--maxr', metavar='<# regions>', type=int,
+ help='maximum number of regions')
+ parser.add_argument('-o', '--out', metavar='<file path>', type=str,
+ default='damon.data', help='output file path')
+
+def main(args=None):
+ if not args:
+ parser = argparse.ArgumentParser()
+ set_argparser(parser)
+ args = parser.parse_args()
+
+ chk_prerequisites()
+
+ signal.signal(signal.SIGINT, sighandler)
+ signal.signal(signal.SIGTERM, sighandler)
+ orig_attrs = current_attrs()
+
+ new_attrs = cmd_args_to_attrs(args)
+ target = args.target
+
+ target_fields = target.split()
+ if not subprocess.call('which %s > /dev/null' % target_fields[0],
+ shell=True, executable='/bin/bash'):
+ do_trace(target, False, new_attrs, orig_attrs)
+ else:
+ try:
+ pid = int(target)
+ except:
+ print('target \'%s\' is neither a command, nor a pid' % target)
+ exit(1)
+ do_trace(target, True, new_attrs, orig_attrs)
+
+if __name__ == '__main__':
+ main()
diff --git a/tools/damon/report.py b/tools/damon/report.py
new file mode 100644
index 000000000000..c661c7b2f1af
--- /dev/null
+++ b/tools/damon/report.py
@@ -0,0 +1,45 @@
+#!/usr/bin/env python3
+# SPDX-License-Identifier: GPL-2.0
+
+import argparse
+
+import bin2txt
+import heats
+import nr_regions
+import wss
+
+def set_argparser(parser):
+ subparsers = parser.add_subparsers(title='report type', dest='report_type',
+ metavar='<report type>', help='the type of the report to generate')
+ subparsers.required = True
+
+ parser_raw = subparsers.add_parser('raw', help='human readable raw data')
+ bin2txt.set_argparser(parser_raw)
+
+ parser_heats = subparsers.add_parser('heats', help='heats of regions')
+ heats.set_argparser(parser_heats)
+
+ parser_wss = subparsers.add_parser('wss', help='working set size')
+ wss.set_argparser(parser_wss)
+
+ parser_nr_regions = subparsers.add_parser('nr_regions',
+ help='number of regions')
+ nr_regions.set_argparser(parser_nr_regions)
+
+def main(args=None):
+ if not args:
+ parser = argparse.ArgumentParser()
+ set_argparser(parser)
+ args = parser.parse_args()
+
+ if args.report_type == 'raw':
+ bin2txt.main(args)
+ elif args.report_type == 'heats':
+ heats.main(args)
+ elif args.report_type == 'wss':
+ wss.main(args)
+ elif args.report_type == 'nr_regions':
+ nr_regions.main(args)
+
+if __name__ == '__main__':
+ main()
diff --git a/tools/damon/wss.py b/tools/damon/wss.py
new file mode 100644
index 000000000000..a6a80ecfca05
--- /dev/null
+++ b/tools/damon/wss.py
@@ -0,0 +1,121 @@
+#!/usr/bin/env python3
+# SPDX-License-Identifier: GPL-2.0
+
+"Print out the distribution of the working set sizes of the given trace"
+
+import argparse
+import os
+import struct
+import subprocess
+import sys
+import tempfile
+
+def patterns(f):
+ wss = 0
+ nr_regions = struct.unpack('I', f.read(4))[0]
+
+ patterns = []
+ for r in range(nr_regions):
+ saddr = struct.unpack('L', f.read(8))[0]
+ eaddr = struct.unpack('L', f.read(8))[0]
+ nr_accesses = struct.unpack('I', f.read(4))[0]
+ patterns.append([eaddr - saddr, nr_accesses])
+ return patterns
+
+def plot_dist(data_file, output_file, xlabel):
+ terminal = output_file.split('.')[-1]
+ if not terminal in ['pdf', 'jpeg', 'png', 'svg']:
+ os.remove(data_file)
+ print("Unsupported plot output type.")
+ exit(-1)
+
+ gnuplot_cmd = """
+ set term %s;
+ set output '%s';
+ set key off;
+ set ylabel 'working set size (bytes)';
+ set xlabel '%s';
+ plot '%s' with linespoints;""" % (terminal, output_file, xlabel, data_file)
+ subprocess.call(['gnuplot', '-e', gnuplot_cmd])
+ os.remove(data_file)
+
+def set_argparser(parser):
+ parser.add_argument('--input', '-i', type=str, metavar='<file>',
+ default='damon.data', help='input file name')
+ parser.add_argument('--range', '-r', type=int, nargs=3,
+ metavar=('<start>', '<stop>', '<step>'),
+ help='range of wss percentiles to print')
+ parser.add_argument('--sortby', '-s', choices=['time', 'size'],
+ help='the metric to be used for the sort of the working set sizes')
+ parser.add_argument('--plot', '-p', type=str, metavar='<file>',
+ help='plot the distribution to an image file')
+
+def main(args=None):
+ if not args:
+ parser = argparse.ArgumentParser()
+ set_argparser(parser)
+ args = parser.parse_args()
+
+ percentiles = [0, 25, 50, 75, 100]
+
+ file_path = args.input
+ if args.range:
+ percentiles = range(args.range[0], args.range[1], args.range[2])
+ wss_sort = True
+ if args.sortby == 'time':
+ wss_sort = False
+
+ pid_pattern_map = {}
+ with open(file_path, 'rb') as f:
+ start_time = None
+ while True:
+ timebin = f.read(16)
+ if len(timebin) != 16:
+ break
+ nr_tasks = struct.unpack('I', f.read(4))[0]
+ for t in range(nr_tasks):
+ pid = struct.unpack('L', f.read(8))[0]
+ if not pid_pattern_map:
+ pid_pattern_map[pid] = []
+ pid_pattern_map[pid].append(patterns(f))
+
+ orig_stdout = sys.stdout
+ if args.plot:
+ tmp_path = tempfile.mkstemp()[1]
+ tmp_file = open(tmp_path, 'w')
+ sys.stdout = tmp_file
+
+ print('# <percentile> <wss>')
+ for pid in pid_pattern_map.keys():
+ snapshots = pid_pattern_map[pid][20:]
+ wss_dist = []
+ for snapshot in snapshots:
+ wss = 0
+ for p in snapshot:
+ if p[1] <= 0:
+ continue
+ wss += p[0]
+ wss_dist.append(wss)
+ if wss_sort:
+ wss_dist.sort(reverse=False)
+
+ print('# pid\t%s' % pid)
+ print('# avr:\t%d' % (sum(wss_dist) / len(wss_dist)))
+ for percentile in percentiles:
+ thres_idx = int(percentile / 100.0 * len(wss_dist))
+ if thres_idx == len(wss_dist):
+ thres_idx -= 1
+ threshold = wss_dist[thres_idx]
+ print('%d\t%d' % (percentile, wss_dist[thres_idx]))
+
+ if args.plot:
+ sys.stdout = orig_stdout
+ tmp_file.flush()
+ tmp_file.close()
+ xlabel = 'runtime (percent)'
+ if wss_sort:
+ xlabel = 'percentile'
+ plot_dist(tmp_path, args.plot, xlabel)
+
+if __name__ == '__main__':
+ main()
--
2.17.1
From: SeongJae Park <[email protected]>
This commit adds kunit based unit tests for DAMON.
Signed-off-by: SeongJae Park <[email protected]>
---
mm/Kconfig | 11 +
mm/damon-test.h | 571 ++++++++++++++++++++++++++++++++++++++++++++++++
mm/damon.c | 2 +
3 files changed, 584 insertions(+)
create mode 100644 mm/damon-test.h
diff --git a/mm/Kconfig b/mm/Kconfig
index b7af8a1b5cb5..7b023799aa38 100644
--- a/mm/Kconfig
+++ b/mm/Kconfig
@@ -748,4 +748,15 @@ config DAMON
be 1) accurate enough to be useful for performance-centric domains,
and 2) sufficiently light-weight so that it can be applied online.
+config DAMON_TEST
+ bool "Test for damon"
+ depends on DAMON && KUNIT
+ help
+ This builds the DAMON Kunit test suite.
+
+ For more information on KUnit and unit tests in general, please refer
+ to the KUnit documentation.
+
+ If unsure, say N.
+
endmenu
diff --git a/mm/damon-test.h b/mm/damon-test.h
new file mode 100644
index 000000000000..0d94910b8fe5
--- /dev/null
+++ b/mm/damon-test.h
@@ -0,0 +1,571 @@
+/* SPDX-License-Identifier: GPL-2.0 */
+/*
+ * Data Access Monitor Unit Tests
+ *
+ * Copyright 2019 Amazon.com, Inc. or its affiliates. All rights reserved.
+ *
+ * Author: SeongJae Park <[email protected]>
+ */
+
+#ifdef CONFIG_DAMON_TEST
+
+#ifndef _DAMON_TEST_H
+#define _DAMON_TEST_H
+
+#include <kunit/test.h>
+
+static void damon_test_str_to_pids(struct kunit *test)
+{
+ char *question;
+ unsigned long *answers;
+ unsigned long expected[] = {12, 35, 46};
+ ssize_t nr_integers = 0, i;
+
+ question = "123";
+ answers = str_to_pids(question, strnlen(question, 128), &nr_integers);
+ KUNIT_EXPECT_EQ(test, 1l, nr_integers);
+ KUNIT_EXPECT_EQ(test, 123ul, answers[0]);
+ kfree(answers);
+
+ question = "123abc";
+ answers = str_to_pids(question, strnlen(question, 128), &nr_integers);
+ KUNIT_EXPECT_EQ(test, 1l, nr_integers);
+ KUNIT_EXPECT_EQ(test, 123ul, answers[0]);
+ kfree(answers);
+
+ question = "a123";
+ answers = str_to_pids(question, strnlen(question, 128), &nr_integers);
+ KUNIT_EXPECT_EQ(test, 0l, nr_integers);
+ KUNIT_EXPECT_PTR_EQ(test, answers, (unsigned long *)NULL);
+
+ question = "12 35";
+ answers = str_to_pids(question, strnlen(question, 128), &nr_integers);
+ KUNIT_EXPECT_EQ(test, 2l, nr_integers);
+ for (i = 0; i < nr_integers; i++)
+ KUNIT_EXPECT_EQ(test, expected[i], answers[i]);
+ kfree(answers);
+
+ question = "12 35 46";
+ answers = str_to_pids(question, strnlen(question, 128), &nr_integers);
+ KUNIT_EXPECT_EQ(test, 3l, nr_integers);
+ for (i = 0; i < nr_integers; i++)
+ KUNIT_EXPECT_EQ(test, expected[i], answers[i]);
+ kfree(answers);
+
+ question = "12 35 abc 46";
+ answers = str_to_pids(question, strnlen(question, 128), &nr_integers);
+ KUNIT_EXPECT_EQ(test, 2l, nr_integers);
+ for (i = 0; i < 2; i++)
+ KUNIT_EXPECT_EQ(test, expected[i], answers[i]);
+ kfree(answers);
+
+ question = "";
+ answers = str_to_pids(question, strnlen(question, 128), &nr_integers);
+ KUNIT_EXPECT_EQ(test, 0l, nr_integers);
+ KUNIT_EXPECT_PTR_EQ(test, (unsigned long *)NULL, answers);
+ kfree(answers);
+
+ question = "\n";
+ answers = str_to_pids(question, strnlen(question, 128), &nr_integers);
+ KUNIT_EXPECT_EQ(test, 0l, nr_integers);
+ KUNIT_EXPECT_PTR_EQ(test, (unsigned long *)NULL, answers);
+ kfree(answers);
+}
+
+static void damon_test_regions(struct kunit *test)
+{
+ struct damon_region *r;
+ struct damon_task *t;
+
+ r = damon_new_region(1, 2);
+ KUNIT_EXPECT_EQ(test, 1ul, r->vm_start);
+ KUNIT_EXPECT_EQ(test, 2ul, r->vm_end);
+ KUNIT_EXPECT_EQ(test, 0u, r->nr_accesses);
+ KUNIT_EXPECT_TRUE(test, r->sampling_addr >= r->vm_start);
+ KUNIT_EXPECT_TRUE(test, r->sampling_addr < r->vm_end);
+
+ t = damon_new_task(42);
+ KUNIT_EXPECT_EQ(test, 0u, nr_damon_regions(t));
+
+ damon_add_region_tail(r, t);
+ KUNIT_EXPECT_EQ(test, 1u, nr_damon_regions(t));
+
+ damon_del_region(r);
+ KUNIT_EXPECT_EQ(test, 0u, nr_damon_regions(t));
+
+ damon_free_task(t);
+}
+
+static void damon_test_tasks(struct kunit *test)
+{
+ struct damon_task *t;
+
+ t = damon_new_task(42);
+ KUNIT_EXPECT_EQ(test, 42ul, t->pid);
+ KUNIT_EXPECT_EQ(test, 0u, nr_damon_tasks());
+
+ damon_add_task_tail(t);
+ KUNIT_EXPECT_EQ(test, 1u, nr_damon_tasks());
+
+ damon_destroy_task(t);
+ KUNIT_EXPECT_EQ(test, 0u, nr_damon_tasks());
+}
+
+static void damon_test_set_pids(struct kunit *test)
+{
+ unsigned long pids[] = {1, 2, 3};
+ char buf[64];
+
+ damon_set_pids(pids, 3);
+ damon_sprint_pids(buf, 64);
+ pr_info("buf: %s (%zu)\n", buf, strlen(buf));
+ KUNIT_EXPECT_EQ(test, 0, strncmp(buf, "1 2 3\n", 64));
+
+ damon_set_pids(NULL, 0);
+ damon_sprint_pids(buf, 64);
+ KUNIT_EXPECT_EQ(test, 0, strncmp(buf, "\n", 64));
+
+ damon_set_pids((unsigned long []){1, 2}, 2);
+ damon_sprint_pids(buf, 64);
+ KUNIT_EXPECT_EQ(test, 0, strncmp(buf, "1 2\n", 64));
+
+ damon_set_pids((unsigned long []){2}, 1);
+ damon_sprint_pids(buf, 64);
+ KUNIT_EXPECT_EQ(test, 0, strncmp(buf, "2\n", 64));
+
+ damon_set_pids(NULL, 0);
+ damon_sprint_pids(buf, 64);
+ KUNIT_EXPECT_EQ(test, 0, strncmp(buf, "\n", 64));
+}
+
+static void damon_test_three_regions_in_vmas(struct kunit *test)
+{
+ struct region regions[3] = {0,};
+
+ struct vm_area_struct vmas[] = {
+ (struct vm_area_struct) {.vm_start = 10, .vm_end = 20},
+ (struct vm_area_struct) {.vm_start = 20, .vm_end = 25},
+ (struct vm_area_struct) {.vm_start = 200, .vm_end = 210},
+ (struct vm_area_struct) {.vm_start = 210, .vm_end = 220},
+ (struct vm_area_struct) {.vm_start = 300, .vm_end = 305},
+ (struct vm_area_struct) {.vm_start = 307, .vm_end = 330},
+ };
+ vmas[0].vm_next = &vmas[1];
+ vmas[1].vm_next = &vmas[2];
+ vmas[2].vm_next = &vmas[3];
+ vmas[3].vm_next = &vmas[4];
+ vmas[4].vm_next = &vmas[5];
+ vmas[5].vm_next = NULL;
+
+ damon_three_regions_in_vmas(&vmas[0], regions);
+
+ KUNIT_EXPECT_EQ(test, 10ul, regions[0].start);
+ KUNIT_EXPECT_EQ(test, 25ul, regions[0].end);
+ KUNIT_EXPECT_EQ(test, 200ul, regions[1].start);
+ KUNIT_EXPECT_EQ(test, 220ul, regions[1].end);
+ KUNIT_EXPECT_EQ(test, 300ul, regions[2].start);
+ KUNIT_EXPECT_EQ(test, 330ul, regions[2].end);
+}
+
+/* Clean up global state of damon */
+static void damon_cleanup_global_state(void)
+{
+ struct damon_task *t, *next;
+
+ damon_for_each_task_safe(t, next)
+ damon_destroy_task(t);
+
+ damon_rbuf_offset = 0;
+}
+
+static void damon_test_aggregate(struct kunit *test)
+{
+ unsigned long pids[] = {1, 2, 3};
+ unsigned long saddr[][3] = {{10, 20, 30}, {5, 42, 49}, {13, 33, 55} };
+ unsigned long eaddr[][3] = {{15, 27, 40}, {31, 45, 55}, {23, 44, 66} };
+ unsigned long accesses[][3] = {{42, 95, 84}, {10, 20, 30}, {0, 1, 2} };
+ struct damon_task *t;
+ struct damon_region *r;
+ int it, ir;
+ ssize_t sz, sr, sp;
+
+ damon_set_pids(pids, 3);
+
+ it = 0;
+ damon_for_each_task(t) {
+ for (ir = 0; ir < 3; ir++) {
+ r = damon_new_region(saddr[it][ir], eaddr[it][ir]);
+ r->nr_accesses = accesses[it][ir];
+ damon_add_region_tail(r, t);
+ }
+ it++;
+ }
+ kdamond_flush_aggregated();
+ it = 0;
+ damon_for_each_task(t) {
+ ir = 0;
+ damon_for_each_region(r, t) {
+ KUNIT_EXPECT_EQ(test, 0u, r->nr_accesses);
+ ir++;
+ }
+ KUNIT_EXPECT_EQ(test, 3, ir);
+ it++;
+ }
+ KUNIT_EXPECT_EQ(test, 3, it);
+
+ sr = sizeof(r->vm_start) + sizeof(r->vm_end) + sizeof(r->nr_accesses);
+ sp = sizeof(t->pid) + sizeof(unsigned int) + 3 * sr;
+ sz = sizeof(struct timespec64) + sizeof(unsigned int) + 3 * sp;
+ KUNIT_EXPECT_EQ(test, (unsigned int)sz, damon_rbuf_offset);
+
+ damon_cleanup_global_state();
+}
+
+static void damon_test_write_rbuf(struct kunit *test)
+{
+ char *data;
+
+ data = "hello";
+ damon_write_rbuf(data, strnlen(data, 256));
+ KUNIT_EXPECT_EQ(test, damon_rbuf_offset, 5u);
+
+ damon_write_rbuf(data, 0);
+ KUNIT_EXPECT_EQ(test, damon_rbuf_offset, 5u);
+
+ KUNIT_EXPECT_EQ(test, strncmp(damon_rbuf, data, 5), 0);
+}
+
+static void damon_test_update_two_gaps(struct kunit *test)
+{
+ struct damon_task *t;
+ struct damon_region *r, *prev = NULL;
+ unsigned long regions[] = {10, 20, 20, 30,
+ 50, 55, 55, 57, 57, 59,
+ 70, 80, 80, 90, 90, 100}; /* 10-30, 50-59, 70-100 */
+ struct region new_regions[3] = {
+ (struct region){.start = 5, .end = 27},
+ (struct region){.start = 45, .end = 55},
+ (struct region){.start = 73, .end = 104} };
+ int i;
+ bool first_gap = true;
+
+ t = damon_new_task(42);
+ for (i = 0; i < ARRAY_SIZE(regions) / 2; i++) {
+ r = damon_new_region(regions[i * 2], regions[i * 2 + 1]);
+ damon_add_region_tail(r, t);
+ }
+ damon_add_task_tail(t);
+
+ damon_apply_three_regions(t, new_regions);
+
+ damon_for_each_region(r, t) {
+ if (prev == NULL) {
+ KUNIT_EXPECT_EQ(test, r->vm_start, 5ul);
+ goto next;
+ }
+
+ if (prev->vm_end != r->vm_start && first_gap) {
+ KUNIT_EXPECT_EQ(test, prev->vm_end, 27ul);
+ KUNIT_EXPECT_EQ(test, r->vm_start, 45ul);
+ first_gap = false;
+ goto next;
+ }
+
+ if (prev->vm_end != r->vm_start && !first_gap) {
+ KUNIT_EXPECT_EQ(test, prev->vm_end, 55ul);
+ KUNIT_EXPECT_EQ(test, r->vm_start, 73ul);
+ goto next;
+ }
+
+next:
+ prev = r;
+ }
+
+ damon_cleanup_global_state();
+}
+
+static void damon_test_update_two_gaps2(struct kunit *test)
+{
+ struct damon_task *t;
+ struct damon_region *r;
+ /* 10-20-30, 50-55-57-59, 70-80-90-100 */
+ unsigned long regions[] = {10, 20, 20, 30,
+ 50, 55, 55, 57, 57, 59,
+ 70, 80, 80, 90, 90, 100};
+ struct region new_regions[3] = {
+ (struct region){.start = 5, .end = 27},
+ (struct region){.start = 56, .end = 57},
+ (struct region){.start = 65, .end = 104} };
+ /* expect 5-27, 56-57, 65-80-90-104 */
+ unsigned long answers[] = {5, 20, 20, 27,
+ 56, 57,
+ 65, 80, 80, 90, 90, 104};
+ int i;
+
+ t = damon_new_task(42);
+ for (i = 0; i < ARRAY_SIZE(regions) / 2; i++) {
+ r = damon_new_region(regions[i * 2], regions[i * 2 + 1]);
+ damon_add_region_tail(r, t);
+ }
+ damon_add_task_tail(t);
+
+ damon_apply_three_regions(t, new_regions);
+
+ for (i = 0; i < ARRAY_SIZE(answers) / 2; i++) {
+ r = damon_nth_region_of(t, i);
+ KUNIT_EXPECT_EQ(test, r->vm_start, answers[i * 2]);
+ KUNIT_EXPECT_EQ(test, r->vm_end, answers[i++ * 2 + 1]);
+ }
+
+ damon_cleanup_global_state();
+}
+
+static void damon_test_update_two_gaps3(struct kunit *test)
+{
+ struct damon_task *t;
+ struct damon_region *r;
+ /* 10-20-30, 50-55-57-59, 70-80-90-100 */
+ unsigned long regions[] = {10, 20, 20, 30,
+ 50, 55, 55, 57, 57, 59,
+ 70, 80, 80, 90, 90, 100};
+ struct region new_regions[3] = {
+ (struct region){.start = 5, .end = 27},
+ (struct region){.start = 61, .end = 63},
+ (struct region){.start = 65, .end = 104} };
+ /* expect 5-27, 56-57, 65-80-90-104 */
+ unsigned long answers[] = {5, 20, 20, 27,
+ 61, 63,
+ 65, 80, 80, 90, 90, 104};
+ int i;
+
+ t = damon_new_task(42);
+ for (i = 0; i < ARRAY_SIZE(regions) / 2; i++) {
+ r = damon_new_region(regions[i * 2], regions[i * 2 + 1]);
+ damon_add_region_tail(r, t);
+ }
+ damon_add_task_tail(t);
+
+ damon_apply_three_regions(t, new_regions);
+
+ for (i = 0; i < ARRAY_SIZE(answers) / 2; i++) {
+ r = damon_nth_region_of(t, i);
+ KUNIT_EXPECT_EQ(test, r->vm_start, answers[i * 2]);
+ KUNIT_EXPECT_EQ(test, r->vm_end, answers[i++ * 2 + 1]);
+ }
+
+ damon_cleanup_global_state();
+}
+
+static void damon_test_update_two_gaps4(struct kunit *test)
+{
+ struct damon_task *t;
+ struct damon_region *r;
+ /* 10-20-30, 50-55-57-59, 70-80-90-100 */
+ unsigned long regions[] = {10, 20, 20, 30,
+ 50, 55, 55, 57, 57, 59,
+ 70, 80, 80, 90, 90, 100};
+ struct region new_regions[3] = {
+ (struct region){.start = 5, .end = 7},
+ (struct region){.start = 30, .end = 32},
+ (struct region){.start = 65, .end = 68} };
+ /* expect 5-27, 56-57, 65-80-90-104 */
+ unsigned long answers[] = {5, 7, 30, 32, 65, 68};
+ int i;
+
+ t = damon_new_task(42);
+ for (i = 0; i < ARRAY_SIZE(regions) / 2; i++) {
+ r = damon_new_region(regions[i * 2], regions[i * 2 + 1]);
+ damon_add_region_tail(r, t);
+ }
+ damon_add_task_tail(t);
+
+ damon_apply_three_regions(t, new_regions);
+
+ for (i = 0; i < ARRAY_SIZE(answers) / 2; i++) {
+ r = damon_nth_region_of(t, i);
+ KUNIT_EXPECT_EQ(test, r->vm_start, answers[i * 2]);
+ KUNIT_EXPECT_EQ(test, r->vm_end, answers[i++ * 2 + 1]);
+ }
+
+ damon_cleanup_global_state();
+}
+
+static void damon_test_split_evenly(struct kunit *test)
+{
+ struct damon_task *t;
+ struct damon_region *r;
+ unsigned long i;
+
+ KUNIT_EXPECT_EQ(test, damon_split_region_evenly(NULL, 5), -EINVAL);
+
+ t = damon_new_task(42);
+ r = damon_new_region(0, 100);
+ KUNIT_EXPECT_EQ(test, damon_split_region_evenly(r, 0), -EINVAL);
+
+ damon_add_region_tail(r, t);
+ KUNIT_EXPECT_EQ(test, damon_split_region_evenly(r, 10), 0);
+ KUNIT_EXPECT_EQ(test, nr_damon_regions(t), 10u);
+
+ i = 0;
+ damon_for_each_region(r, t) {
+ KUNIT_EXPECT_EQ(test, r->vm_start, i++ * 10);
+ KUNIT_EXPECT_EQ(test, r->vm_end, i * 10);
+ }
+ damon_free_task(t);
+
+ t = damon_new_task(42);
+ r = damon_new_region(5, 59);
+ damon_add_region_tail(r, t);
+ KUNIT_EXPECT_EQ(test, damon_split_region_evenly(r, 5), 0);
+ KUNIT_EXPECT_EQ(test, nr_damon_regions(t), 5u);
+
+ i = 0;
+ damon_for_each_region(r, t) {
+ if (i == 4)
+ break;
+ KUNIT_EXPECT_EQ(test, r->vm_start, 5 + 10 * i++);
+ KUNIT_EXPECT_EQ(test, r->vm_end, 5 + 10 * i);
+ }
+ KUNIT_EXPECT_EQ(test, r->vm_start, 5 + 10 * i);
+ KUNIT_EXPECT_EQ(test, r->vm_end, 59ul);
+ damon_free_task(t);
+
+ t = damon_new_task(42);
+ r = damon_new_region(5, 6);
+ damon_add_region_tail(r, t);
+ KUNIT_EXPECT_EQ(test, damon_split_region_evenly(r, 2), -EINVAL);
+ KUNIT_EXPECT_EQ(test, nr_damon_regions(t), 1u);
+
+ damon_for_each_region(r, t) {
+ KUNIT_EXPECT_EQ(test, r->vm_start, 5ul);
+ KUNIT_EXPECT_EQ(test, r->vm_end, 6ul);
+ }
+ damon_free_task(t);
+}
+
+static void damon_test_split_at(struct kunit *test)
+{
+ struct damon_task *t;
+ struct damon_region *r;
+
+ t = damon_new_task(42);
+ r = damon_new_region(0, 100);
+ damon_add_region_tail(r, t);
+ damon_split_region_at(r, 25);
+ KUNIT_EXPECT_EQ(test, r->vm_start, 0ul);
+ KUNIT_EXPECT_EQ(test, r->vm_end, 25ul);
+
+ r = damon_next_region(r);
+ KUNIT_EXPECT_EQ(test, r->vm_start, 25ul);
+ KUNIT_EXPECT_EQ(test, r->vm_end, 100ul);
+
+ damon_free_task(t);
+}
+
+static void damon_test_merge_two(struct kunit *test)
+{
+ struct damon_task *t;
+ struct damon_region *r, *r2, *r3;
+ int i;
+
+ t = damon_new_task(42);
+ r = damon_new_region(0, 100);
+ r->nr_accesses = 10;
+ damon_add_region_tail(r, t);
+ r2 = damon_new_region(100, 300);
+ r2->nr_accesses = 20;
+ damon_add_region_tail(r2, t);
+
+ damon_merge_two_regions(r, r2);
+ KUNIT_EXPECT_EQ(test, r->vm_start, 0ul);
+ KUNIT_EXPECT_EQ(test, r->vm_end, 300ul);
+ KUNIT_EXPECT_EQ(test, r->nr_accesses, 16u);
+
+ i = 0;
+ damon_for_each_region(r3, t) {
+ KUNIT_EXPECT_PTR_EQ(test, r, r3);
+ i++;
+ }
+ KUNIT_EXPECT_EQ(test, i, 1);
+
+ damon_free_task(t);
+}
+
+static void damon_test_merge_regions_of(struct kunit *test)
+{
+ struct damon_task *t;
+ struct damon_region *r;
+ unsigned long sa[] = {0, 100, 114, 122, 130, 156, 170, 184};
+ unsigned long ea[] = {100, 112, 122, 130, 156, 170, 184, 230};
+ unsigned int nrs[] = {0, 0, 10, 10, 20, 30, 1, 2};
+
+ unsigned long saddrs[] = {0, 114, 130, 156, 170};
+ unsigned long eaddrs[] = {112, 130, 156, 170, 230};
+ int i;
+
+ t = damon_new_task(42);
+ for (i = 0; i < ARRAY_SIZE(sa); i++) {
+ r = damon_new_region(sa[i], ea[i]);
+ r->nr_accesses = nrs[i];
+ damon_add_region_tail(r, t);
+ }
+
+ damon_merge_regions_of(t, 9);
+ /* 0-112, 114-130, 130-156, 156-170 */
+ KUNIT_EXPECT_EQ(test, nr_damon_regions(t), 5u);
+ for (i = 0; i < 5; i++) {
+ r = damon_nth_region_of(t, i);
+ KUNIT_EXPECT_EQ(test, r->vm_start, saddrs[i]);
+ KUNIT_EXPECT_EQ(test, r->vm_end, eaddrs[i]);
+ }
+ damon_free_task(t);
+}
+
+static void damon_test_split_regions_of(struct kunit *test)
+{
+ struct damon_task *t;
+ struct damon_region *r;
+
+ t = damon_new_task(42);
+ r = damon_new_region(0, 22);
+ damon_add_region_tail(r, t);
+ damon_split_regions_of(t);
+ KUNIT_EXPECT_EQ(test, nr_damon_regions(t), 2u);
+ damon_free_task(t);
+}
+
+static void damon_test_kdamond_need_stop(struct kunit *test)
+{
+ KUNIT_EXPECT_TRUE(test, kdamond_need_stop());
+}
+
+static struct kunit_case damon_test_cases[] = {
+ KUNIT_CASE(damon_test_str_to_pids),
+ KUNIT_CASE(damon_test_tasks),
+ KUNIT_CASE(damon_test_regions),
+ KUNIT_CASE(damon_test_set_pids),
+ KUNIT_CASE(damon_test_three_regions_in_vmas),
+ KUNIT_CASE(damon_test_aggregate),
+ KUNIT_CASE(damon_test_write_rbuf),
+ KUNIT_CASE(damon_test_update_two_gaps),
+ KUNIT_CASE(damon_test_update_two_gaps2),
+ KUNIT_CASE(damon_test_update_two_gaps3),
+ KUNIT_CASE(damon_test_update_two_gaps4),
+ KUNIT_CASE(damon_test_split_evenly),
+ KUNIT_CASE(damon_test_split_at),
+ KUNIT_CASE(damon_test_merge_two),
+ KUNIT_CASE(damon_test_merge_regions_of),
+ KUNIT_CASE(damon_test_split_regions_of),
+ KUNIT_CASE(damon_test_kdamond_need_stop),
+ {},
+};
+
+static struct kunit_suite damon_test_suite = {
+ .name = "damon",
+ .test_cases = damon_test_cases,
+};
+kunit_test_suite(damon_test_suite);
+
+#endif /* _DAMON_TEST_H */
+
+#endif /* CONFIG_DAMON_TEST */
diff --git a/mm/damon.c b/mm/damon.c
index 0e99b4875700..c4b6b2db9a8c 100644
--- a/mm/damon.c
+++ b/mm/damon.c
@@ -1262,3 +1262,5 @@ static int __init damon_init(void)
}
module_init(damon_init);
+
+#include "damon-test.h"
--
2.17.1
Adding more recipients for comments. The original RFC mail is available at:
https://lore.kernel.org/linux-mm/[email protected]/
Thanks,
SeongJae Park
On Fri, 10 Jan 2020 14:15:17 +0100 SeongJae Park <[email protected]> wrote:
> From: SeongJae Park <[email protected]>
>
> This RFC patchset introduces a new kernel module for practical monitoring of
> data accesses, namely DAMON.
>
> The patches are organized in the following sequence. The first and second
> patch introduces the core logic and the raw level user interface of DAMON,
> respectively. To provide a minimal reference to the raw level interfaces and
> for more convenient test of the DAMON itself, the third patch implements an
> user space wrapper tools for the DAMON. The fourth patch adds a document for
> the DAMON, and finally the fifth patch provides DAMON's unit tests, which is
> using the kunit framework.
>
> The patches are based on the v5.4 plus the back-ported kunit, which retrieved
> from v5.5-rc1. You can also clone the complete git tree by:
>
> $ git clone git://github.com/sjp38/linux -b damon/rfc/v1
>
> The web is also available:
> https://github.com/sjp38/linux/releases/tag/damon/rfc/v1
>
> ----
>
> DAMON is a kernel module that allows users to monitor the actual memory access
> pattern of specific user-space processes. It aims to be 1) accurate enough to
> be useful for performance-centric domains, and 2) sufficiently light-weight so
> that it can be applied online.
>
> For the goals, DAMON utilizes its two core mechanisms, called region-based
> sampling and adaptive regions adjustment. The region-based sampling allows
> users to make their own trade-off between the quality and the overhead of the
> monitoring and set the upperbound of the monitoring overhead. Further, the
> adaptive regions adjustment mechanism makes DAMON to maximize the quality and
> minimize the overhead with its best efforts while preserving the users
> configured trade-off.
>
>
> Background
> ==========
>
> For performance-centric analysis and optimizations of memory management schemes
> (either that of kernel space or user space), the actual data access pattern of
> the workloads is highly useful. The information need to be only reasonable
> rather than strictly correct, because some level of incorrectness can be
> handled in many performance-centric domains. It also need to be taken within
> reasonably short time with only light-weight overhead.
>
> Manually extracting such data is not easy and time consuming if the target
> workload is huge and complex, even for the developers of the programs. There
> are a range of tools and techniques developed for general memory access
> investigations, and some of those could be partially used for this purpose.
> However, most of those are not practical or unscalable, mainly because those
> are designed with no consideration about the trade-off between the accuracy of
> the output and the overhead.
>
> The memory access instrumentation techniques which is applied to many tools
> such as Intel PIN is essential for correctness required cases such as invalid
> memory access bug detections. However, those usually incur high overhead which
> is unacceptable for many of the performance-centric domains. Periodic access
> checks based on H/W or S/W access counting features (e.g., the Accessed bits of
> PTEs or the PG_Idle flags of pages) can dramatically decrease the overhead by
> forgiving some of the quality, compared to the instrumentation based
> techniques. The reduced quality is still reasonable for many of the domains,
> but the overhead can arbitrarily increase as the size of the target workload
> grows. Miniature-like static region based sampling can set the upperbound of
> the overhead, but it will now decrease the quality of the output as the size of
> the workload grows.
>
>
> Related Works
> =============
>
> There are a number of researches[1,2,3,4,5,6] optimizing memory management
> mechanisms based on the actual memory access patterns that shows impressive
> results. However, most of those has no deep consideration about the monitoring
> of the accesses itself. Some of those focused on the overhead of the
> monitoring, but does not consider the accuracy scalability[6] or has additional
> dependencies[7]. Indeed, one recent research[5] about the proactive
> reclamation has also proposed[8] to the kernel community but the monitoring
> overhead was considered a main problem.
>
> [1] Subramanya R Dulloor, Amitabha Roy, Zheguang Zhao, Narayanan Sundaram,
> Nadathur Satish, Rajesh Sankaran, Jeff Jackson, and Karsten Schwan. 2016.
> Data tiering in heterogeneous memory systems. In Proceedings of the 11th
> European Conference on Computer Systems (EuroSys). ACM, 15.
> [2] Youngjin Kwon, Hangchen Yu, Simon Peter, Christopher J Rossbach, and Emmett
> Witchel. 2016. Coordinated and efficient huge page management with ingens.
> In 12th USENIX Symposium on Operating Systems Design and Implementation
> (OSDI). 705–721.
> [3] Harald Servat, Antonio J Peña, Germán Llort, Estanislao Mercadal,
> HansChristian Hoppe, and Jesús Labarta. 2017. Automating the application
> data placement in hybrid memory systems. In 2017 IEEE International
> Conference on Cluster Computing (CLUSTER). IEEE, 126–136.
> [4] Vlad Nitu, Boris Teabe, Alain Tchana, Canturk Isci, and Daniel Hagimont.
> 2018. Welcome to zombieland: practical and energy-efficient memory
> disaggregation in a datacenter. In Proceedings of the 13th European
> Conference on Computer Systems (EuroSys). ACM, 16.
> [5] Andres Lagar-Cavilla, Junwhan Ahn, Suleiman Souhlal, Neha Agarwal, Radoslaw
> Burny, Shakeel Butt, Jichuan Chang, Ashwin Chaugule, Nan Deng, Junaid
> Shahid, Greg Thelen, Kamil Adam Yurtsever, Yu Zhao, and Parthasarathy
> Ranganathan. 2019. Software-Defined Far Memory in Warehouse-Scale
> Computers. In Proceedings of the 24th International Conference on
> Architectural Support for Programming Languages and Operating Systems
> (ASPLOS). ACM, New York, NY, USA, 317–330.
> DOI:https://doi.org/10.1145/3297858.3304053
> [6] Carl Waldspurger, Trausti Saemundsson, Irfan Ahmad, and Nohhyun Park.
> 2017. Cache Modeling and Optimization using Miniature Simulations. In 2017
> USENIX Annual Technical Conference (ATC). USENIX Association, Santa
> Clara, CA, 487–498.
> https://www.usenix.org/conference/atc17/technical-sessions/
> [7] Haojie Wang, Jidong Zhai, Xiongchao Tang, Bowen Yu, Xiaosong Ma, and
> Wenguang Chen. 2018. Spindle: Informed Memory Access Monitoring. In 2018
> USENIX Annual Technical Conference (ATC). USENIX Association, Boston, MA,
> 561–574. https://www.usenix.org/conference/atc18/presentation/wang-haojie
> [8] Jonathan Corbet. 2019. Proactively reclaiming idle memory. (2019).
> https://lwn.net/Articles/787611/.
>
>
> Expected Use-cases
> ==================
>
> A straightforward usecase of DAMON would be the program behavior analysis.
> With the DAMON output, users can confirm whether the program is running as
> intended or not. This will be useful for debuggings and tests of design
> points.
>
> The monitored results can also be useful for counting the dynamic working set
> size of workloads. For the administration of memory overcommitted systems or
> selection of the environments (e.g., containers providing different amount of
> memory) for your workloads, this will be useful.
>
> If you are a programmer, you can optimize your program by managing the memory
> based on the actual data access pattern. For example, you can identify the
> dynamic hotness of your data using DAMON and call ``mlock()`` to keep your hot
> data in DRAM, or call ``madvise()`` with ``MADV_PAGEOUT`` to proactively
> reclaim cold data. Even though your program is guaranteed to not encounter
> memory pressure, you can still improve the performance by applying the DAMON
> outputs for call of ``MADV_HUGEPAGE`` and ``MADV_NOHUGEPAGE``. More creative
> optimizations would be possible. Our evaluations of DAMON includes a
> straightforward optimization using the ``mlock()``. Please refer to the below
> Evaluation section for more detail.
>
> As DAMON incurs very low overhead, such optimizations can be applied not only
> offline, but also online. Also, there is no reason to limit such optimizations
> to the user space. Several parts of the kernel's memory management mechanisms
> could be also optimized using DAMON. The reclamation, the THP (de)promotion
> decisions, and the compaction would be such a candidates. Nevertheless,
> current version of DAMON is not highly optimized for the online/in-kernel uses.
>
>
> Mechanisms of DAMON
> ===================
>
>
> Basic Access Check
> ------------------
>
> DAMON basically reports what pages are how frequently accessed. The report is
> passed to users in binary format via a ``result file`` which users can set it's
> path. Note that the frequency is not an absolute number of accesses, but a
> relative frequency among the pages of the target workloads.
>
> Users can also control the resolution of the reports by setting two time
> intervals, ``sampling interval`` and ``aggregation interval``. In detail,
> DAMON checks access to each page per ``sampling interval``, aggregates the
> results (counts the number of the accesses to each page), and reports the
> aggregated results per ``aggregation interval``. For the access check of each
> page, DAMON uses the Accessed bits of PTEs.
>
> This is thus similar to the previously mentioned periodic access checks based
> mechanisms, which overhead is increasing as the size of the target process
> grows.
>
>
> Region Based Sampling
> ---------------------
>
> To avoid the unbounded increase of the overhead, DAMON groups a number of
> adjacent pages that assumed to have same access frequencies into a region. As
> long as the assumption (pages in a region have same access frequencies) is
> kept, only one page in the region is required to be checked. Thus, for each
> ``sampling interval``, DAMON randomly picks one page in each region and clears
> its Accessed bit. After one more ``sampling interval``, DAMON reads the
> Accessed bit of the page and increases the access frequency of the region if
> the bit has set meanwhile. Therefore, the monitoring overhead is controllable
> by setting the number of regions. DAMON allows users to set the minimal and
> maximum number of regions for the trade-off.
>
> Except the assumption, this is almost same with the above-mentioned
> miniature-like static region based sampling. In other words, this scheme
> cannot preserve the quality of the output if the assumption is not guaranteed.
>
>
> Adaptive Regions Adjustment
> ---------------------------
>
> At the beginning of the monitoring, DAMON constructs the initial regions by
> evenly splitting the memory mapped address space of the process into the
> user-specified minimal number of regions. In this initial state, the
> assumption is normally not kept and thus the quality could be low. To keep the
> assumption as much as possible, DAMON adaptively merges and splits each region.
> For each ``aggregation interval``, it compares the access frequencies of
> adjacent regions and merges those if the frequency difference is small. Then,
> after it reports and clears the aggregated access frequency of each region, it
> splits each region into two regions if the total number of regions is smaller
> than the half of the user-specified maximum number of regions.
>
> In this way, DAMON provides its best-effort quality and minimal overhead while
> keeping the bounds users set for their trade-off.
>
>
> Applying Dynamic Memory Mappings
> --------------------------------
>
> Only a number of small parts in the super-huge virtual address space of the
> processes is mapped to physical memory and accessed. Thus, tracking the
> unmapped address regions is just wasteful. However, tracking every memory
> mapping change might incur an overhead. For the reason, DAMON applies the
> dynamic memory mapping changes to the tracking regions only for each of an
> user-specified time interval (``regions update interval``).
>
>
> Evaluations
> ===========
>
> A prototype of DAMON has evaluated on an Intel Xeon E7-8837 machine using 20
> benchmarks that picked from SPEC CPU 2006, NAS, Tensorflow Benchmark,
> SPLASH-2X, and PARSEC 3 benchmark suite. Nonethless, this section provides
> only summary of the results. For more detail, please refer to the slides used
> for the introduction of DAMON at the Linux Plumbers Conference 2019[1] or the
> MIDDLEWARE'19 industrial track paper[2].
>
>
> Quality
> -------
>
> We first traced and visualized the data access pattern of each workload. We
> were able to confirm that the visualized results are reasonably accurate by
> manually comparing those with the source code of the workloads.
>
> To see the usefulness of the monitoring, we optimized 9 memory intensive
> workloads among them for memory pressure situations using the DAMON outputs.
> In detail, we identified frequently accessed memory regions in each workload
> based on the DAMON results and protected them with ``mlock()`` system calls.
> The optimized versions consistently show speedup (2.55x in best case, 1.65x in
> average) under memory pressure situation.
>
>
> Overhead
> --------
>
> We also measured the overhead of DAMON. It was not only under the upperbound
> we set, but was much lower (0.6 percent of the bound in best case, 13.288
> percent of the bound in average). This reduction of the overhead is mainly
> resulted from the adaptive regions adjustment. We also compared the overhead
> with that of the straightforward periodic Accessed bit check-based monitoring,
> which checks the access of every page frame. DAMON's overhead was much smaller
> than the straightforward mechanism by 94,242.42x in best case, 3,159.61x in
> average.
>
>
> References
> ==========
>
> Prototypes of DAMON have introduced by an LPC kernel summit track talk[1] and
> two academic papers[2,3]. Please refer to those for more detailed information,
> especially the evaluations.
>
> [1] SeongJae Park, Tracing Data Access Pattern with Bounded Overhead and
> Best-effort Accuracy. In The Linux Kernel Summit, September 2019.
> https://linuxplumbersconf.org/event/4/contributions/548/
> [2] SeongJae Park, Yunjae Lee, Heon Y. Yeom, Profiling Dynamic Data Access
> Patterns with Controlled Overhead and Quality. In 20th ACM/IFIP
> International Middleware Conference Industry, December 2019.
> https://dl.acm.org/doi/10.1145/3366626.3368125
> [3] SeongJae Park, Yunjae Lee, Yunhee Kim, Heon Y. Yeom, Profiling Dynamic Data
> Access Patterns with Bounded Overhead and Accuracy. In IEEE International
> Workshop on Foundations and Applications of Self- Systems (FAS 2019), June
> 2019.
>
>
> SeongJae Park (5):
> mm: Introduce Data Access MONitor (DAMON)
> mm/damon: Add debugfs interface
> mm/damon: Add minimal user-space tools
> Documentation/admin-guide/mm: Add a document for DAMON
> mm/damon: Add kunit tests
>
> .../admin-guide/mm/data_access_monitor.rst | 235 +++
> Documentation/admin-guide/mm/index.rst | 1 +
> mm/Kconfig | 23 +
> mm/Makefile | 1 +
> mm/damon-test.h | 571 ++++++++
> mm/damon.c | 1266 +++++++++++++++++
> tools/damon/bin2txt.py | 64 +
> tools/damon/damn | 36 +
> tools/damon/heats.py | 358 +++++
> tools/damon/nr_regions.py | 116 ++
> tools/damon/record.py | 182 +++
> tools/damon/report.py | 45 +
> tools/damon/wss.py | 121 ++
> 13 files changed, 3019 insertions(+)
> create mode 100644 Documentation/admin-guide/mm/data_access_monitor.rst
> create mode 100644 mm/damon-test.h
> create mode 100644 mm/damon.c
> create mode 100644 tools/damon/bin2txt.py
> create mode 100644 tools/damon/damn
> create mode 100644 tools/damon/heats.py
> create mode 100644 tools/damon/nr_regions.py
> create mode 100644 tools/damon/record.py
> create mode 100644 tools/damon/report.py
> create mode 100644 tools/damon/wss.py
>
> --
> 2.17.1
>
On Fri, Jan 10, 2020 at 5:18 AM SeongJae Park <[email protected]> wrote:
>
> From: SeongJae Park <[email protected]>
>
> This commit adds kunit based unit tests for DAMON.
>
> Signed-off-by: SeongJae Park <[email protected]>
Sorry for the late review on this: I am still getting caught up on my
vacation backlog.
> ---
> mm/Kconfig | 11 +
> mm/damon-test.h | 571 ++++++++++++++++++++++++++++++++++++++++++++++++
> mm/damon.c | 2 +
> 3 files changed, 584 insertions(+)
> create mode 100644 mm/damon-test.h
>
> diff --git a/mm/Kconfig b/mm/Kconfig
> index b7af8a1b5cb5..7b023799aa38 100644
> --- a/mm/Kconfig
> +++ b/mm/Kconfig
> @@ -748,4 +748,15 @@ config DAMON
> be 1) accurate enough to be useful for performance-centric domains,
> and 2) sufficiently light-weight so that it can be applied online.
>
> +config DAMON_TEST
To be consistent with other KUnit tests, this should be "DAMON_KUNIT_TEST".
> + bool "Test for damon"
> + depends on DAMON && KUNIT
> + help
> + This builds the DAMON Kunit test suite.
> +
> + For more information on KUnit and unit tests in general, please refer
> + to the KUnit documentation.
> +
> + If unsure, say N.
> +
> endmenu
> diff --git a/mm/damon-test.h b/mm/damon-test.h
> new file mode 100644
> index 000000000000..0d94910b8fe5
> --- /dev/null
> +++ b/mm/damon-test.h
> @@ -0,0 +1,571 @@
> +/* SPDX-License-Identifier: GPL-2.0 */
> +/*
> + * Data Access Monitor Unit Tests
> + *
> + * Copyright 2019 Amazon.com, Inc. or its affiliates. All rights reserved.
> + *
> + * Author: SeongJae Park <[email protected]>
> + */
> +
> +#ifdef CONFIG_DAMON_TEST
> +
> +#ifndef _DAMON_TEST_H
> +#define _DAMON_TEST_H
> +
> +#include <kunit/test.h>
> +
> +static void damon_test_str_to_pids(struct kunit *test)
> +{
> + char *question;
> + unsigned long *answers;
> + unsigned long expected[] = {12, 35, 46};
> + ssize_t nr_integers = 0, i;
> +
> + question = "123";
> + answers = str_to_pids(question, strnlen(question, 128), &nr_integers);
> + KUNIT_EXPECT_EQ(test, 1l, nr_integers);
> + KUNIT_EXPECT_EQ(test, 123ul, answers[0]);
> + kfree(answers);
> +
> + question = "123abc";
> + answers = str_to_pids(question, strnlen(question, 128), &nr_integers);
> + KUNIT_EXPECT_EQ(test, 1l, nr_integers);
> + KUNIT_EXPECT_EQ(test, 123ul, answers[0]);
> + kfree(answers);
> +
> + question = "a123";
> + answers = str_to_pids(question, strnlen(question, 128), &nr_integers);
> + KUNIT_EXPECT_EQ(test, 0l, nr_integers);
> + KUNIT_EXPECT_PTR_EQ(test, answers, (unsigned long *)NULL);
> +
> + question = "12 35";
> + answers = str_to_pids(question, strnlen(question, 128), &nr_integers);
> + KUNIT_EXPECT_EQ(test, 2l, nr_integers);
> + for (i = 0; i < nr_integers; i++)
> + KUNIT_EXPECT_EQ(test, expected[i], answers[i]);
> + kfree(answers);
> +
> + question = "12 35 46";
> + answers = str_to_pids(question, strnlen(question, 128), &nr_integers);
> + KUNIT_EXPECT_EQ(test, 3l, nr_integers);
> + for (i = 0; i < nr_integers; i++)
> + KUNIT_EXPECT_EQ(test, expected[i], answers[i]);
> + kfree(answers);
> +
> + question = "12 35 abc 46";
> + answers = str_to_pids(question, strnlen(question, 128), &nr_integers);
> + KUNIT_EXPECT_EQ(test, 2l, nr_integers);
> + for (i = 0; i < 2; i++)
> + KUNIT_EXPECT_EQ(test, expected[i], answers[i]);
> + kfree(answers);
> +
> + question = "";
> + answers = str_to_pids(question, strnlen(question, 128), &nr_integers);
> + KUNIT_EXPECT_EQ(test, 0l, nr_integers);
> + KUNIT_EXPECT_PTR_EQ(test, (unsigned long *)NULL, answers);
> + kfree(answers);
> +
> + question = "\n";
> + answers = str_to_pids(question, strnlen(question, 128), &nr_integers);
> + KUNIT_EXPECT_EQ(test, 0l, nr_integers);
> + KUNIT_EXPECT_PTR_EQ(test, (unsigned long *)NULL, answers);
> + kfree(answers);
> +}
> +
> +static void damon_test_regions(struct kunit *test)
> +{
> + struct damon_region *r;
> + struct damon_task *t;
> +
> + r = damon_new_region(1, 2);
> + KUNIT_EXPECT_EQ(test, 1ul, r->vm_start);
> + KUNIT_EXPECT_EQ(test, 2ul, r->vm_end);
> + KUNIT_EXPECT_EQ(test, 0u, r->nr_accesses);
> + KUNIT_EXPECT_TRUE(test, r->sampling_addr >= r->vm_start);
> + KUNIT_EXPECT_TRUE(test, r->sampling_addr < r->vm_end);
> +
> + t = damon_new_task(42);
> + KUNIT_EXPECT_EQ(test, 0u, nr_damon_regions(t));
> +
> + damon_add_region_tail(r, t);
> + KUNIT_EXPECT_EQ(test, 1u, nr_damon_regions(t));
> +
> + damon_del_region(r);
> + KUNIT_EXPECT_EQ(test, 0u, nr_damon_regions(t));
> +
> + damon_free_task(t);
> +}
> +
> +static void damon_test_tasks(struct kunit *test)
> +{
> + struct damon_task *t;
> +
> + t = damon_new_task(42);
> + KUNIT_EXPECT_EQ(test, 42ul, t->pid);
> + KUNIT_EXPECT_EQ(test, 0u, nr_damon_tasks());
> +
> + damon_add_task_tail(t);
> + KUNIT_EXPECT_EQ(test, 1u, nr_damon_tasks());
> +
> + damon_destroy_task(t);
> + KUNIT_EXPECT_EQ(test, 0u, nr_damon_tasks());
> +}
> +
> +static void damon_test_set_pids(struct kunit *test)
> +{
> + unsigned long pids[] = {1, 2, 3};
> + char buf[64];
> +
> + damon_set_pids(pids, 3);
> + damon_sprint_pids(buf, 64);
> + pr_info("buf: %s (%zu)\n", buf, strlen(buf));
Might want to use kunit_info here so it matches the TAP test log
format. Not a requirement, just an FYI.
> + KUNIT_EXPECT_EQ(test, 0, strncmp(buf, "1 2 3\n", 64));
Here and elsewhere: This should probably use KUNIT_EXPECT_STREQ().
> +
> + damon_set_pids(NULL, 0);
> + damon_sprint_pids(buf, 64);
> + KUNIT_EXPECT_EQ(test, 0, strncmp(buf, "\n", 64));
> +
> + damon_set_pids((unsigned long []){1, 2}, 2);
> + damon_sprint_pids(buf, 64);
> + KUNIT_EXPECT_EQ(test, 0, strncmp(buf, "1 2\n", 64));
> +
> + damon_set_pids((unsigned long []){2}, 1);
> + damon_sprint_pids(buf, 64);
> + KUNIT_EXPECT_EQ(test, 0, strncmp(buf, "2\n", 64));
> +
> + damon_set_pids(NULL, 0);
> + damon_sprint_pids(buf, 64);
> + KUNIT_EXPECT_EQ(test, 0, strncmp(buf, "\n", 64));
> +}
> +
> +static void damon_test_three_regions_in_vmas(struct kunit *test)
> +{
> + struct region regions[3] = {0,};
> +
> + struct vm_area_struct vmas[] = {
> + (struct vm_area_struct) {.vm_start = 10, .vm_end = 20},
> + (struct vm_area_struct) {.vm_start = 20, .vm_end = 25},
> + (struct vm_area_struct) {.vm_start = 200, .vm_end = 210},
> + (struct vm_area_struct) {.vm_start = 210, .vm_end = 220},
> + (struct vm_area_struct) {.vm_start = 300, .vm_end = 305},
> + (struct vm_area_struct) {.vm_start = 307, .vm_end = 330},
> + };
> + vmas[0].vm_next = &vmas[1];
> + vmas[1].vm_next = &vmas[2];
> + vmas[2].vm_next = &vmas[3];
> + vmas[3].vm_next = &vmas[4];
> + vmas[4].vm_next = &vmas[5];
> + vmas[5].vm_next = NULL;
> +
> + damon_three_regions_in_vmas(&vmas[0], regions);
> +
> + KUNIT_EXPECT_EQ(test, 10ul, regions[0].start);
> + KUNIT_EXPECT_EQ(test, 25ul, regions[0].end);
> + KUNIT_EXPECT_EQ(test, 200ul, regions[1].start);
> + KUNIT_EXPECT_EQ(test, 220ul, regions[1].end);
> + KUNIT_EXPECT_EQ(test, 300ul, regions[2].start);
> + KUNIT_EXPECT_EQ(test, 330ul, regions[2].end);
It's not obvious to me what property you are proving here. Might want
to add a comment.
> +}
> +
> +/* Clean up global state of damon */
> +static void damon_cleanup_global_state(void)
> +{
> + struct damon_task *t, *next;
> +
> + damon_for_each_task_safe(t, next)
> + damon_destroy_task(t);
> +
> + damon_rbuf_offset = 0;
> +}
> +
> +static void damon_test_aggregate(struct kunit *test)
> +{
> + unsigned long pids[] = {1, 2, 3};
> + unsigned long saddr[][3] = {{10, 20, 30}, {5, 42, 49}, {13, 33, 55} };
> + unsigned long eaddr[][3] = {{15, 27, 40}, {31, 45, 55}, {23, 44, 66} };
> + unsigned long accesses[][3] = {{42, 95, 84}, {10, 20, 30}, {0, 1, 2} };
> + struct damon_task *t;
> + struct damon_region *r;
> + int it, ir;
> + ssize_t sz, sr, sp;
> +
> + damon_set_pids(pids, 3);
> +
> + it = 0;
> + damon_for_each_task(t) {
> + for (ir = 0; ir < 3; ir++) {
> + r = damon_new_region(saddr[it][ir], eaddr[it][ir]);
> + r->nr_accesses = accesses[it][ir];
> + damon_add_region_tail(r, t);
> + }
> + it++;
> + }
> + kdamond_flush_aggregated();
I think this test case is also difficult to understand. I think you
probably need at least a comment on what this test case does.
> + it = 0;
> + damon_for_each_task(t) {
> + ir = 0;
> + damon_for_each_region(r, t) {
> + KUNIT_EXPECT_EQ(test, 0u, r->nr_accesses);
> + ir++;
> + }
> + KUNIT_EXPECT_EQ(test, 3, ir);
> + it++;
> + }
> + KUNIT_EXPECT_EQ(test, 3, it);
> +
> + sr = sizeof(r->vm_start) + sizeof(r->vm_end) + sizeof(r->nr_accesses);
> + sp = sizeof(t->pid) + sizeof(unsigned int) + 3 * sr;
> + sz = sizeof(struct timespec64) + sizeof(unsigned int) + 3 * sp;
> + KUNIT_EXPECT_EQ(test, (unsigned int)sz, damon_rbuf_offset);
> +
> + damon_cleanup_global_state();
> +}
> +
> +static void damon_test_write_rbuf(struct kunit *test)
> +{
> + char *data;
> +
> + data = "hello";
> + damon_write_rbuf(data, strnlen(data, 256));
> + KUNIT_EXPECT_EQ(test, damon_rbuf_offset, 5u);
> +
> + damon_write_rbuf(data, 0);
> + KUNIT_EXPECT_EQ(test, damon_rbuf_offset, 5u);
> +
> + KUNIT_EXPECT_EQ(test, strncmp(damon_rbuf, data, 5), 0);
> +}
> +
> +static void damon_test_update_two_gaps(struct kunit *test)
> +{
I think this test case is also difficult to understand. I think you
probably need at least a comment on what this test case does.
> + struct damon_task *t;
> + struct damon_region *r, *prev = NULL;
> + unsigned long regions[] = {10, 20, 20, 30,
> + 50, 55, 55, 57, 57, 59,
> + 70, 80, 80, 90, 90, 100}; /* 10-30, 50-59, 70-100 */
> + struct region new_regions[3] = {
> + (struct region){.start = 5, .end = 27},
> + (struct region){.start = 45, .end = 55},
> + (struct region){.start = 73, .end = 104} };
> + int i;
> + bool first_gap = true;
> +
> + t = damon_new_task(42);
> + for (i = 0; i < ARRAY_SIZE(regions) / 2; i++) {
> + r = damon_new_region(regions[i * 2], regions[i * 2 + 1]);
> + damon_add_region_tail(r, t);
> + }
> + damon_add_task_tail(t);
> +
> + damon_apply_three_regions(t, new_regions);
> +
> + damon_for_each_region(r, t) {
> + if (prev == NULL) {
> + KUNIT_EXPECT_EQ(test, r->vm_start, 5ul);
> + goto next;
> + }
> +
> + if (prev->vm_end != r->vm_start && first_gap) {
> + KUNIT_EXPECT_EQ(test, prev->vm_end, 27ul);
> + KUNIT_EXPECT_EQ(test, r->vm_start, 45ul);
> + first_gap = false;
> + goto next;
> + }
> +
> + if (prev->vm_end != r->vm_start && !first_gap) {
> + KUNIT_EXPECT_EQ(test, prev->vm_end, 55ul);
> + KUNIT_EXPECT_EQ(test, r->vm_start, 73ul);
> + goto next;
> + }
> +
> +next:
> + prev = r;
> + }
> +
> + damon_cleanup_global_state();
> +}
> +
> +static void damon_test_update_two_gaps2(struct kunit *test)
> +{
Same here.
> + struct damon_task *t;
> + struct damon_region *r;
> + /* 10-20-30, 50-55-57-59, 70-80-90-100 */
> + unsigned long regions[] = {10, 20, 20, 30,
> + 50, 55, 55, 57, 57, 59,
> + 70, 80, 80, 90, 90, 100};
> + struct region new_regions[3] = {
> + (struct region){.start = 5, .end = 27},
> + (struct region){.start = 56, .end = 57},
> + (struct region){.start = 65, .end = 104} };
> + /* expect 5-27, 56-57, 65-80-90-104 */
> + unsigned long answers[] = {5, 20, 20, 27,
> + 56, 57,
> + 65, 80, 80, 90, 90, 104};
> + int i;
> +
> + t = damon_new_task(42);
> + for (i = 0; i < ARRAY_SIZE(regions) / 2; i++) {
> + r = damon_new_region(regions[i * 2], regions[i * 2 + 1]);
> + damon_add_region_tail(r, t);
> + }
> + damon_add_task_tail(t);
> +
> + damon_apply_three_regions(t, new_regions);
> +
> + for (i = 0; i < ARRAY_SIZE(answers) / 2; i++) {
> + r = damon_nth_region_of(t, i);
> + KUNIT_EXPECT_EQ(test, r->vm_start, answers[i * 2]);
> + KUNIT_EXPECT_EQ(test, r->vm_end, answers[i++ * 2 + 1]);
> + }
> +
> + damon_cleanup_global_state();
> +}
> +
> +static void damon_test_update_two_gaps3(struct kunit *test)
> +{
Same here.
> + struct damon_task *t;
> + struct damon_region *r;
> + /* 10-20-30, 50-55-57-59, 70-80-90-100 */
> + unsigned long regions[] = {10, 20, 20, 30,
> + 50, 55, 55, 57, 57, 59,
> + 70, 80, 80, 90, 90, 100};
> + struct region new_regions[3] = {
> + (struct region){.start = 5, .end = 27},
> + (struct region){.start = 61, .end = 63},
> + (struct region){.start = 65, .end = 104} };
> + /* expect 5-27, 56-57, 65-80-90-104 */
> + unsigned long answers[] = {5, 20, 20, 27,
> + 61, 63,
> + 65, 80, 80, 90, 90, 104};
> + int i;
> +
> + t = damon_new_task(42);
> + for (i = 0; i < ARRAY_SIZE(regions) / 2; i++) {
> + r = damon_new_region(regions[i * 2], regions[i * 2 + 1]);
> + damon_add_region_tail(r, t);
> + }
> + damon_add_task_tail(t);
> +
> + damon_apply_three_regions(t, new_regions);
> +
> + for (i = 0; i < ARRAY_SIZE(answers) / 2; i++) {
> + r = damon_nth_region_of(t, i);
> + KUNIT_EXPECT_EQ(test, r->vm_start, answers[i * 2]);
> + KUNIT_EXPECT_EQ(test, r->vm_end, answers[i++ * 2 + 1]);
> + }
> +
> + damon_cleanup_global_state();
> +}
> +
> +static void damon_test_update_two_gaps4(struct kunit *test)
> +{
Ditto.
> + struct damon_task *t;
> + struct damon_region *r;
> + /* 10-20-30, 50-55-57-59, 70-80-90-100 */
> + unsigned long regions[] = {10, 20, 20, 30,
> + 50, 55, 55, 57, 57, 59,
> + 70, 80, 80, 90, 90, 100};
> + struct region new_regions[3] = {
> + (struct region){.start = 5, .end = 7},
> + (struct region){.start = 30, .end = 32},
> + (struct region){.start = 65, .end = 68} };
> + /* expect 5-27, 56-57, 65-80-90-104 */
> + unsigned long answers[] = {5, 7, 30, 32, 65, 68};
> + int i;
> +
> + t = damon_new_task(42);
> + for (i = 0; i < ARRAY_SIZE(regions) / 2; i++) {
> + r = damon_new_region(regions[i * 2], regions[i * 2 + 1]);
> + damon_add_region_tail(r, t);
> + }
> + damon_add_task_tail(t);
> +
> + damon_apply_three_regions(t, new_regions);
> +
> + for (i = 0; i < ARRAY_SIZE(answers) / 2; i++) {
> + r = damon_nth_region_of(t, i);
> + KUNIT_EXPECT_EQ(test, r->vm_start, answers[i * 2]);
> + KUNIT_EXPECT_EQ(test, r->vm_end, answers[i++ * 2 + 1]);
> + }
> +
> + damon_cleanup_global_state();
> +}
> +
> +static void damon_test_split_evenly(struct kunit *test)
> +{
> + struct damon_task *t;
> + struct damon_region *r;
> + unsigned long i;
> +
> + KUNIT_EXPECT_EQ(test, damon_split_region_evenly(NULL, 5), -EINVAL);
> +
> + t = damon_new_task(42);
> + r = damon_new_region(0, 100);
> + KUNIT_EXPECT_EQ(test, damon_split_region_evenly(r, 0), -EINVAL);
> +
> + damon_add_region_tail(r, t);
> + KUNIT_EXPECT_EQ(test, damon_split_region_evenly(r, 10), 0);
> + KUNIT_EXPECT_EQ(test, nr_damon_regions(t), 10u);
> +
> + i = 0;
> + damon_for_each_region(r, t) {
> + KUNIT_EXPECT_EQ(test, r->vm_start, i++ * 10);
> + KUNIT_EXPECT_EQ(test, r->vm_end, i * 10);
> + }
> + damon_free_task(t);
> +
> + t = damon_new_task(42);
> + r = damon_new_region(5, 59);
> + damon_add_region_tail(r, t);
> + KUNIT_EXPECT_EQ(test, damon_split_region_evenly(r, 5), 0);
> + KUNIT_EXPECT_EQ(test, nr_damon_regions(t), 5u);
> +
> + i = 0;
> + damon_for_each_region(r, t) {
> + if (i == 4)
> + break;
> + KUNIT_EXPECT_EQ(test, r->vm_start, 5 + 10 * i++);
> + KUNIT_EXPECT_EQ(test, r->vm_end, 5 + 10 * i);
> + }
> + KUNIT_EXPECT_EQ(test, r->vm_start, 5 + 10 * i);
> + KUNIT_EXPECT_EQ(test, r->vm_end, 59ul);
> + damon_free_task(t);
> +
> + t = damon_new_task(42);
> + r = damon_new_region(5, 6);
> + damon_add_region_tail(r, t);
> + KUNIT_EXPECT_EQ(test, damon_split_region_evenly(r, 2), -EINVAL);
> + KUNIT_EXPECT_EQ(test, nr_damon_regions(t), 1u);
> +
> + damon_for_each_region(r, t) {
> + KUNIT_EXPECT_EQ(test, r->vm_start, 5ul);
> + KUNIT_EXPECT_EQ(test, r->vm_end, 6ul);
> + }
> + damon_free_task(t);
> +}
> +
> +static void damon_test_split_at(struct kunit *test)
> +{
> + struct damon_task *t;
> + struct damon_region *r;
> +
> + t = damon_new_task(42);
> + r = damon_new_region(0, 100);
> + damon_add_region_tail(r, t);
> + damon_split_region_at(r, 25);
> + KUNIT_EXPECT_EQ(test, r->vm_start, 0ul);
> + KUNIT_EXPECT_EQ(test, r->vm_end, 25ul);
> +
> + r = damon_next_region(r);
> + KUNIT_EXPECT_EQ(test, r->vm_start, 25ul);
> + KUNIT_EXPECT_EQ(test, r->vm_end, 100ul);
> +
> + damon_free_task(t);
> +}
> +
> +static void damon_test_merge_two(struct kunit *test)
> +{
> + struct damon_task *t;
> + struct damon_region *r, *r2, *r3;
> + int i;
> +
> + t = damon_new_task(42);
> + r = damon_new_region(0, 100);
> + r->nr_accesses = 10;
> + damon_add_region_tail(r, t);
> + r2 = damon_new_region(100, 300);
> + r2->nr_accesses = 20;
> + damon_add_region_tail(r2, t);
> +
> + damon_merge_two_regions(r, r2);
> + KUNIT_EXPECT_EQ(test, r->vm_start, 0ul);
> + KUNIT_EXPECT_EQ(test, r->vm_end, 300ul);
> + KUNIT_EXPECT_EQ(test, r->nr_accesses, 16u);
> +
> + i = 0;
> + damon_for_each_region(r3, t) {
> + KUNIT_EXPECT_PTR_EQ(test, r, r3);
> + i++;
> + }
> + KUNIT_EXPECT_EQ(test, i, 1);
> +
> + damon_free_task(t);
> +}
> +
> +static void damon_test_merge_regions_of(struct kunit *test)
> +{
> + struct damon_task *t;
> + struct damon_region *r;
> + unsigned long sa[] = {0, 100, 114, 122, 130, 156, 170, 184};
> + unsigned long ea[] = {100, 112, 122, 130, 156, 170, 184, 230};
> + unsigned int nrs[] = {0, 0, 10, 10, 20, 30, 1, 2};
> +
> + unsigned long saddrs[] = {0, 114, 130, 156, 170};
> + unsigned long eaddrs[] = {112, 130, 156, 170, 230};
> + int i;
> +
> + t = damon_new_task(42);
> + for (i = 0; i < ARRAY_SIZE(sa); i++) {
> + r = damon_new_region(sa[i], ea[i]);
> + r->nr_accesses = nrs[i];
> + damon_add_region_tail(r, t);
> + }
> +
> + damon_merge_regions_of(t, 9);
> + /* 0-112, 114-130, 130-156, 156-170 */
> + KUNIT_EXPECT_EQ(test, nr_damon_regions(t), 5u);
> + for (i = 0; i < 5; i++) {
> + r = damon_nth_region_of(t, i);
> + KUNIT_EXPECT_EQ(test, r->vm_start, saddrs[i]);
> + KUNIT_EXPECT_EQ(test, r->vm_end, eaddrs[i]);
> + }
> + damon_free_task(t);
> +}
> +
> +static void damon_test_split_regions_of(struct kunit *test)
> +{
> + struct damon_task *t;
> + struct damon_region *r;
> +
> + t = damon_new_task(42);
> + r = damon_new_region(0, 22);
> + damon_add_region_tail(r, t);
> + damon_split_regions_of(t);
> + KUNIT_EXPECT_EQ(test, nr_damon_regions(t), 2u);
> + damon_free_task(t);
> +}
> +
> +static void damon_test_kdamond_need_stop(struct kunit *test)
> +{
> + KUNIT_EXPECT_TRUE(test, kdamond_need_stop());
> +}
> +
> +static struct kunit_case damon_test_cases[] = {
> + KUNIT_CASE(damon_test_str_to_pids),
> + KUNIT_CASE(damon_test_tasks),
> + KUNIT_CASE(damon_test_regions),
> + KUNIT_CASE(damon_test_set_pids),
> + KUNIT_CASE(damon_test_three_regions_in_vmas),
> + KUNIT_CASE(damon_test_aggregate),
> + KUNIT_CASE(damon_test_write_rbuf),
> + KUNIT_CASE(damon_test_update_two_gaps),
> + KUNIT_CASE(damon_test_update_two_gaps2),
> + KUNIT_CASE(damon_test_update_two_gaps3),
> + KUNIT_CASE(damon_test_update_two_gaps4),
> + KUNIT_CASE(damon_test_split_evenly),
> + KUNIT_CASE(damon_test_split_at),
> + KUNIT_CASE(damon_test_merge_two),
> + KUNIT_CASE(damon_test_merge_regions_of),
> + KUNIT_CASE(damon_test_split_regions_of),
> + KUNIT_CASE(damon_test_kdamond_need_stop),
> + {},
> +};
> +
> +static struct kunit_suite damon_test_suite = {
> + .name = "damon",
> + .test_cases = damon_test_cases,
> +};
> +kunit_test_suite(damon_test_suite);
> +
> +#endif /* _DAMON_TEST_H */
> +
> +#endif /* CONFIG_DAMON_TEST */
> diff --git a/mm/damon.c b/mm/damon.c
> index 0e99b4875700..c4b6b2db9a8c 100644
> --- a/mm/damon.c
> +++ b/mm/damon.c
> @@ -1262,3 +1262,5 @@ static int __init damon_init(void)
> }
>
> module_init(damon_init);
> +
> +#include "damon-test.h"
> --
> 2.17.1
>
On Thu, 23 Jan 2020 13:12:55 -0800 Brendan Higgins <[email protected]> wrote:
> On Fri, Jan 10, 2020 at 5:18 AM SeongJae Park <[email protected]> wrote:
> >
> > From: SeongJae Park <[email protected]>
> >
> > This commit adds kunit based unit tests for DAMON.
> >
> > Signed-off-by: SeongJae Park <[email protected]>
>
> Sorry for the late review on this: I am still getting caught up on my
> vacation backlog.
Thank you so much for this review, Brendan :)
BTW, I posted 'PATCH v1' of this [1] meanwhile and I forgot adding you as
recipients, sorry. That said, the kunit related part has no change with the
next spin, so your reviews will applied. Will not miss you from 'v2'.
[1] https://lore.kernel.org/linux-mm/[email protected]/
>
> > ---
> > mm/Kconfig | 11 +
> > mm/damon-test.h | 571 ++++++++++++++++++++++++++++++++++++++++++++++++
> > mm/damon.c | 2 +
> > 3 files changed, 584 insertions(+)
> > create mode 100644 mm/damon-test.h
> >
> > diff --git a/mm/Kconfig b/mm/Kconfig
> > index b7af8a1b5cb5..7b023799aa38 100644
> > --- a/mm/Kconfig
> > +++ b/mm/Kconfig
> > @@ -748,4 +748,15 @@ config DAMON
> > be 1) accurate enough to be useful for performance-centric domains,
> > and 2) sufficiently light-weight so that it can be applied online.
> >
> > +config DAMON_TEST
>
> To be consistent with other KUnit tests, this should be "DAMON_KUNIT_TEST".
Good point, will do so.
>
> > + bool "Test for damon"
> > + depends on DAMON && KUNIT
> > + help
> > + This builds the DAMON Kunit test suite.
> > +
> > + For more information on KUnit and unit tests in general, please refer
> > + to the KUnit documentation.
> > +
> > + If unsure, say N.
> > +
> > endmenu
> > diff --git a/mm/damon-test.h b/mm/damon-test.h
> > new file mode 100644
> > index 000000000000..0d94910b8fe5
> > --- /dev/null
> > +++ b/mm/damon-test.h
> > @@ -0,0 +1,571 @@
[...]
> > +
> > +static void damon_test_set_pids(struct kunit *test)
> > +{
> > + unsigned long pids[] = {1, 2, 3};
> > + char buf[64];
> > +
> > + damon_set_pids(pids, 3);
> > + damon_sprint_pids(buf, 64);
> > + pr_info("buf: %s (%zu)\n", buf, strlen(buf));
>
> Might want to use kunit_info here so it matches the TAP test log
> format. Not a requirement, just an FYI.
Oh, this is a debugging code I missed to delete. Will delete from next spin.
Also, will use 'kunit_info()' like things if I need any log, either.
>
> > + KUNIT_EXPECT_EQ(test, 0, strncmp(buf, "1 2 3\n", 64));
>
> Here and elsewhere: This should probably use KUNIT_EXPECT_STREQ().
Good point, will fix with the next spin.
>
[...]
> > +
> > +static void damon_test_three_regions_in_vmas(struct kunit *test)
> > +{
> > + struct region regions[3] = {0,};
> > +
> > + struct vm_area_struct vmas[] = {
> > + (struct vm_area_struct) {.vm_start = 10, .vm_end = 20},
> > + (struct vm_area_struct) {.vm_start = 20, .vm_end = 25},
> > + (struct vm_area_struct) {.vm_start = 200, .vm_end = 210},
> > + (struct vm_area_struct) {.vm_start = 210, .vm_end = 220},
> > + (struct vm_area_struct) {.vm_start = 300, .vm_end = 305},
> > + (struct vm_area_struct) {.vm_start = 307, .vm_end = 330},
> > + };
> > + vmas[0].vm_next = &vmas[1];
> > + vmas[1].vm_next = &vmas[2];
> > + vmas[2].vm_next = &vmas[3];
> > + vmas[3].vm_next = &vmas[4];
> > + vmas[4].vm_next = &vmas[5];
> > + vmas[5].vm_next = NULL;
> > +
> > + damon_three_regions_in_vmas(&vmas[0], regions);
> > +
> > + KUNIT_EXPECT_EQ(test, 10ul, regions[0].start);
> > + KUNIT_EXPECT_EQ(test, 25ul, regions[0].end);
> > + KUNIT_EXPECT_EQ(test, 200ul, regions[1].start);
> > + KUNIT_EXPECT_EQ(test, 220ul, regions[1].end);
> > + KUNIT_EXPECT_EQ(test, 300ul, regions[2].start);
> > + KUNIT_EXPECT_EQ(test, 330ul, regions[2].end);
>
> It's not obvious to me what property you are proving here. Might want
> to add a comment.
It's closely related with DAMON internal logic. Will add a reference to a
document for the internal logic and what I'm checking, as you suggested. Same
for other ambiguous test code fragments you pointed out below.
>
[...]
> > +
> > +static void damon_test_aggregate(struct kunit *test)
> > +{
> > + unsigned long pids[] = {1, 2, 3};
> > + unsigned long saddr[][3] = {{10, 20, 30}, {5, 42, 49}, {13, 33, 55} };
> > + unsigned long eaddr[][3] = {{15, 27, 40}, {31, 45, 55}, {23, 44, 66} };
> > + unsigned long accesses[][3] = {{42, 95, 84}, {10, 20, 30}, {0, 1, 2} };
> > + struct damon_task *t;
> > + struct damon_region *r;
> > + int it, ir;
> > + ssize_t sz, sr, sp;
> > +
> > + damon_set_pids(pids, 3);
> > +
> > + it = 0;
> > + damon_for_each_task(t) {
> > + for (ir = 0; ir < 3; ir++) {
> > + r = damon_new_region(saddr[it][ir], eaddr[it][ir]);
> > + r->nr_accesses = accesses[it][ir];
> > + damon_add_region_tail(r, t);
> > + }
> > + it++;
> > + }
> > + kdamond_flush_aggregated();
>
> I think this test case is also difficult to understand. I think you
> probably need at least a comment on what this test case does.
>
> > + it = 0;
> > + damon_for_each_task(t) {
> > + ir = 0;
> > + damon_for_each_region(r, t) {
> > + KUNIT_EXPECT_EQ(test, 0u, r->nr_accesses);
> > + ir++;
> > + }
> > + KUNIT_EXPECT_EQ(test, 3, ir);
> > + it++;
> > + }
> > + KUNIT_EXPECT_EQ(test, 3, it);
> > +
> > + sr = sizeof(r->vm_start) + sizeof(r->vm_end) + sizeof(r->nr_accesses);
> > + sp = sizeof(t->pid) + sizeof(unsigned int) + 3 * sr;
> > + sz = sizeof(struct timespec64) + sizeof(unsigned int) + 3 * sp;
> > + KUNIT_EXPECT_EQ(test, (unsigned int)sz, damon_rbuf_offset);
> > +
> > + damon_cleanup_global_state();
> > +}
> > +
[...]
> > +
> > +static void damon_test_update_two_gaps(struct kunit *test)
> > +{
>
> I think this test case is also difficult to understand. I think you
> probably need at least a comment on what this test case does.
>
> > + struct damon_task *t;
> > + struct damon_region *r, *prev = NULL;
> > + unsigned long regions[] = {10, 20, 20, 30,
> > + 50, 55, 55, 57, 57, 59,
> > + 70, 80, 80, 90, 90, 100}; /* 10-30, 50-59, 70-100 */
> > + struct region new_regions[3] = {
> > + (struct region){.start = 5, .end = 27},
> > + (struct region){.start = 45, .end = 55},
> > + (struct region){.start = 73, .end = 104} };
> > + int i;
> > + bool first_gap = true;
> > +
> > + t = damon_new_task(42);
> > + for (i = 0; i < ARRAY_SIZE(regions) / 2; i++) {
> > + r = damon_new_region(regions[i * 2], regions[i * 2 + 1]);
> > + damon_add_region_tail(r, t);
> > + }
> > + damon_add_task_tail(t);
> > +
> > + damon_apply_three_regions(t, new_regions);
> > +
> > + damon_for_each_region(r, t) {
> > + if (prev == NULL) {
> > + KUNIT_EXPECT_EQ(test, r->vm_start, 5ul);
> > + goto next;
> > + }
> > +
> > + if (prev->vm_end != r->vm_start && first_gap) {
> > + KUNIT_EXPECT_EQ(test, prev->vm_end, 27ul);
> > + KUNIT_EXPECT_EQ(test, r->vm_start, 45ul);
> > + first_gap = false;
> > + goto next;
> > + }
> > +
> > + if (prev->vm_end != r->vm_start && !first_gap) {
> > + KUNIT_EXPECT_EQ(test, prev->vm_end, 55ul);
> > + KUNIT_EXPECT_EQ(test, r->vm_start, 73ul);
> > + goto next;
> > + }
> > +
> > +next:
> > + prev = r;
> > + }
> > +
> > + damon_cleanup_global_state();
> > +}
> > +
> > +static void damon_test_update_two_gaps2(struct kunit *test)
> > +{
>
> Same here.
>
> > + struct damon_task *t;
> > + struct damon_region *r;
> > + /* 10-20-30, 50-55-57-59, 70-80-90-100 */
> > + unsigned long regions[] = {10, 20, 20, 30,
> > + 50, 55, 55, 57, 57, 59,
> > + 70, 80, 80, 90, 90, 100};
> > + struct region new_regions[3] = {
> > + (struct region){.start = 5, .end = 27},
> > + (struct region){.start = 56, .end = 57},
> > + (struct region){.start = 65, .end = 104} };
> > + /* expect 5-27, 56-57, 65-80-90-104 */
> > + unsigned long answers[] = {5, 20, 20, 27,
> > + 56, 57,
> > + 65, 80, 80, 90, 90, 104};
> > + int i;
> > +
> > + t = damon_new_task(42);
> > + for (i = 0; i < ARRAY_SIZE(regions) / 2; i++) {
> > + r = damon_new_region(regions[i * 2], regions[i * 2 + 1]);
> > + damon_add_region_tail(r, t);
> > + }
> > + damon_add_task_tail(t);
> > +
> > + damon_apply_three_regions(t, new_regions);
> > +
> > + for (i = 0; i < ARRAY_SIZE(answers) / 2; i++) {
> > + r = damon_nth_region_of(t, i);
> > + KUNIT_EXPECT_EQ(test, r->vm_start, answers[i * 2]);
> > + KUNIT_EXPECT_EQ(test, r->vm_end, answers[i++ * 2 + 1]);
> > + }
> > +
> > + damon_cleanup_global_state();
> > +}
> > +
> > +static void damon_test_update_two_gaps3(struct kunit *test)
> > +{
>
> Same here.
>
> > + struct damon_task *t;
> > + struct damon_region *r;
> > + /* 10-20-30, 50-55-57-59, 70-80-90-100 */
> > + unsigned long regions[] = {10, 20, 20, 30,
> > + 50, 55, 55, 57, 57, 59,
> > + 70, 80, 80, 90, 90, 100};
> > + struct region new_regions[3] = {
> > + (struct region){.start = 5, .end = 27},
> > + (struct region){.start = 61, .end = 63},
> > + (struct region){.start = 65, .end = 104} };
> > + /* expect 5-27, 56-57, 65-80-90-104 */
> > + unsigned long answers[] = {5, 20, 20, 27,
> > + 61, 63,
> > + 65, 80, 80, 90, 90, 104};
> > + int i;
> > +
> > + t = damon_new_task(42);
> > + for (i = 0; i < ARRAY_SIZE(regions) / 2; i++) {
> > + r = damon_new_region(regions[i * 2], regions[i * 2 + 1]);
> > + damon_add_region_tail(r, t);
> > + }
> > + damon_add_task_tail(t);
> > +
> > + damon_apply_three_regions(t, new_regions);
> > +
> > + for (i = 0; i < ARRAY_SIZE(answers) / 2; i++) {
> > + r = damon_nth_region_of(t, i);
> > + KUNIT_EXPECT_EQ(test, r->vm_start, answers[i * 2]);
> > + KUNIT_EXPECT_EQ(test, r->vm_end, answers[i++ * 2 + 1]);
> > + }
> > +
> > + damon_cleanup_global_state();
> > +}
> > +
> > +static void damon_test_update_two_gaps4(struct kunit *test)
> > +{
>
> Ditto.
>
> > + struct damon_task *t;
> > + struct damon_region *r;
> > + /* 10-20-30, 50-55-57-59, 70-80-90-100 */
> > + unsigned long regions[] = {10, 20, 20, 30,
> > + 50, 55, 55, 57, 57, 59,
> > + 70, 80, 80, 90, 90, 100};
> > + struct region new_regions[3] = {
> > + (struct region){.start = 5, .end = 7},
> > + (struct region){.start = 30, .end = 32},
> > + (struct region){.start = 65, .end = 68} };
> > + /* expect 5-27, 56-57, 65-80-90-104 */
> > + unsigned long answers[] = {5, 7, 30, 32, 65, 68};
> > + int i;
> > +
> > + t = damon_new_task(42);
> > + for (i = 0; i < ARRAY_SIZE(regions) / 2; i++) {
> > + r = damon_new_region(regions[i * 2], regions[i * 2 + 1]);
> > + damon_add_region_tail(r, t);
> > + }
> > + damon_add_task_tail(t);
> > +
> > + damon_apply_three_regions(t, new_regions);
> > +
> > + for (i = 0; i < ARRAY_SIZE(answers) / 2; i++) {
> > + r = damon_nth_region_of(t, i);
> > + KUNIT_EXPECT_EQ(test, r->vm_start, answers[i * 2]);
> > + KUNIT_EXPECT_EQ(test, r->vm_end, answers[i++ * 2 + 1]);
> > + }
> > +
> > + damon_cleanup_global_state();
> > +}
> > +
[...]
Will apply all of your suggestions, soon.
Thanks,
SeongJae Park