src/python/m5/stats/__init__.py - public/gem5 - Git at Google

 # Copyright (c) 2017-2020 ARM Limited
 # All rights reserved.
 #
 # The license below extends only to copyright in the software and shall
 # not be construed as granting a license to any other intellectual
 # property including but not limited to intellectual property relating
 # to a hardware implementation of the functionality of the software
 # licensed hereunder.  You may use the software subject to the license
 # terms below provided that you ensure that this notice is replicated
 # unmodified and in its entirety in all distributions of the software,
 # modified or unmodified, in source code or in binary form.
 #
 # Copyright (c) 2007 The Regents of The University of Michigan
 # Copyright (c) 2010 The Hewlett-Packard Development Company
 # All rights reserved.
 #
 # Redistribution and use in source and binary forms, with or without
 # modification, are permitted provided that the following conditions are
 # met: redistributions of source code must retain the above copyright
 # notice, this list of conditions and the following disclaimer;
 # redistributions in binary form must reproduce the above copyright
 # notice, this list of conditions and the following disclaimer in the
 # documentation and/or other materials provided with the distribution;
 # neither the name of the copyright holders nor the names of its
 # contributors may be used to endorse or promote products derived from
 # this software without specific prior written permission.
 #
 # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
 # "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
 # LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
 # A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
 # OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
 # SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
 # LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
 # DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
 # THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
 # (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
 # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

 import m5

 import _m5.stats
 from m5.objects import Root
 from m5.params import isNullPointer
 from .gem5stats import JsonOutputVistor
 from m5.util import attrdict, fatal

 # Stat exports
 from _m5.stats import schedStatEvent as schedEvent
 from _m5.stats import periodicStatDump

 outputList = []

 # Dictionary of stat visitor factories populated by the _url_factory
 # visitor.
 factories = { }

 # List of all factories. Contains tuples of (factory, schemes,
 # enabled).
 all_factories = []

 def _url_factory(schemes, enable=True):
     """Wrap a plain Python function with URL parsing helpers

     Wrap a plain Python function f(fn, **kwargs) to expect a URL that
     has been split using urlparse.urlsplit. First positional argument
     is assumed to be a filename, this is created as the concatenation
     of the netloc (~hostname) and path in the parsed URL. Keyword
     arguments are derived from the query values in the URL.

     Arguments:
         schemes: A list of URL schemes to use for this function.

     Keyword arguments:
         enable: Enable/disable this factory. Typically used when the
                 presence of a function depends on some runtime property.

     For example:
         wrapped_f(urlparse.urlsplit("text://stats.txt?desc=False")) ->
         f("stats.txt", desc=False)

     """

     from functools import wraps

     def decorator(func):
         @wraps(func)
         def wrapper(url):
             try:
                 from urllib.parse import parse_qs
             except ImportError:
                 # Python 2 fallback
                 from urlparse import parse_qs
             from ast import literal_eval

             qs = parse_qs(url.query, keep_blank_values=True)

             # parse_qs returns a list of values for each parameter. Only
             # use the last value since kwargs don't allow multiple values
             # per parameter. Use literal_eval to transform string param
             # values into proper Python types.
             def parse_value(key, values):
                 if len(values) == 0 or (len(values) == 1 and not values[0]):
                     fatal("%s: '%s' doesn't have a value." % (
                         url.geturl(), key))
                 elif len(values) > 1:
                     fatal("%s: '%s' has multiple values." % (
                         url.geturl(), key))
                 else:
                     try:
                         return key, literal_eval(values[0])
                     except ValueError:
                         fatal("%s: %s isn't a valid Python literal" \
                               % (url.geturl(), values[0]))

             kwargs = dict([ parse_value(k, v) for k, v in qs.items() ])

             try:
                 return func("%s%s" % (url.netloc, url.path), **kwargs)
             except TypeError:
                 fatal("Illegal stat visitor parameter specified")

         all_factories.append((wrapper, schemes, enable))
         for scheme in schemes:
             assert scheme not in factories
             factories[scheme] = wrapper if enable else None
         return wrapper

     return decorator

 @_url_factory([ None, "", "text", "file", ])
 def _textFactory(fn, desc=True, spaces=True):
     """Output stats in text format.

     Text stat files contain one stat per line with an optional
     description. The description is enabled by default, but can be
     disabled by setting the desc parameter to False.

     Parameters:
       * desc (bool): Output stat descriptions (default: True)
       * spaces (bool): Output alignment spaces (default: True)

     Example:
       text://stats.txt?desc=False;spaces=False

     """

     return _m5.stats.initText(fn, desc, spaces)

 @_url_factory([ "h5", ], enable=hasattr(_m5.stats, "initHDF5"))
 def _hdf5Factory(fn, chunking=10, desc=True, formulas=True):
     """Output stats in HDF5 format.

     The HDF5 file format is a structured binary file format. It has
     the multiple benefits over traditional text stat files:

       * Efficient storage of time series (multiple stat dumps)
       * Fast lookup of stats
       * Plenty of existing tooling (e.g., Python libraries and graphical
         viewers)
       * File format can be used to store frame buffers together with
         normal stats.

     There are some drawbacks compared to the default text format:
       * Large startup cost (single stat dump larger than text equivalent)
       * Stat dumps are slower than text


     Known limitations:
       * Distributions and histograms currently unsupported.
       * No support for forking.


     Parameters:
       * chunking (unsigned): Number of time steps to pre-allocate (default: 10)
       * desc (bool): Output stat descriptions (default: True)
       * formulas (bool): Output derived stats (default: True)

     Example:
       h5://stats.h5?desc=False;chunking=100;formulas=False

     """

     return _m5.stats.initHDF5(fn, chunking, desc, formulas)

 @_url_factory(["json"])
 def _jsonFactory(fn):
     """Output stats in JSON format.

     Example:
       json://stats.json

     """

     return JsonOutputVistor(fn)

 def addStatVisitor(url):
     """Add a stat visitor specified using a URL string

     Stat visitors are specified using URLs on the following format:
     format://path[?param=value[;param=value]]

     The available formats are listed in the factories list. Factories
     are called with the path as the first positional parameter and the
     parameters are keyword arguments. Parameter values must be valid
     Python literals.

     """

     try:
         from urllib.parse import urlsplit
     except ImportError:
         # Python 2 fallback
         from urlparse import urlsplit

     parsed = urlsplit(url)

     try:
         factory = factories[parsed.scheme]
     except KeyError:
         fatal("Illegal stat file type '%s' specified." % parsed.scheme)

     if factory is None:
         fatal("Stat type '%s' disabled at compile time" % parsed.scheme)

     outputList.append(factory(parsed))

 def printStatVisitorTypes():
     """List available stat visitors and their documentation"""

     import inspect

     def print_doc(doc):
         for line in doc.splitlines():
             print("| %s" % line)
         print()

     enabled_visitors = [ x for x in all_factories if x[2] ]
     for factory, schemes, _ in enabled_visitors:
         print("%s:" % ", ".join(filter(lambda x: x is not None, schemes)))

         # Try to extract the factory doc string
         print_doc(inspect.getdoc(factory))

 def initSimStats():
     _m5.stats.initSimStats()
     _m5.stats.registerPythonStatsHandlers()

 def _visit_groups(visitor, root=None):
     if root is None:
         root = Root.getInstance()
     for group in root.getStatGroups().values():
         visitor(group)
         _visit_groups(visitor, root=group)

 def _visit_stats(visitor, root=None):
     def for_each_stat(g):
         for stat in g.getStats():
             visitor(g, stat)
     _visit_groups(for_each_stat, root=root)

 def _bindStatHierarchy(root):
     def _bind_obj(name, obj):
         if isNullPointer(obj):
             return
         if m5.SimObject.isSimObjectVector(obj):
             if len(obj) == 1:
                 _bind_obj(name, obj[0])
             else:
                 for idx, obj in enumerate(obj):
                     _bind_obj("{}{}".format(name, idx), obj)
         else:
             # We need this check because not all obj.getCCObject() is an
             # instance of Stat::Group. For example, sc_core::sc_module, the C++
             # class of SystemC_ScModule, is not a subclass of Stat::Group. So
             # it will cause a type error if obj is a SystemC_ScModule when
             # calling addStatGroup().
             if isinstance(obj.getCCObject(), _m5.stats.Group):
                 parent = root
                 while parent:
                     if hasattr(parent, 'addStatGroup'):
                         parent.addStatGroup(name, obj.getCCObject())
                         break
                     parent = parent.get_parent();

             _bindStatHierarchy(obj)

     for name, obj in root._children.items():
         _bind_obj(name, obj)

 names = []
 stats_dict = {}
 stats_list = []
 def enable():
     '''Enable the statistics package.  Before the statistics package is
     enabled, all statistics must be created and initialized and once
     the package is enabled, no more statistics can be created.'''

     def check_stat(group, stat):
         if not stat.check() or not stat.baseCheck():
             fatal("statistic '%s' (%d) was not properly initialized " \
                   "by a regStats() function\n", stat.name, stat.id)

         if not (stat.flags & flags.display):
             stat.name = "__Stat%06d" % stat.id


     # Legacy stat
     global stats_list
     stats_list = list(_m5.stats.statsList())

     for stat in stats_list:
         check_stat(None, stat)

     stats_list.sort(key=lambda s: s.name.split('.'))
     for stat in stats_list:
         stats_dict[stat.name] = stat
         stat.enable()


     # New stats
     _visit_stats(check_stat)
     _visit_stats(lambda g, s: s.enable())

     _m5.stats.enable();

 def prepare():
     '''Prepare all stats for data access.  This must be done before
     dumping and serialization.'''

     # Legacy stats
     for stat in stats_list:
         stat.prepare()

     # New stats
     _visit_stats(lambda g, s: s.prepare())

 def _dump_to_visitor(visitor, roots=None):
     # New stats
     def dump_group(group):
         for stat in group.getStats():
             stat.visit(visitor)
         for n, g in group.getStatGroups().items():
             visitor.beginGroup(n)
             dump_group(g)
             visitor.endGroup()

     if roots:
         # New stats from selected subroots.
         for root in roots:
             for p in root.path_list():
                 visitor.beginGroup(p)
             dump_group(root)
             for p in reversed(root.path_list()):
                 visitor.endGroup()
     else:
         # New stats starting from root.
         dump_group(Root.getInstance())

         # Legacy stats
         for stat in stats_list:
             stat.visit(visitor)

 lastDump = 0
 # List[SimObject].
 global_dump_roots = []

 def dump(roots=None):
     '''Dump all statistics data to the registered outputs'''

     all_roots = []
     if roots is not None:
         all_roots.extend(roots)
     global global_dump_roots
     all_roots.extend(global_dump_roots)

     now = m5.curTick()
     global lastDump
     assert lastDump <= now
     new_dump = lastDump != now
     lastDump = now

     # Don't allow multiple global stat dumps in the same tick. It's
     # still possible to dump a multiple sub-trees.
     if not new_dump and not all_roots:
         return

     # Only prepare stats the first time we dump them in the same tick.
     if new_dump:
         _m5.stats.processDumpQueue()
         # Notify new-style stats group that we are about to dump stats.
         sim_root = Root.getInstance()
         if sim_root:
             sim_root.preDumpStats();
         prepare()

     for output in outputList:
         if isinstance(output, JsonOutputVistor):
             if not all_roots:
                 output.dump(Root.getInstance())
             else:
                 output.dump(all_roots)
         else:
             if output.valid():
                 output.begin()
                 _dump_to_visitor(output, roots=all_roots)
                 output.end()

 def reset():
     '''Reset all statistics to the base state'''

     # call reset stats on all SimObjects
     root = Root.getInstance()
     if root:
         root.resetStats()

     # call any other registered legacy stats reset callbacks
     for stat in stats_list:
         stat.reset()

     _m5.stats.processResetQueue()

 flags = attrdict({
     'none'    : 0x0000,
     'init'    : 0x0001,
     'display' : 0x0002,
     'total'   : 0x0010,
     'pdf'     : 0x0020,
     'cdf'     : 0x0040,
     'dist'    : 0x0080,
     'nozero'  : 0x0100,
     'nonan'   : 0x0200,
 })
	# Copyright (c) 2017-2020 ARM Limited
	# All rights reserved.
	#
	# The license below extends only to copyright in the software and shall
	# not be construed as granting a license to any other intellectual
	# property including but not limited to intellectual property relating
	# to a hardware implementation of the functionality of the software
	# licensed hereunder. You may use the software subject to the license
	# terms below provided that you ensure that this notice is replicated
	# unmodified and in its entirety in all distributions of the software,
	# modified or unmodified, in source code or in binary form.
	#
	# Copyright (c) 2007 The Regents of The University of Michigan
	# Copyright (c) 2010 The Hewlett-Packard Development Company
	# All rights reserved.
	#
	# Redistribution and use in source and binary forms, with or without
	# modification, are permitted provided that the following conditions are
	# met: redistributions of source code must retain the above copyright
	# notice, this list of conditions and the following disclaimer;
	# redistributions in binary form must reproduce the above copyright
	# notice, this list of conditions and the following disclaimer in the
	# documentation and/or other materials provided with the distribution;
	# neither the name of the copyright holders nor the names of its
	# contributors may be used to endorse or promote products derived from
	# this software without specific prior written permission.
	#
	# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
	# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
	# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
	# A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
	# OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
	# SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
	# LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
	# DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
	# THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
	# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
	# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

	import m5

	import _m5.stats
	from m5.objects import Root
	from m5.params import isNullPointer
	from .gem5stats import JsonOutputVistor
	from m5.util import attrdict, fatal

	# Stat exports
	from _m5.stats import schedStatEvent as schedEvent
	from _m5.stats import periodicStatDump

	outputList = []

	# Dictionary of stat visitor factories populated by the _url_factory
	# visitor.
	factories = { }

	# List of all factories. Contains tuples of (factory, schemes,
	# enabled).
	all_factories = []

	def _url_factory(schemes, enable=True):
	"""Wrap a plain Python function with URL parsing helpers

	Wrap a plain Python function f(fn, **kwargs) to expect a URL that
	has been split using urlparse.urlsplit. First positional argument
	is assumed to be a filename, this is created as the concatenation
	of the netloc (~hostname) and path in the parsed URL. Keyword
	arguments are derived from the query values in the URL.

	Arguments:
	schemes: A list of URL schemes to use for this function.

	Keyword arguments:
	enable: Enable/disable this factory. Typically used when the
	presence of a function depends on some runtime property.

	For example:
	wrapped_f(urlparse.urlsplit("text://stats.txt?desc=False")) ->
	f("stats.txt", desc=False)

	"""

	from functools import wraps

	def decorator(func):
	@wraps(func)
	def wrapper(url):
	try:
	from urllib.parse import parse_qs
	except ImportError:
	# Python 2 fallback
	from urlparse import parse_qs
	from ast import literal_eval

	qs = parse_qs(url.query, keep_blank_values=True)

	# parse_qs returns a list of values for each parameter. Only
	# use the last value since kwargs don't allow multiple values
	# per parameter. Use literal_eval to transform string param
	# values into proper Python types.
	def parse_value(key, values):
	if len(values) == 0 or (len(values) == 1 and not values[0]):
	fatal("%s: '%s' doesn't have a value." % (
	url.geturl(), key))
	elif len(values) > 1:
	fatal("%s: '%s' has multiple values." % (
	url.geturl(), key))
	else:
	try:
	return key, literal_eval(values[0])
	except ValueError:
	fatal("%s: %s isn't a valid Python literal" \
	% (url.geturl(), values[0]))

	kwargs = dict([ parse_value(k, v) for k, v in qs.items() ])

	try:
	return func("%s%s" % (url.netloc, url.path), **kwargs)
	except TypeError:
	fatal("Illegal stat visitor parameter specified")

	all_factories.append((wrapper, schemes, enable))
	for scheme in schemes:
	assert scheme not in factories
	factories[scheme] = wrapper if enable else None
	return wrapper

	return decorator

	@_url_factory([ None, "", "text", "file", ])
	def _textFactory(fn, desc=True, spaces=True):
	"""Output stats in text format.

	Text stat files contain one stat per line with an optional
	description. The description is enabled by default, but can be
	disabled by setting the desc parameter to False.

	Parameters:
	* desc (bool): Output stat descriptions (default: True)
	* spaces (bool): Output alignment spaces (default: True)

	Example:
	text://stats.txt?desc=False;spaces=False

	"""

	return _m5.stats.initText(fn, desc, spaces)

	@_url_factory([ "h5", ], enable=hasattr(_m5.stats, "initHDF5"))
	def _hdf5Factory(fn, chunking=10, desc=True, formulas=True):
	"""Output stats in HDF5 format.

	The HDF5 file format is a structured binary file format. It has
	the multiple benefits over traditional text stat files:

	* Efficient storage of time series (multiple stat dumps)
	* Fast lookup of stats
	* Plenty of existing tooling (e.g., Python libraries and graphical
	viewers)
	* File format can be used to store frame buffers together with
	normal stats.

	There are some drawbacks compared to the default text format:
	* Large startup cost (single stat dump larger than text equivalent)
	* Stat dumps are slower than text


	Known limitations:
	* Distributions and histograms currently unsupported.
	* No support for forking.


	Parameters:
	* chunking (unsigned): Number of time steps to pre-allocate (default: 10)
	* desc (bool): Output stat descriptions (default: True)
	* formulas (bool): Output derived stats (default: True)

	Example:
	h5://stats.h5?desc=False;chunking=100;formulas=False

	"""

	return _m5.stats.initHDF5(fn, chunking, desc, formulas)

	@_url_factory(["json"])
	def _jsonFactory(fn):
	"""Output stats in JSON format.

	Example:
	json://stats.json

	"""

	return JsonOutputVistor(fn)

	def addStatVisitor(url):
	"""Add a stat visitor specified using a URL string

	Stat visitors are specified using URLs on the following format:
	format://path[?param=value[;param=value]]

	The available formats are listed in the factories list. Factories
	are called with the path as the first positional parameter and the
	parameters are keyword arguments. Parameter values must be valid
	Python literals.

	"""

	try:
	from urllib.parse import urlsplit
	except ImportError:
	# Python 2 fallback
	from urlparse import urlsplit

	parsed = urlsplit(url)

	try:
	factory = factories[parsed.scheme]
	except KeyError:
	fatal("Illegal stat file type '%s' specified." % parsed.scheme)

	if factory is None:
	fatal("Stat type '%s' disabled at compile time" % parsed.scheme)

	outputList.append(factory(parsed))

	def printStatVisitorTypes():
	"""List available stat visitors and their documentation"""

	import inspect

	def print_doc(doc):
	for line in doc.splitlines():
	print("\| %s" % line)
	print()

	enabled_visitors = [ x for x in all_factories if x[2] ]
	for factory, schemes, _ in enabled_visitors:
	print("%s:" % ", ".join(filter(lambda x: x is not None, schemes)))

	# Try to extract the factory doc string
	print_doc(inspect.getdoc(factory))

	def initSimStats():
	_m5.stats.initSimStats()
	_m5.stats.registerPythonStatsHandlers()

	def _visit_groups(visitor, root=None):
	if root is None:
	root = Root.getInstance()
	for group in root.getStatGroups().values():
	visitor(group)
	_visit_groups(visitor, root=group)

	def _visit_stats(visitor, root=None):
	def for_each_stat(g):
	for stat in g.getStats():
	visitor(g, stat)
	_visit_groups(for_each_stat, root=root)

	def _bindStatHierarchy(root):
	def _bind_obj(name, obj):
	if isNullPointer(obj):
	return
	if m5.SimObject.isSimObjectVector(obj):
	if len(obj) == 1:
	_bind_obj(name, obj[0])
	else:
	for idx, obj in enumerate(obj):
	_bind_obj("{}{}".format(name, idx), obj)
	else:
	# We need this check because not all obj.getCCObject() is an
	# instance of Stat::Group. For example, sc_core::sc_module, the C++
	# class of SystemC_ScModule, is not a subclass of Stat::Group. So
	# it will cause a type error if obj is a SystemC_ScModule when
	# calling addStatGroup().
	if isinstance(obj.getCCObject(), _m5.stats.Group):
	parent = root
	while parent:
	if hasattr(parent, 'addStatGroup'):
	parent.addStatGroup(name, obj.getCCObject())
	break
	parent = parent.get_parent();

	_bindStatHierarchy(obj)

	for name, obj in root._children.items():
	_bind_obj(name, obj)

	names = []
	stats_dict = {}
	stats_list = []
	def enable():
	'''Enable the statistics package. Before the statistics package is
	enabled, all statistics must be created and initialized and once
	the package is enabled, no more statistics can be created.'''

	def check_stat(group, stat):
	if not stat.check() or not stat.baseCheck():
	fatal("statistic '%s' (%d) was not properly initialized " \
	"by a regStats() function\n", stat.name, stat.id)

	if not (stat.flags & flags.display):
	stat.name = "__Stat%06d" % stat.id


	# Legacy stat
	global stats_list
	stats_list = list(_m5.stats.statsList())

	for stat in stats_list:
	check_stat(None, stat)

	stats_list.sort(key=lambda s: s.name.split('.'))
	for stat in stats_list:
	stats_dict[stat.name] = stat
	stat.enable()


	# New stats
	_visit_stats(check_stat)
	_visit_stats(lambda g, s: s.enable())

	_m5.stats.enable();

	def prepare():
	'''Prepare all stats for data access. This must be done before
	dumping and serialization.'''

	# Legacy stats
	for stat in stats_list:
	stat.prepare()

	# New stats
	_visit_stats(lambda g, s: s.prepare())

	def _dump_to_visitor(visitor, roots=None):
	# New stats
	def dump_group(group):
	for stat in group.getStats():
	stat.visit(visitor)
	for n, g in group.getStatGroups().items():
	visitor.beginGroup(n)
	dump_group(g)
	visitor.endGroup()

	if roots:
	# New stats from selected subroots.
	for root in roots:
	for p in root.path_list():
	visitor.beginGroup(p)
	dump_group(root)
	for p in reversed(root.path_list()):
	visitor.endGroup()
	else:
	# New stats starting from root.
	dump_group(Root.getInstance())

	# Legacy stats
	for stat in stats_list:
	stat.visit(visitor)

	lastDump = 0
	# List[SimObject].
	global_dump_roots = []

	def dump(roots=None):
	'''Dump all statistics data to the registered outputs'''

	all_roots = []
	if roots is not None:
	all_roots.extend(roots)
	global global_dump_roots
	all_roots.extend(global_dump_roots)

	now = m5.curTick()
	global lastDump
	assert lastDump <= now
	new_dump = lastDump != now
	lastDump = now

	# Don't allow multiple global stat dumps in the same tick. It's
	# still possible to dump a multiple sub-trees.
	if not new_dump and not all_roots:
	return

	# Only prepare stats the first time we dump them in the same tick.
	if new_dump:
	_m5.stats.processDumpQueue()
	# Notify new-style stats group that we are about to dump stats.
	sim_root = Root.getInstance()
	if sim_root:
	sim_root.preDumpStats();
	prepare()

	for output in outputList:
	if isinstance(output, JsonOutputVistor):
	if not all_roots:
	output.dump(Root.getInstance())
	else:
	output.dump(all_roots)
	else:
	if output.valid():
	output.begin()
	_dump_to_visitor(output, roots=all_roots)
	output.end()

	def reset():
	'''Reset all statistics to the base state'''

	# call reset stats on all SimObjects
	root = Root.getInstance()
	if root:
	root.resetStats()

	# call any other registered legacy stats reset callbacks
	for stat in stats_list:
	stat.reset()

	_m5.stats.processResetQueue()

	flags = attrdict({
	'none' : 0x0000,
	'init' : 0x0001,
	'display' : 0x0002,
	'total' : 0x0010,
	'pdf' : 0x0020,
	'cdf' : 0x0040,
	'dist' : 0x0080,
	'nozero' : 0x0100,
	'nonan' : 0x0200,
	})