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mmperf.py
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mmperf.py
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#!/usr/bin/env python3
import sys
import argparse
import os
import os.path
import platform
import time
import subprocess
import shutil
import re
import collections
import signal
from datetime import datetime
from multiprocessing import Pool
from pathlib import Path
from functools import reduce
import matplotlib.pyplot as plt
import numpy as np
import GPUtil
plt.style.use('ggplot')
BAR_WIDTH = 0.15
BAR_COLORS = {'mkl': 'cornflowerblue',
'accelerate': 'lightgray',
'mlir': 'sandybrown',
'mlircuda': 'green',
'openblas': 'mediumseagreen',
'blis': 'mediumspringgreen',
'blasfeo': 'olivedrab',
'cublas': 'chocolate',
'halide': 'gold',
'ruy': 'violet',
'tvm' : 'indigo',
'naive': 'black',
'nodai': 'red',
'nodai-1': 'dodgerblue',
'nodai-2': 'purple',
'ireevmvx': 'thistle',
'ireedylib': 'aqua',
'ireecuda': 'deeppink',
'ireellvmsandbox': 'wheat'}
BENCHMARK_ENV = os.environ.copy()
BENCHMARK_ENV.update({
"MKL_NUM_THREADS": "1",
"OPENBLAS_NUM_THREADS": "1",
"BLIS_NUM_THREADS": "1",
"HL_NUM_THREADS": "1",
"VECLIB_MAXIMUM_THREADS": "1",
"OMP_NUM_THREADS": "1",
"TVM_NUM_THREADS": "1",
})
def path_expand(s):
return Path(s).expanduser().resolve()
def add_arguments(parser):
parser.add_argument('bins', type=path_expand, help='Path where the test binaries are')
parser.add_argument('results', type=path_expand, help='Result directory')
parser.add_argument('-j', '--jobs', type=int, default=1, help='Number of parallel jobs for running the benchmarks')
def make_result_dir(base_dir):
timestamp = datetime.now().strftime("%Y-%m-%d_%H-%M-%S-%f")
result_dir = (base_dir / timestamp).resolve()
os.makedirs(result_dir)
return result_dir
def write_system_info(output_dir, cpuinfo_dir):
pfm = platform.system()
if pfm == "Linux":
# linux
print("Linux System Detected.. looking for /proc/cpuinfo")
shutil.copyfile(Path("/proc/cpuinfo"), output_dir / "cpuinfo")
cpu_pattern = re.compile('cpu[0-9]+')
cpudirs = [x for x in Path("/sys/devices/system/cpu/").iterdir() if cpu_pattern.match(x.name)]
with open(output_dir / 'scaling_governor', 'w') as f:
for cpu in cpudirs:
sc_gov = (cpu / 'cpufreq' / 'scaling_governor')
if sc_gov.is_file():
f.write(cpu.name + ": " + sc_gov.read_text())
else:
f.write(cpu.name + ": not available")
with open(output_dir / 'core_frequencies', 'w') as f:
for cpu in cpudirs:
sc_freq = (cpu / 'cpufreq' / 'scaling_cur_freq')
if sc_freq.is_file():
f.write(cpu.name + ": " + sc_freq.read_text())
else:
f.write(cpu.name + ": not available")
elif pfm == "Darwin":
# OSX
print("OSX System Detected")
else:
print("Unidentified system")
with open(output_dir / 'arch-info', 'w') as fh:
proc = subprocess.run([cpuinfo_dir / "bin" / "cpu-info"],
capture_output=True, text=True, check=True)
fh.write(proc.stdout)
proc = subprocess.run([cpuinfo_dir / "bin" / "isa-info"],
capture_output=True, text=True, check=True)
fh.write(proc.stdout)
proc = subprocess.run([cpuinfo_dir / "bin" / "cache-info"],
capture_output=True, text=True, check=True)
fh.write(proc.stdout)
# Obtain GPU information if available
try:
GPUs = GPUtil.getGPUs()
# TODO: investigate why GPUs gets set to empty list in some cases
if (len(GPUs) > 0):
with open(output_dir / 'gpu-info', 'w') as fg:
gpu_name = GPUs[0].name
fg.write(gpu_name)
except:
pass
def autolabel(rects):
"""
Attach a text label above each bar displaying its height
"""
for rect in rects:
height = rect.get_height()
# If the floor value of GFLOPS is 0 print its float value
if(int(height) == 0):
plt.text(rect.get_x() + rect.get_width()/2., 1.02*height,
'%.3f' % float(height), fontsize=5, ha='center', va='bottom')
else:
plt.text(rect.get_x() + rect.get_width()/2., 1.02*height,
'%d' % int(height), fontsize=5, ha='center', va='bottom')
_result_dir = None
_env = None
def _do_single_permutation(i, path, duration=None):
t0 = time.perf_counter()
if not duration:
duration = 1
reps = str(duration)
result = subprocess.run([str(path), f'{reps}'], stdout=subprocess.DEVNULL, cwd=_result_dir, env=_env, check=False)
t1 = time.perf_counter()
gflops_path = _result_dir / (path.name + '_perf.out')
if gflops_path.is_file():
speed = float(gflops_path.read_text().split()[0])
runtime = t1 - t0
if result.returncode != 0:
print("Benchmark failed with error code:",
signal.Signals(-result.returncode) if result.returncode < 0
else result.returncode)
return i, False, runtime
else:
return i, speed, runtime
def _worker_init(result_dir, env):
global _result_dir, _env, _num_tasks, _done_tasks
print('worker init')
_result_dir = result_dir
_env = env
def do_permutations(jobs, perms, bin_path, result_dir, env, duration=None):
num_tasks = len(perms)
speeds = np.zeros((num_tasks,))
runtimes = np.zeros((num_tasks,))
async_results = [None] * num_tasks
done_tasks = 0
def callback(job_values):
nonlocal done_tasks
index, speed, runtime = job_values
runtimes[index] = runtime
done_tasks += 1
if speed is False:
print(f'{done_tasks}/{num_tasks} done, {perms[index]} took {runtime} and FAILED!')
else:
speeds[index] = speed
print(f'{done_tasks}/{num_tasks} done, {perms[index]} took {runtime} and yields {speed}')
with Pool(jobs, _worker_init, (result_dir, env)) as pool:
for i, perm in enumerate(perms):
async_results[i] = pool.apply_async(_do_single_permutation, (i, bin_path / perm, duration), callback=callback)
print("Submitted all jobs to pool")
for ar in async_results:
ar.get()
pool.close()
pool.join()
return speeds
def main(argv):
parser = argparse.ArgumentParser()
add_arguments(parser)
args = parser.parse_args(argv[1:])
result_dir = make_result_dir(args.results)
write_system_info(result_dir, args.bins.parent / 'cpuinfo-install')
# get only the executables
bin_paths = [x for x in args.bins.iterdir() if
x.is_file() and x.stat().st_mode & 0o111 and x.name.startswith('matmul')]
# run them in parallel and collect the results
speeds = do_permutations(args.jobs, list(x.name for x in bin_paths), args.bins, result_dir, BENCHMARK_ENV)
# break up and interpret the file names
binaries = {}
for i, path in enumerate(bin_paths):
parts = path.name.split('_')[1:]
parts[1] = parts[1].replace('m', '', 1)
size = tuple(int(y) for y in parts[1].split('x'))
binaries.setdefault(parts[0], []).append(
{'path': path.resolve(), 'size': size, 'speed': speeds[i]})
# used to impose a consistent sorting of the matrix sizes in the plot
bar_ordering = list(collections.OrderedDict.fromkeys(y['size'] for x in binaries for y in binaries[x]))
bar_ordering.sort(key=lambda s: (reduce(lambda x, y: x*y, s), s))
any_error = False
for idx, backend in enumerate(binaries):
bar_x = []
speeds = []
for binary in binaries[backend]:
print(backend, binary)
speeds.append(binary['speed'])
bar_x.append(bar_ordering.index(binary['size']) + idx * BAR_WIDTH)
if len(bar_x) > 0:
autolabel(plt.bar(bar_x, speeds, BAR_WIDTH, color=BAR_COLORS[backend], label=backend))
else:
print("No results could be collected for backend", backend)
plt.xlabel("Matrix sizes")
plt.ylabel("GFLOPS")
plt.title("Single Precision Matrix Multiplication")
system_info = ""
f=open(result_dir / 'arch-info')
lines=f.readlines()
system_info = system_info + "CPU:{}: {} (cores x Microarch)".format(lines[1].strip(), lines[3].strip())
f.close()
gpu_info_file = Path(result_dir / 'gpu-info')
if gpu_info_file.exists():
f=open(gpu_info_file)
lines=f.readlines()
system_info = system_info + ", GPU Model:{}".format(lines[0].strip())
f.close()
plt.suptitle(system_info, fontsize=7)
x_pos = [i + 0.5*(len(binaries) - 1)*BAR_WIDTH for i in range(len(bar_ordering))]
plt.xticks(x_pos, ['x'.join(str(d) for d in s) for s in bar_ordering], rotation=90, fontsize=5)
plt.legend(loc='best')
plt.savefig(result_dir / 'matmul.png', dpi=300, bbox_inches='tight')
if any_error:
print("Some benchmarks had problems, see above.")
return 1
return 0
if __name__ == '__main__':
sys.exit(main(sys.argv))