blob: 95d21825085bb127fab874ca8699807fa16259f8 [file] [log] [blame]
# 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.
#
# 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.
# This configuration file extends the example ARM big.LITTLE(tm)
# with example power models.
import argparse
import os
import m5
from m5.objects import MathExprPowerModel, PowerModel
import fs_bigLITTLE as bL
class CpuPowerOn(MathExprPowerModel):
def __init__(self, cpu_path, **kwargs):
super(CpuPowerOn, self).__init__(**kwargs)
# 2A per IPC, 3pA per cache miss
# and then convert to Watt
self.dyn = (
"voltage * (2 * {}.ipc + 3 * 0.000000001 * "
"{}.dcache.overallMisses / simSeconds)".format(cpu_path, cpu_path)
)
self.st = "4 * temp"
class CpuPowerOff(MathExprPowerModel):
dyn = "0"
st = "0"
class CpuPowerModel(PowerModel):
def __init__(self, cpu_path, **kwargs):
super(CpuPowerModel, self).__init__(**kwargs)
self.pm = [
CpuPowerOn(cpu_path), # ON
CpuPowerOff(), # CLK_GATED
CpuPowerOff(), # SRAM_RETENTION
CpuPowerOff(), # OFF
]
class L2PowerOn(MathExprPowerModel):
def __init__(self, l2_path, **kwargs):
super(L2PowerOn, self).__init__(**kwargs)
# Example to report l2 Cache overallAccesses
# The estimated power is converted to Watt and will vary based
# on the size of the cache
self.dyn = "{}.overallAccesses * 0.000018000".format(l2_path)
self.st = "(voltage * 3)/10"
class L2PowerOff(MathExprPowerModel):
dyn = "0"
st = "0"
class L2PowerModel(PowerModel):
def __init__(self, l2_path, **kwargs):
super(L2PowerModel, self).__init__(**kwargs)
# Choose a power model for every power state
self.pm = [
L2PowerOn(l2_path), # ON
L2PowerOff(), # CLK_GATED
L2PowerOff(), # SRAM_RETENTION
L2PowerOff(), # OFF
]
def main():
parser = argparse.ArgumentParser(
description="Generic ARM big.LITTLE configuration with "
"example power models"
)
bL.addOptions(parser)
options = parser.parse_args()
if options.cpu_type != "timing":
m5.fatal("The power example script requires 'timing' CPUs.")
root = bL.build(options)
# Wire up some example power models to the CPUs
for cpu in root.system.descendants():
if not isinstance(cpu, m5.objects.BaseCPU):
continue
cpu.power_state.default_state = "ON"
cpu.power_model = CpuPowerModel(cpu.path())
# Example power model for the L2 Cache of the bigCluster
for l2 in root.system.bigCluster.l2.descendants():
if not isinstance(l2, m5.objects.Cache):
continue
l2.power_state.default_state = "ON"
l2.power_model = L2PowerModel(l2.path())
bL.instantiate(options)
print("*" * 70)
print(
"WARNING: The power numbers generated by this script are "
"examples. They are not representative of any particular "
"implementation or process."
)
print("*" * 70)
# Dumping stats periodically
m5.stats.periodicStatDump(m5.ticks.fromSeconds(0.1e-3))
bL.run()
if __name__ == "__m5_main__":
main()