> On Mon, Oct 16, 2017 at 3:26 PM, <kan.li...@intel.com> wrote:
> > From: Kan Liang <kan.li...@intel.com>
> >
> > There could be different types of memory in the system. E.g normal
> > System Memory, Persistent Memory. To understand how the workload
> maps to
> > those memories, it's important to know the I/O statistics on different
> > type of memorys. Perf can collect address maps with physical addresses,
> > but those are raw data. It still needs extra work to resolve the
> > physical addresses.
> > Providing a script to facilitate the physical addresses resolving and
> > I/O statistics.
> >
> > Profiling with mem-loads and mem-stores if they are available.
> > Looking up the physical address samples in /proc/iomem
> > Providing memory type summary
> >
> > Here is an example
> > #perf script record mem-phys-addr -- pmem_test_kernel
> > [ perf record: Woken up 32 times to write data ]
> > [ perf record: Captured and wrote 7.797 MB perf.data (101995 samples) ]
> > #perf script report mem-phys-addr
> > Memory type summary
> >
> > Event: mem-loads
> > Memory type count percentage
> > ---------------------------------------- ----------- -----------
> > Persistent Memory 43740 60.6%
> > System RAM 27179 37.7%
> > N/A 1268 1.8%
> >
> > Event: mem-stores
> > Memory type count percentage
> > ---------------------------------------- ----------- -----------
> > System RAM 24508 82.2%
> > N/A 5140 17.2%
> > Persistent Memory 160 0.5%
> >
> > Signed-off-by: Kan Liang <kan.li...@intel.com>
> > ---
> > tools/perf/scripts/python/bin/mem-phys-addr-record | 30 ++++++
> > tools/perf/scripts/python/bin/mem-phys-addr-report | 3 +
> > tools/perf/scripts/python/mem-phys-addr.py | 109
> +++++++++++++++++++++
> > .../util/scripting-engines/trace-event-python.c | 2 +
> > 4 files changed, 144 insertions(+)
> > create mode 100644 tools/perf/scripts/python/bin/mem-phys-addr-
> record
> > create mode 100644 tools/perf/scripts/python/bin/mem-phys-addr-report
> > create mode 100644 tools/perf/scripts/python/mem-phys-addr.py
> >
> > diff --git a/tools/perf/scripts/python/bin/mem-phys-addr-record
> b/tools/perf/scripts/python/bin/mem-phys-addr-record
> > new file mode 100644
> > index 0000000..395b256
> > --- /dev/null
> > +++ b/tools/perf/scripts/python/bin/mem-phys-addr-record
> > @@ -0,0 +1,30 @@
> > +#!/bin/bash
> > +
> > +#
> > +# Profiling physical memory accesses
> > +#
> > +
> > +load=`perf list pmu | grep mem-loads`
> > +store=`perf list pmu | grep mem-stores`
> > +if [ -z "$load" ] && [ -z "$store" ] ; then
> > + echo "There is no mem-loads or mem-stores support"
> > + exit 1
> > +fi
> > +
> > +arg="-e"
> > +if [ ! -z "$store" ] ; then
> > + arg="$arg mem-stores:P"
> > +fi
> > +
> > +if [ ! -z "$load" ] ; then
> > + if [ ! -z "$store" ] ; then
> > + arg="$arg,mem-loads:P"
> > + else
> > + arg="$arg mem-loads:P"
> > + fi
> > + arg="$arg -W"
> > +fi
> > +
> > +arg="$arg -d --phys-data"
> > +
> > +perf record $arg $@
> > diff --git a/tools/perf/scripts/python/bin/mem-phys-addr-report
> b/tools/perf/scripts/python/bin/mem-phys-addr-report
> > new file mode 100644
> > index 0000000..3f2b847
> > --- /dev/null
> > +++ b/tools/perf/scripts/python/bin/mem-phys-addr-report
> > @@ -0,0 +1,3 @@
> > +#!/bin/bash
> > +# description: resolve physical address samples
> > +perf script $@ -s "$PERF_EXEC_PATH"/scripts/python/mem-phys-addr.py
> > diff --git a/tools/perf/scripts/python/mem-phys-addr.py
> b/tools/perf/scripts/python/mem-phys-addr.py
> > new file mode 100644
> > index 0000000..73b3a63
> > --- /dev/null
> > +++ b/tools/perf/scripts/python/mem-phys-addr.py
> > @@ -0,0 +1,109 @@
> > +# mem-phys-addr.py: Resolve physical address samples
> > +# Copyright (c) 2017, Intel Corporation.
> > +#
> > +# This program is free software; you can redistribute it and/or modify it
> > +# under the terms and conditions of the GNU General Public License,
> > +# version 2, as published by the Free Software Foundation.
> > +#
> > +# This program is distributed in the hope it will be useful, but WITHOUT
> > +# ANY WARRANTY; without even the implied warranty of
> MERCHANTABILITY or
> > +# FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
> License for
> > +# more details.
> > +
> > +from __future__ import division
> > +import os
> > +import sys
> > +import struct
> > +import re
> > +import bisect
> > +import collections
> > +
> > +sys.path.append(os.environ['PERF_EXEC_PATH'] + \
> > + '/scripts/python/Perf-Trace-Util/lib/Perf/Trace')
> > +
> > +system_ram = []
> > +pmem = []
> > +f = None
> > +load_event = ('mem-loads', '0x1cd')
> > +store_event = ('mem-stores', '0x82d0');
>
> I don't like the fact that you are mixing DLA and Load Latency.
> The two mechanism do not operate the same way and any attempt
> at comparing the loads and stores lead to misinterpretations.
>
OK. I will only keep "-d --phys-data" options as default.
For the event, is only mem-loads good enough as default event?
Or should we just let the user fill up the event?
Thanks,
Kan
> > +load_mem_type_cnt = collections.Counter()
> > +store_mem_type_cnt = collections.Counter()
> > +
> > +def parse_iomem():
> > + global f
> > + f = open('/proc/iomem', 'r')
> > + for i, j in enumerate(f):
> > + m = re.split('-|:',j,2)
> > + if m[2].strip() == 'System RAM':
> > + system_ram.append(long(m[0], 16))
> > + system_ram.append(long(m[1], 16))
> > + if m[2].strip() == 'Persistent Memory':
> > + pmem.append(long(m[0], 16))
> > + pmem.append(long(m[1], 16))
> > +
> > +def print_memory_type():
> > + print "Memory type summary\n"
> > + print "Event: mem-loads"
> > + print "%-40s %10s %10s\n" % ("Memory type", "count",
> "percentage"),
> > + print "%-40s %10s %10s\n" %
> > ("----------------------------------------", \
> > + "-----------", "-----------"),
> > + total = sum(load_mem_type_cnt.values())
> > + for mem_type, count in sorted(load_mem_type_cnt.most_common(),
> \
> > + key = lambda(k, v): (v, k), reverse
> > = True):
> > + print "%-40s %10d %10.1f%%\n" % (mem_type, count, 100 *
> count / total),
> > + print "\n\n"
> > + print "Event: mem-stores"
> > + print "%-40s %10s %10s\n" % ("Memory type", "count",
> "percentage"),
> > + print "%-40s %10s %10s\n" %
> > ("----------------------------------------", \
> > + "-----------", "-----------"),
> > + total = sum(store_mem_type_cnt.values())
> > + for mem_type, count in sorted(store_mem_type_cnt.most_common(),
> \
> > + key = lambda(k, v): (v, k), reverse
> > = True):
> > + print "%-40s %10d %10.1f%%\n" % (mem_type, count, 100 *
> count / total),
> > +
> > +def trace_begin():
> > + parse_iomem()
> > +
> > +def trace_end():
> > + print_memory_type()
> > + f.close()
> > +
> > +def is_system_ram(phys_addr):
> > + #/proc/iomem is sorted
> > + position = bisect.bisect(system_ram, phys_addr)
> > + if position % 2 == 0:
> > + return False
> > + return True
> > +
> > +def is_persistent_mem(phys_addr):
> > + position = bisect.bisect(pmem, phys_addr)
> > + if position % 2 == 0:
> > + return False
> > + return True
> > +
> > +def find_memory_type(phys_addr):
> > + if phys_addr == 0:
> > + return "N/A"
> > + if is_system_ram(phys_addr):
> > + return "System RAM"
> > +
> > + if is_persistent_mem(phys_addr):
> > + return "Persistent Memory"
> > +
> > + #slow path, search all
> > + f.seek(0, 0)
> > + for j in f:
> > + m = re.split('-|:',j,2)
> > + if long(m[0], 16) <= phys_addr <= long(m[1], 16):
> > + return m[2]
> > + return "N/A"
> > +
> > +def process_event(param_dict):
> > + name = param_dict["ev_name"]
> > + sample = param_dict["sample"]
> > + phys_addr = sample["phys_addr"]
> > +
> > + if any(x in name for x in load_event):
> > + load_mem_type_cnt[find_memory_type(phys_addr)] += 1
> > + if any(x in name for x in store_event):
> > + store_mem_type_cnt[find_memory_type(phys_addr)] += 1
> > diff --git a/tools/perf/util/scripting-engines/trace-event-python.c
> b/tools/perf/util/scripting-engines/trace-event-python.c
> > index c7187f0..8cd6317 100644
> > --- a/tools/perf/util/scripting-engines/trace-event-python.c
> > +++ b/tools/perf/util/scripting-engines/trace-event-python.c
> > @@ -500,6 +500,8 @@ static PyObject *get_perf_sample_dict(struct
> perf_sample *sample,
> > PyLong_FromUnsignedLongLong(sample->time));
> > pydict_set_item_string_decref(dict_sample, "period",
> > PyLong_FromUnsignedLongLong(sample->period));
> > + pydict_set_item_string_decref(dict_sample, "phys_addr",
> > + PyLong_FromUnsignedLongLong(sample->phys_addr));
> > set_sample_read_in_dict(dict_sample, sample, evsel);
> > pydict_set_item_string_decref(dict, "sample", dict_sample);
> >
> > --
> > 2.7.4
> >
