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# Copyright (c) 2021 The Regents of the University of California.
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#
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"""
Script to run NAS parallel benchmarks with gem5. The script expects the
benchmark program to run. The input is in the format
<benchmark_prog>.<class>.x .The system is fixed with 2 CPU cores, MESI
Two Level system cache and 3 GB DDR4 memory. It uses the x86 board.
This script will count the total number of instructions executed
in the ROI. It also tracks how much wallclock and simulated time.
Usage:
------
```
scons build/X86/gem5.opt
./build/X86/gem5.opt \
configs/example/gem5_library/x86-npb-benchmarks.py \
--benchmark <benchmark_name> \
--size <benchmark_class>
```
"""
import argparse
import time
import m5
from m5.objects import Root
from gem5.utils.requires import requires
from gem5.components.boards.x86_board import X86Board
from gem5.components.memory import DualChannelDDR4_2400
from gem5.components.processors.simple_switchable_processor import (
SimpleSwitchableProcessor,
)
from gem5.components.processors.cpu_types import CPUTypes
from gem5.isas import ISA
from gem5.coherence_protocol import CoherenceProtocol
from gem5.resources.resource import Resource
from gem5.simulate.simulator import Simulator
from gem5.simulate.simulator import ExitEvent
from m5.stats.gem5stats import get_simstat
from m5.util import warn
requires(
isa_required=ISA.X86,
coherence_protocol_required=CoherenceProtocol.MESI_TWO_LEVEL,
kvm_required=True,
)
# Following are the list of benchmark programs for npb.
benchmark_choices = ["bt", "cg", "ep", "ft", "is", "lu", "mg", "sp"]
# We are restricting classes of NPB to A, B and C as the other classes (D and
# F) require main memory size of more than 3 GB. The X86Board is currently
# limited to 3 GB of memory. This limitation is explained later in line 136.
# The resource disk has binaries for class D. However, only `ep` benchmark
# works with class D in the current configuration. More information on the
# memory footprint for NPB is available at https://arxiv.org/abs/2010.13216
size_choices = ["A", "B", "C"]
parser = argparse.ArgumentParser(
description="An example configuration script to run the npb benchmarks."
)
# The only positional argument accepted is the benchmark name in this script.
parser.add_argument(
"--benchmark",
type=str,
required=True,
help="Input the benchmark program to execute.",
choices=benchmark_choices,
)
parser.add_argument(
"--size",
type=str,
required=True,
help="Input the class of the program to simulate.",
choices=size_choices,
)
parser.add_argument(
"--ticks",
type=int,
help="Optionally put the maximum number of ticks to execute during the "
"ROI. It accepts an integer value.",
)
args = parser.parse_args()
# The simulation may fail in the case of `mg` with class C as it uses 3.3 GB
# of memory (more information is availabe at https://arxiv.org/abs/2010.13216).
# We warn the user here.
if args.benchmark == "mg" and args.size == "C":
warn(
"mg.C uses 3.3 GB of memory. Currently we are simulating 3 GB\
of main memory in the system."
)
# The simulation will fail in the case of `ft` with class C. We warn the user
# here.
elif args.benchmark == "ft" and args.size == "C":
warn(
"There is not enough memory for ft.C. Currently we are\
simulating 3 GB of main memory in the system."
)
# Checking for the maximum number of instructions, if provided by the user.
# Setting up all the fixed system parameters here
# Caches: MESI Two Level Cache Hierarchy
from gem5.components.cachehierarchies.ruby.mesi_two_level_cache_hierarchy import (
MESITwoLevelCacheHierarchy,
)
cache_hierarchy = MESITwoLevelCacheHierarchy(
l1d_size="32kB",
l1d_assoc=8,
l1i_size="32kB",
l1i_assoc=8,
l2_size="256kB",
l2_assoc=16,
num_l2_banks=2,
)
# Memory: Dual Channel DDR4 2400 DRAM device.
# The X86 board only supports 3 GB of main memory.
memory = DualChannelDDR4_2400(size="3GB")
# Here we setup the processor. This is a special switchable processor in which
# a starting core type and a switch core type must be specified. Once a
# configuration is instantiated a user may call `processor.switch()` to switch
# from the starting core types to the switch core types. In this simulation
# we start with KVM cores to simulate the OS boot, then switch to the Timing
# cores for the command we wish to run after boot.
processor = SimpleSwitchableProcessor(
starting_core_type=CPUTypes.KVM,
switch_core_type=CPUTypes.TIMING,
isa=ISA.X86,
num_cores=2,
)
# Here we setup the board. The X86Board allows for Full-System X86 simulations
board = X86Board(
clk_freq="3GHz",
processor=processor,
memory=memory,
cache_hierarchy=cache_hierarchy,
)
# Here we set the FS workload, i.e., npb benchmark program
# After simulation has ended you may inspect
# `m5out/system.pc.com_1.device` to the stdout, if any.
# After the system boots, we execute the benchmark program and wait till the
# ROI `workbegin` annotation is reached (m5_work_begin()). We start collecting
# the number of committed instructions till ROI ends (marked by `workend`).
# We then finish executing the rest of the benchmark.
# Also, we sleep the system for some time so that the output is printed
# properly.
command = (
"/home/gem5/NPB3.3-OMP/bin/{}.{}.x;".format(args.benchmark, args.size)
+ "sleep 5;"
+ "m5 exit;"
)
board.set_kernel_disk_workload(
# The x86 linux kernel will be automatically downloaded to the
# `~/.cache/gem5` directory if not already present.
# npb benchamarks was tested with kernel version 4.19.83
kernel=Resource("x86-linux-kernel-4.19.83"),
# The x86-npb image will be automatically downloaded to the
# `~/.cache/gem5` directory if not already present.
disk_image=Resource("x86-npb"),
readfile_contents=command,
)
# The first exit_event ends with a `workbegin` cause. This means that the
# system started successfully and the execution on the program started.
def handle_workbegin():
print("Done booting Linux")
print("Resetting stats at the start of ROI!")
m5.stats.reset()
# We have completed up to this step using KVM cpu. Now we switch to timing
# cpu for detailed simulation.
# # Next, we need to check if the user passed a value for --ticks. If yes,
# then we limit out execution to this number of ticks during the ROI.
# Otherwise, we simulate until the ROI ends.
processor.switch()
if args.ticks:
# schedule an exit event for this amount of ticks in the future.
# The simulation will then continue.
m5.scheduleTickExitFromCurrent(args.ticks)
yield False
# The next exit_event is to simulate the ROI. It should be exited with a cause
# marked by `workend`.
# We exepect that ROI ends with `workend` or `simulate() limit reached`.
def handle_workend():
print("Dump stats at the end of the ROI!")
m5.stats.dump()
yield True
simulator = Simulator(
board=board,
on_exit_event={
ExitEvent.WORKBEGIN: handle_workbegin(),
ExitEvent.WORKEND: handle_workend(),
},
)
# We maintain the wall clock time.
globalStart = time.time()
print("Running the simulation")
print("Using KVM cpu")
# We start the simulation.
simulator.run()
# We need to note that the benchmark is not executed completely till this
# point, but, the ROI has. We collect the essential statistics here before
# resuming the simulation again.
# Simulation is over at this point. We acknowledge that all the simulation
# events were successful.
print("All simulation events were successful.")
# We print the final simulation statistics.
print("Done with the simulation")
print()
print("Performance statistics:")
# manually calculate ROI time if ticks arg is used in case the
# entire ROI wasn't simulated
if args.ticks:
print(f"Simulated time in ROI (to tick): {args.ticks/ 1e12}s")
else:
print(f"Simulated time in ROI: {simulator.get_roi_ticks()[0] / 1e12}s")
print(
f"Ran a total of {simulator.get_current_tick() / 1e12} simulated seconds"
)
print(
"Total wallclock time: %.2fs, %.2f min"
% (time.time() - globalStart, (time.time() - globalStart) / 60)
)