blob: 803e0318f2fea1c5cc19e036316c6d00fb407783 [file] [log] [blame] [edit]
#!/usr/bin/env python3
# SPDX-License-Identifier: GPL-2.0-only
# Copyright (C) 2024 ARM Ltd.
#
# Utility providing smaps-like output detailing transparent hugepage usage.
# For more info, run:
# ./thpmaps --help
#
# Requires numpy:
# pip3 install numpy
import argparse
import collections
import math
import os
import re
import resource
import shutil
import sys
import textwrap
import time
import numpy as np
with open('/sys/kernel/mm/transparent_hugepage/hpage_pmd_size') as f:
PAGE_SIZE = resource.getpagesize()
PAGE_SHIFT = int(math.log2(PAGE_SIZE))
PMD_SIZE = int(f.read())
PMD_ORDER = int(math.log2(PMD_SIZE / PAGE_SIZE))
def align_forward(v, a):
return (v + (a - 1)) & ~(a - 1)
def align_offset(v, a):
return v & (a - 1)
def kbnr(kb):
# Convert KB to number of pages.
return (kb << 10) >> PAGE_SHIFT
def nrkb(nr):
# Convert number of pages to KB.
return (nr << PAGE_SHIFT) >> 10
def odkb(order):
# Convert page order to KB.
return (PAGE_SIZE << order) >> 10
def cont_ranges_all(search, index):
# Given a list of arrays, find the ranges for which values are monotonically
# incrementing in all arrays. all arrays in search and index must be the
# same size.
sz = len(search[0])
r = np.full(sz, 2)
d = np.diff(search[0]) == 1
for dd in [np.diff(arr) == 1 for arr in search[1:]]:
d &= dd
r[1:] -= d
r[:-1] -= d
return [np.repeat(arr, r).reshape(-1, 2) for arr in index]
class ArgException(Exception):
pass
class FileIOException(Exception):
pass
class BinArrayFile:
# Base class used to read /proc/<pid>/pagemap and /proc/kpageflags into a
# numpy array. Use inherrited class in a with clause to ensure file is
# closed when it goes out of scope.
def __init__(self, filename, element_size):
self.element_size = element_size
self.filename = filename
self.fd = os.open(self.filename, os.O_RDONLY)
def cleanup(self):
os.close(self.fd)
def __enter__(self):
return self
def __exit__(self, exc_type, exc_val, exc_tb):
self.cleanup()
def _readin(self, offset, buffer):
length = os.preadv(self.fd, (buffer,), offset)
if len(buffer) != length:
raise FileIOException('error: {} failed to read {} bytes at {:x}'
.format(self.filename, len(buffer), offset))
def _toarray(self, buf):
assert(self.element_size == 8)
return np.frombuffer(buf, dtype=np.uint64)
def getv(self, vec):
vec *= self.element_size
offsets = vec[:, 0]
lengths = (np.diff(vec) + self.element_size).reshape(len(vec))
buf = bytearray(int(np.sum(lengths)))
view = memoryview(buf)
pos = 0
for offset, length in zip(offsets, lengths):
offset = int(offset)
length = int(length)
self._readin(offset, view[pos:pos+length])
pos += length
return self._toarray(buf)
def get(self, index, nr=1):
offset = index * self.element_size
length = nr * self.element_size
buf = bytearray(length)
self._readin(offset, buf)
return self._toarray(buf)
PM_PAGE_PRESENT = 1 << 63
PM_PFN_MASK = (1 << 55) - 1
class PageMap(BinArrayFile):
# Read ranges of a given pid's pagemap into a numpy array.
def __init__(self, pid='self'):
super().__init__(f'/proc/{pid}/pagemap', 8)
KPF_ANON = 1 << 12
KPF_COMPOUND_HEAD = 1 << 15
KPF_COMPOUND_TAIL = 1 << 16
KPF_THP = 1 << 22
class KPageFlags(BinArrayFile):
# Read ranges of /proc/kpageflags into a numpy array.
def __init__(self):
super().__init__(f'/proc/kpageflags', 8)
vma_all_stats = set([
"Size",
"Rss",
"Pss",
"Pss_Dirty",
"Shared_Clean",
"Shared_Dirty",
"Private_Clean",
"Private_Dirty",
"Referenced",
"Anonymous",
"KSM",
"LazyFree",
"AnonHugePages",
"ShmemPmdMapped",
"FilePmdMapped",
"Shared_Hugetlb",
"Private_Hugetlb",
"Swap",
"SwapPss",
"Locked",
])
vma_min_stats = set([
"Rss",
"Anonymous",
"AnonHugePages",
"ShmemPmdMapped",
"FilePmdMapped",
])
VMA = collections.namedtuple('VMA', [
'name',
'start',
'end',
'read',
'write',
'execute',
'private',
'pgoff',
'major',
'minor',
'inode',
'stats',
])
class VMAList:
# A container for VMAs, parsed from /proc/<pid>/smaps. Iterate over the
# instance to receive VMAs.
def __init__(self, pid='self', stats=[]):
self.vmas = []
with open(f'/proc/{pid}/smaps', 'r') as file:
for line in file:
elements = line.split()
if '-' in elements[0]:
start, end = map(lambda x: int(x, 16), elements[0].split('-'))
major, minor = map(lambda x: int(x, 16), elements[3].split(':'))
self.vmas.append(VMA(
name=elements[5] if len(elements) == 6 else '',
start=start,
end=end,
read=elements[1][0] == 'r',
write=elements[1][1] == 'w',
execute=elements[1][2] == 'x',
private=elements[1][3] == 'p',
pgoff=int(elements[2], 16),
major=major,
minor=minor,
inode=int(elements[4], 16),
stats={},
))
else:
param = elements[0][:-1]
if param in stats:
value = int(elements[1])
self.vmas[-1].stats[param] = {'type': None, 'value': value}
def __iter__(self):
yield from self.vmas
def thp_parse(vma, kpageflags, ranges, indexes, vfns, pfns, anons, heads):
# Given 4 same-sized arrays representing a range within a page table backed
# by THPs (vfns: virtual frame numbers, pfns: physical frame numbers, anons:
# True if page is anonymous, heads: True if page is head of a THP), return a
# dictionary of statistics describing the mapped THPs.
stats = {
'file': {
'partial': 0,
'aligned': [0] * (PMD_ORDER + 1),
'unaligned': [0] * (PMD_ORDER + 1),
},
'anon': {
'partial': 0,
'aligned': [0] * (PMD_ORDER + 1),
'unaligned': [0] * (PMD_ORDER + 1),
},
}
for rindex, rpfn in zip(ranges[0], ranges[2]):
index_next = int(rindex[0])
index_end = int(rindex[1]) + 1
pfn_end = int(rpfn[1]) + 1
folios = indexes[index_next:index_end][heads[index_next:index_end]]
# Account pages for any partially mapped THP at the front. In that case,
# the first page of the range is a tail.
nr = (int(folios[0]) if len(folios) else index_end) - index_next
stats['anon' if anons[index_next] else 'file']['partial'] += nr
# Account pages for any partially mapped THP at the back. In that case,
# the next page after the range is a tail.
if len(folios):
flags = int(kpageflags.get(pfn_end)[0])
if flags & KPF_COMPOUND_TAIL:
nr = index_end - int(folios[-1])
folios = folios[:-1]
index_end -= nr
stats['anon' if anons[index_end - 1] else 'file']['partial'] += nr
# Account fully mapped THPs in the middle of the range.
if len(folios):
folio_nrs = np.append(np.diff(folios), np.uint64(index_end - folios[-1]))
folio_orders = np.log2(folio_nrs).astype(np.uint64)
for index, order in zip(folios, folio_orders):
index = int(index)
order = int(order)
nr = 1 << order
vfn = int(vfns[index])
align = 'aligned' if align_forward(vfn, nr) == vfn else 'unaligned'
anon = 'anon' if anons[index] else 'file'
stats[anon][align][order] += nr
# Account PMD-mapped THPs spearately, so filter out of the stats. There is a
# race between acquiring the smaps stats and reading pagemap, where memory
# could be deallocated. So clamp to zero incase it would have gone negative.
anon_pmd_mapped = vma.stats['AnonHugePages']['value']
file_pmd_mapped = vma.stats['ShmemPmdMapped']['value'] + \
vma.stats['FilePmdMapped']['value']
stats['anon']['aligned'][PMD_ORDER] = max(0, stats['anon']['aligned'][PMD_ORDER] - kbnr(anon_pmd_mapped))
stats['file']['aligned'][PMD_ORDER] = max(0, stats['file']['aligned'][PMD_ORDER] - kbnr(file_pmd_mapped))
rstats = {
f"anon-thp-pmd-aligned-{odkb(PMD_ORDER)}kB": {'type': 'anon', 'value': anon_pmd_mapped},
f"file-thp-pmd-aligned-{odkb(PMD_ORDER)}kB": {'type': 'file', 'value': file_pmd_mapped},
}
def flatten_sub(type, subtype, stats):
param = f"{type}-thp-pte-{subtype}-{{}}kB"
for od, nr in enumerate(stats[2:], 2):
rstats[param.format(odkb(od))] = {'type': type, 'value': nrkb(nr)}
def flatten_type(type, stats):
flatten_sub(type, 'aligned', stats['aligned'])
flatten_sub(type, 'unaligned', stats['unaligned'])
rstats[f"{type}-thp-pte-partial"] = {'type': type, 'value': nrkb(stats['partial'])}
flatten_type('anon', stats['anon'])
flatten_type('file', stats['file'])
return rstats
def cont_parse(vma, order, ranges, anons, heads):
# Given 4 same-sized arrays representing a range within a page table backed
# by THPs (vfns: virtual frame numbers, pfns: physical frame numbers, anons:
# True if page is anonymous, heads: True if page is head of a THP), return a
# dictionary of statistics describing the contiguous blocks.
nr_cont = 1 << order
nr_anon = 0
nr_file = 0
for rindex, rvfn, rpfn in zip(*ranges):
index_next = int(rindex[0])
index_end = int(rindex[1]) + 1
vfn_start = int(rvfn[0])
pfn_start = int(rpfn[0])
if align_offset(pfn_start, nr_cont) != align_offset(vfn_start, nr_cont):
continue
off = align_forward(vfn_start, nr_cont) - vfn_start
index_next += off
while index_next + nr_cont <= index_end:
folio_boundary = heads[index_next+1:index_next+nr_cont].any()
if not folio_boundary:
if anons[index_next]:
nr_anon += nr_cont
else:
nr_file += nr_cont
index_next += nr_cont
# Account blocks that are PMD-mapped spearately, so filter out of the stats.
# There is a race between acquiring the smaps stats and reading pagemap,
# where memory could be deallocated. So clamp to zero incase it would have
# gone negative.
anon_pmd_mapped = vma.stats['AnonHugePages']['value']
file_pmd_mapped = vma.stats['ShmemPmdMapped']['value'] + \
vma.stats['FilePmdMapped']['value']
nr_anon = max(0, nr_anon - kbnr(anon_pmd_mapped))
nr_file = max(0, nr_file - kbnr(file_pmd_mapped))
rstats = {
f"anon-cont-pmd-aligned-{nrkb(nr_cont)}kB": {'type': 'anon', 'value': anon_pmd_mapped},
f"file-cont-pmd-aligned-{nrkb(nr_cont)}kB": {'type': 'file', 'value': file_pmd_mapped},
}
rstats[f"anon-cont-pte-aligned-{nrkb(nr_cont)}kB"] = {'type': 'anon', 'value': nrkb(nr_anon)}
rstats[f"file-cont-pte-aligned-{nrkb(nr_cont)}kB"] = {'type': 'file', 'value': nrkb(nr_file)}
return rstats
def vma_print(vma, pid):
# Prints a VMA instance in a format similar to smaps. The main difference is
# that the pid is included as the first value.
print("{:010d}: {:016x}-{:016x} {}{}{}{} {:08x} {:02x}:{:02x} {:08x} {}"
.format(
pid, vma.start, vma.end,
'r' if vma.read else '-', 'w' if vma.write else '-',
'x' if vma.execute else '-', 'p' if vma.private else 's',
vma.pgoff, vma.major, vma.minor, vma.inode, vma.name
))
def stats_print(stats, tot_anon, tot_file, inc_empty):
# Print a statistics dictionary.
label_field = 32
for label, stat in stats.items():
type = stat['type']
value = stat['value']
if value or inc_empty:
pad = max(0, label_field - len(label) - 1)
if type == 'anon' and tot_anon > 0:
percent = f' ({value / tot_anon:3.0%})'
elif type == 'file' and tot_file > 0:
percent = f' ({value / tot_file:3.0%})'
else:
percent = ''
print(f"{label}:{' ' * pad}{value:8} kB{percent}")
def vma_parse(vma, pagemap, kpageflags, contorders):
# Generate thp and cont statistics for a single VMA.
start = vma.start >> PAGE_SHIFT
end = vma.end >> PAGE_SHIFT
pmes = pagemap.get(start, end - start)
present = pmes & PM_PAGE_PRESENT != 0
pfns = pmes & PM_PFN_MASK
pfns = pfns[present]
vfns = np.arange(start, end, dtype=np.uint64)
vfns = vfns[present]
pfn_vec = cont_ranges_all([pfns], [pfns])[0]
flags = kpageflags.getv(pfn_vec)
anons = flags & KPF_ANON != 0
heads = flags & KPF_COMPOUND_HEAD != 0
thps = flags & KPF_THP != 0
vfns = vfns[thps]
pfns = pfns[thps]
anons = anons[thps]
heads = heads[thps]
indexes = np.arange(len(vfns), dtype=np.uint64)
ranges = cont_ranges_all([vfns, pfns], [indexes, vfns, pfns])
thpstats = thp_parse(vma, kpageflags, ranges, indexes, vfns, pfns, anons, heads)
contstats = [cont_parse(vma, order, ranges, anons, heads) for order in contorders]
tot_anon = vma.stats['Anonymous']['value']
tot_file = vma.stats['Rss']['value'] - tot_anon
return {
**thpstats,
**{k: v for s in contstats for k, v in s.items()}
}, tot_anon, tot_file
def do_main(args):
pids = set()
rollup = {}
rollup_anon = 0
rollup_file = 0
if args.cgroup:
strict = False
for walk_info in os.walk(args.cgroup):
cgroup = walk_info[0]
with open(f'{cgroup}/cgroup.procs') as pidfile:
for line in pidfile.readlines():
pids.add(int(line.strip()))
elif args.pid:
strict = True
pids = pids.union(args.pid)
else:
strict = False
for pid in os.listdir('/proc'):
if pid.isdigit():
pids.add(int(pid))
if not args.rollup:
print(" PID START END PROT OFFSET DEV INODE OBJECT")
for pid in pids:
try:
with PageMap(pid) as pagemap:
with KPageFlags() as kpageflags:
for vma in VMAList(pid, vma_all_stats if args.inc_smaps else vma_min_stats):
if (vma.read or vma.write or vma.execute) and vma.stats['Rss']['value'] > 0:
stats, vma_anon, vma_file = vma_parse(vma, pagemap, kpageflags, args.cont)
else:
stats = {}
vma_anon = 0
vma_file = 0
if args.inc_smaps:
stats = {**vma.stats, **stats}
if args.rollup:
for k, v in stats.items():
if k in rollup:
assert(rollup[k]['type'] == v['type'])
rollup[k]['value'] += v['value']
else:
rollup[k] = v
rollup_anon += vma_anon
rollup_file += vma_file
else:
vma_print(vma, pid)
stats_print(stats, vma_anon, vma_file, args.inc_empty)
except (FileNotFoundError, ProcessLookupError, FileIOException):
if strict:
raise
if args.rollup:
stats_print(rollup, rollup_anon, rollup_file, args.inc_empty)
def main():
docs_width = shutil.get_terminal_size().columns
docs_width -= 2
docs_width = min(80, docs_width)
def format(string):
text = re.sub(r'\s+', ' ', string)
text = re.sub(r'\s*\\n\s*', '\n', text)
paras = text.split('\n')
paras = [textwrap.fill(p, width=docs_width) for p in paras]
return '\n'.join(paras)
def formatter(prog):
return argparse.RawDescriptionHelpFormatter(prog, width=docs_width)
def size2order(human):
units = {
"K": 2**10, "M": 2**20, "G": 2**30,
"k": 2**10, "m": 2**20, "g": 2**30,
}
unit = 1
if human[-1] in units:
unit = units[human[-1]]
human = human[:-1]
try:
size = int(human)
except ValueError:
raise ArgException('error: --cont value must be integer size with optional KMG unit')
size *= unit
order = int(math.log2(size / PAGE_SIZE))
if order < 1:
raise ArgException('error: --cont value must be size of at least 2 pages')
if (1 << order) * PAGE_SIZE != size:
raise ArgException('error: --cont value must be size of power-of-2 pages')
if order > PMD_ORDER:
raise ArgException('error: --cont value must be less than or equal to PMD order')
return order
parser = argparse.ArgumentParser(formatter_class=formatter,
description=format("""Prints information about how transparent huge
pages are mapped, either system-wide, or for a specified
process or cgroup.\\n
\\n
When run with --pid, the user explicitly specifies the set
of pids to scan. e.g. "--pid 10 [--pid 134 ...]". When run
with --cgroup, the user passes either a v1 or v2 cgroup and
all pids that belong to the cgroup subtree are scanned. When
run with neither --pid nor --cgroup, the full set of pids on
the system is gathered from /proc and scanned as if the user
had provided "--pid 1 --pid 2 ...".\\n
\\n
A default set of statistics is always generated for THP
mappings. However, it is also possible to generate
additional statistics for "contiguous block mappings" where
the block size is user-defined.\\n
\\n
Statistics are maintained independently for anonymous and
file-backed (pagecache) memory and are shown both in kB and
as a percentage of either total anonymous or total
file-backed memory as appropriate.\\n
\\n
THP Statistics\\n
--------------\\n
\\n
Statistics are always generated for fully- and
contiguously-mapped THPs whose mapping address is aligned to
their size, for each <size> supported by the system.
Separate counters describe THPs mapped by PTE vs those
mapped by PMD. (Although note a THP can only be mapped by
PMD if it is PMD-sized):\\n
\\n
- anon-thp-pte-aligned-<size>kB\\n
- file-thp-pte-aligned-<size>kB\\n
- anon-thp-pmd-aligned-<size>kB\\n
- file-thp-pmd-aligned-<size>kB\\n
\\n
Similarly, statistics are always generated for fully- and
contiguously-mapped THPs whose mapping address is *not*
aligned to their size, for each <size> supported by the
system. Due to the unaligned mapping, it is impossible to
map by PMD, so there are only PTE counters for this case:\\n
\\n
- anon-thp-pte-unaligned-<size>kB\\n
- file-thp-pte-unaligned-<size>kB\\n
\\n
Statistics are also always generated for mapped pages that
belong to a THP but where the is THP is *not* fully- and
contiguously- mapped. These "partial" mappings are all
counted in the same counter regardless of the size of the
THP that is partially mapped:\\n
\\n
- anon-thp-pte-partial\\n
- file-thp-pte-partial\\n
\\n
Contiguous Block Statistics\\n
---------------------------\\n
\\n
An optional, additional set of statistics is generated for
every contiguous block size specified with `--cont <size>`.
These statistics show how much memory is mapped in
contiguous blocks of <size> and also aligned to <size>. A
given contiguous block must all belong to the same THP, but
there is no requirement for it to be the *whole* THP.
Separate counters describe contiguous blocks mapped by PTE
vs those mapped by PMD:\\n
\\n
- anon-cont-pte-aligned-<size>kB\\n
- file-cont-pte-aligned-<size>kB\\n
- anon-cont-pmd-aligned-<size>kB\\n
- file-cont-pmd-aligned-<size>kB\\n
\\n
As an example, if monitoring 64K contiguous blocks (--cont
64K), there are a number of sources that could provide such
blocks: a fully- and contiguously-mapped 64K THP that is
aligned to a 64K boundary would provide 1 block. A fully-
and contiguously-mapped 128K THP that is aligned to at least
a 64K boundary would provide 2 blocks. Or a 128K THP that
maps its first 100K, but contiguously and starting at a 64K
boundary would provide 1 block. A fully- and
contiguously-mapped 2M THP would provide 32 blocks. There
are many other possible permutations.\\n"""),
epilog=format("""Requires root privilege to access pagemap and
kpageflags."""))
group = parser.add_mutually_exclusive_group(required=False)
group.add_argument('--pid',
metavar='pid', required=False, type=int, default=[], action='append',
help="""Process id of the target process. Maybe issued multiple times to
scan multiple processes. --pid and --cgroup are mutually exclusive.
If neither are provided, all processes are scanned to provide
system-wide information.""")
group.add_argument('--cgroup',
metavar='path', required=False,
help="""Path to the target cgroup in sysfs. Iterates over every pid in
the cgroup and its children. --pid and --cgroup are mutually
exclusive. If neither are provided, all processes are scanned to
provide system-wide information.""")
parser.add_argument('--rollup',
required=False, default=False, action='store_true',
help="""Sum the per-vma statistics to provide a summary over the whole
system, process or cgroup.""")
parser.add_argument('--cont',
metavar='size[KMG]', required=False, default=[], action='append',
help="""Adds stats for memory that is mapped in contiguous blocks of
<size> and also aligned to <size>. May be issued multiple times to
track multiple sized blocks. Useful to infer e.g. arm64 contpte and
hpa mappings. Size must be a power-of-2 number of pages.""")
parser.add_argument('--inc-smaps',
required=False, default=False, action='store_true',
help="""Include all numerical, additive /proc/<pid>/smaps stats in the
output.""")
parser.add_argument('--inc-empty',
required=False, default=False, action='store_true',
help="""Show all statistics including those whose value is 0.""")
parser.add_argument('--periodic',
metavar='sleep_ms', required=False, type=int,
help="""Run in a loop, polling every sleep_ms milliseconds.""")
args = parser.parse_args()
try:
args.cont = [size2order(cont) for cont in args.cont]
except ArgException as e:
parser.print_usage()
raise
if args.periodic:
while True:
do_main(args)
print()
time.sleep(args.periodic / 1000)
else:
do_main(args)
if __name__ == "__main__":
try:
main()
except Exception as e:
prog = os.path.basename(sys.argv[0])
print(f'{prog}: {e}')
exit(1)