scripts/performance: Add dissect.py script
Python script that dissects QEMU execution into three main phases:
code generation, JIT execution and helpers execution.
Syntax:
dissect.py [-h] -- <qemu executable> [<qemu executable options>] \
<target executable> [<target executable options>]
[-h] - Print the script arguments help message.
Example of usage:
dissect.py -- qemu-arm coulomb_double-arm
Example output:
Total Instructions: 4,702,865,362
Code Generation: 115,819,309 2.463%
JIT Execution: 1,081,980,528 23.007%
Helpers: 3,505,065,525 74.530%
Signed-off-by: Ahmed Karaman <ahmedkhaledkaraman@gmail.com>
Reviewed-by: Aleksandar Markovic <aleksandar.qemu.devel@gmail.com>
Reviewed-by: Philippe Mathieu-Daudé <philmd@redhat.com>
Message-Id: <20200709052055.2650-2-ahmedkhaledkaraman@gmail.com>
Signed-off-by: Philippe Mathieu-Daudé <philmd@redhat.com>
This commit is contained in:
Ahmed Karaman
Philippe Mathieu-Daudé
parent
1a53dfee92
commit
01afa757b6
166
scripts/performance/dissect.py
Executable file
166
scripts/performance/dissect.py
Executable file
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#!/usr/bin/env python3
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# Print the percentage of instructions spent in each phase of QEMU
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# execution.
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#
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# Syntax:
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# dissect.py [-h] -- <qemu executable> [<qemu executable options>] \
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# <target executable> [<target executable options>]
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#
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# [-h] - Print the script arguments help message.
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#
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# Example of usage:
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# dissect.py -- qemu-arm coulomb_double-arm
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#
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# This file is a part of the project "TCG Continuous Benchmarking".
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#
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# Copyright (C) 2020 Ahmed Karaman <ahmedkhaledkaraman@gmail.com>
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# Copyright (C) 2020 Aleksandar Markovic <aleksandar.qemu.devel@gmail.com>
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#
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# This program is free software: you can redistribute it and/or modify
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# it under the terms of the GNU General Public License as published by
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# the Free Software Foundation, either version 2 of the License, or
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# (at your option) any later version.
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#
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# This program is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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# GNU General Public License for more details.
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#
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# You should have received a copy of the GNU General Public License
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# along with this program. If not, see <https://www.gnu.org/licenses/>.
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import argparse
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import os
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import subprocess
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import sys
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import tempfile
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def get_JIT_line(callgrind_data):
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"""
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Search for the first instance of the JIT call in
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the callgrind_annotate output when ran using --tree=caller
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This is equivalent to the self number of instructions of JIT.
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Parameters:
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callgrind_data (list): callgrind_annotate output
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Returns:
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(int): Line number
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"""
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line = -1
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for i in range(len(callgrind_data)):
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if callgrind_data[i].strip('\n') and \
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callgrind_data[i].split()[-1] == "[???]":
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line = i
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break
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if line == -1:
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sys.exit("Couldn't locate the JIT call ... Exiting.")
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return line
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def main():
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# Parse the command line arguments
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parser = argparse.ArgumentParser(
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usage='dissect.py [-h] -- '
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'<qemu executable> [<qemu executable options>] '
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'<target executable> [<target executable options>]')
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parser.add_argument('command', type=str, nargs='+', help=argparse.SUPPRESS)
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args = parser.parse_args()
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# Extract the needed variables from the args
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command = args.command
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# Insure that valgrind is installed
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check_valgrind = subprocess.run(
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["which", "valgrind"], stdout=subprocess.DEVNULL)
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if check_valgrind.returncode:
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sys.exit("Please install valgrind before running the script.")
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# Save all intermediate files in a temporary directory
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with tempfile.TemporaryDirectory() as tmpdirname:
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# callgrind output file path
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data_path = os.path.join(tmpdirname, "callgrind.data")
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# callgrind_annotate output file path
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annotate_out_path = os.path.join(tmpdirname, "callgrind_annotate.out")
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# Run callgrind
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callgrind = subprocess.run((["valgrind",
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"--tool=callgrind",
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"--callgrind-out-file=" + data_path]
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+ command),
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stdout=subprocess.DEVNULL,
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stderr=subprocess.PIPE)
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if callgrind.returncode:
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sys.exit(callgrind.stderr.decode("utf-8"))
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# Save callgrind_annotate output
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with open(annotate_out_path, "w") as output:
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callgrind_annotate = subprocess.run(
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["callgrind_annotate", data_path, "--tree=caller"],
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stdout=output,
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stderr=subprocess.PIPE)
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if callgrind_annotate.returncode:
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sys.exit(callgrind_annotate.stderr.decode("utf-8"))
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# Read the callgrind_annotate output to callgrind_data[]
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callgrind_data = []
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with open(annotate_out_path, 'r') as data:
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callgrind_data = data.readlines()
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# Line number with the total number of instructions
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total_instructions_line_number = 20
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# Get the total number of instructions
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total_instructions_line_data = \
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callgrind_data[total_instructions_line_number]
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total_instructions = total_instructions_line_data.split()[0]
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total_instructions = int(total_instructions.replace(',', ''))
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# Line number with the JIT self number of instructions
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JIT_self_instructions_line_number = get_JIT_line(callgrind_data)
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# Get the JIT self number of instructions
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JIT_self_instructions_line_data = \
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callgrind_data[JIT_self_instructions_line_number]
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JIT_self_instructions = JIT_self_instructions_line_data.split()[0]
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JIT_self_instructions = int(JIT_self_instructions.replace(',', ''))
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# Line number with the JIT self + inclusive number of instructions
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# It's the line above the first JIT call when running with --tree=caller
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JIT_total_instructions_line_number = JIT_self_instructions_line_number-1
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# Get the JIT self + inclusive number of instructions
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JIT_total_instructions_line_data = \
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callgrind_data[JIT_total_instructions_line_number]
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JIT_total_instructions = JIT_total_instructions_line_data.split()[0]
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JIT_total_instructions = int(JIT_total_instructions.replace(',', ''))
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# Calculate number of instructions in helpers and code generation
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helpers_instructions = JIT_total_instructions-JIT_self_instructions
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code_generation_instructions = total_instructions-JIT_total_instructions
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# Print results (Insert commas in large numbers)
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# Print total number of instructions
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print('{:<20}{:>20}\n'.
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format("Total Instructions:",
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format(total_instructions, ',')))
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# Print code generation instructions and percentage
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print('{:<20}{:>20}\t{:>6.3f}%'.
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format("Code Generation:",
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format(code_generation_instructions, ","),
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(code_generation_instructions / total_instructions) * 100))
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# Print JIT instructions and percentage
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print('{:<20}{:>20}\t{:>6.3f}%'.
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format("JIT Execution:",
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format(JIT_self_instructions, ","),
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(JIT_self_instructions / total_instructions) * 100))
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# Print helpers instructions and percentage
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print('{:<20}{:>20}\t{:>6.3f}%'.
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format("Helpers:",
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format(helpers_instructions, ","),
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(helpers_instructions/total_instructions)*100))
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if __name__ == "__main__":
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main()
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