Files
project_6/upstream_ref/nvidia_sgemm_practice/plot.py

67 lines
2.1 KiB
Python
Raw Normal View History

import os
import re
import matplotlib.pyplot as plt
from matplotlib.pyplot import MultipleLocator
import argparse
def parse_file(file):
with open(file, 'r') as f:
lines = [line.strip() for line in f.readlines()]
data = []
pattern = "Average elasped time: \((.*?)\) second, performance: \((.*?)\) GFLOPS. size: \((.*?)\)."
for line in lines:
r = re.match(pattern, line)
if r:
gflops = float(r.group(2))
data.append(gflops)
return data
def plot(num1, num2, y1, y2, save_dir):
x = [(i + 1) * 256 for i in range(len(y1))]
fig = plt.figure(figsize=(12, 10))
if num1 == 0:
num1 = "culas"
plt.plot(x, y1, c='k', linewidth=2, label=f"kernel_{num1}")
plt.plot(x, y2, c='b', linewidth=2, label=f"kernel_{num2}")
plt.legend()
plt.scatter(x, y1, marker="s", s=60, c='', edgecolors='k', linewidth=2)
plt.scatter(x, y2, marker="^", s=60, c='', edgecolors='b', linewidth=2)
plt.tick_params(labelsize=10)
plt.xlabel("Matrix size (M=N=K)", fontsize=12, fontweight='bold')
plt.ylabel("Performance (GFLOPS)", fontsize=12, fontweight='bold')
plt.title(f"Comparison bewteen: kernel_{num1} and kernel_{num2}", fontsize=16, fontweight='bold')
x_major_locator = MultipleLocator(256)
plt.gca().xaxis.set_major_locator(x_major_locator)
plt.savefig(f"{save_dir}/kernel_{num1}_vs_{num2}.png")
def main(args):
root = os.path.dirname(os.path.abspath(__file__))
data1 = parse_file(os.path.join(root, f'test/test_kernel_{args.one}.txt'))
data2 = parse_file(os.path.join(root, f'test/test_kernel_{args.another}.txt'))
plot(args.one, args.another, data1, data2, args.save_dir)
def parse_args():
parser = argparse.ArgumentParser(description='plot kernel performance')
parser.add_argument('one', type=int, help='one kernel num')
parser.add_argument('another', type=int, help='another kernel num')
parser.add_argument('--save_dir', default='images')
return parser.parse_args()
if __name__ == "__main__":
args = parse_args()
main(args)
# python plot.py 0 1