Perf analysis scripts.

This commit is contained in:
Ville Pietilä
2025-12-12 10:33:32 -05:00
parent fa19112a68
commit 3361cfd1bf
3 changed files with 116 additions and 13 deletions

View File

@@ -51,11 +51,11 @@ def run_ck_profiler_cmd(cmd_args, profiler_type, bin_path, results_file, log_to_
env["CK_PROFILER_LOG_FILE"] = results_file
env["CK_TILE_PROFILER_LOG_FILE"] = results_file
timeoutInSec = 300 * 60 # 300 minutes timeout
if log_to_stdout:
subprocess.run(cmd)
subprocess.run(cmd, timeout=timeoutInSec, env=env)
else:
with open(os.devnull, 'w') as devnull:
timeoutInSec = 300 * 60 # 300 minutes timeout
try:
subprocess.run(cmd, stdout=devnull, stderr=devnull, timeout=timeoutInSec, env=env)
except subprocess.TimeoutExpired:
@@ -416,19 +416,14 @@ def main():
if not os.path.exists(args.results_path):
os.makedirs(args.results_path)
results_file = os.path.join(args.results_path, f"ck_results_{args.data_type}_{os.getpid()}.txt")
# Get computer host name
hostname = os.uname().nodename.split('.')[0]
results_file = os.path.join(args.results_path, f"ck_results_{hostname}_{args.data_type}_{os.getpid()}.txt")
data_type_arg = data_type_str_to_profiler_arg(args.data_type)
for i, cmd in enumerate(profiler_commands):
cmd_concatenated_str = ' '.join(cmd)
print(f"\n####################################################################################################################")
print(f"Running command {i + 1}/{len(profiler_commands)}: {cmd_concatenated_str}")
print(f"######################################################################################################################")
# with open(results_file, 'a') as f:
# f.write(cmd_concatenated_str + "\n")
# run_ck_profiler_cmd(cmd, ProfilerType.CK_TILE, args.bin_path, results_file, args.log_to_stdout)
# Set the correct data type based on user input
cmd[1] = data_type_arg
@@ -438,6 +433,15 @@ def main():
# We don't want to run verification. We assume CK already works correctly.
cmd[3] = '0' # Set verification flag to 0 (no verification)
cmd_concatenated_str = ' '.join(cmd)
print(f"\n####################################################################################################################")
print(f"Running command {i + 1}/{len(profiler_commands)}: {cmd_concatenated_str}")
print(f"######################################################################################################################")
# Print the command to the output file
with open(results_file, 'a') as f:
f.write(cmd_concatenated_str + "\n")
run_ck_profiler_cmd(cmd, ProfilerType.CK, args.bin_path, results_file, args.log_to_stdout)
if __name__ == "__main__":

89
script/plot_navi_perf.py Executable file
View File

@@ -0,0 +1,89 @@
#!/usr/bin/env python3
import os
import argparse
import subprocess
import sys
import matplotlib.pyplot as plt
# Non-interactive backend for matplotlib
plt.switch_backend('Agg')
import numpy as np
def parse_cli_args():
"""Parse command line arguments"""
parser = argparse.ArgumentParser(description="Run CK and CK Tile convolution profilers.")
parser.add_argument("--input-file-int8", type=str, dest="input_file_int8", required=False, help="Path to the file containing test results for int8.")
parser.add_argument("--input-file-fp16", type=str, dest="input_file_fp16", required=False, help="Path to the file containing test results for fp16.")
args, unknown_args = parser.parse_known_args()
if unknown_args:
print(f"Unknown arguments: {unknown_args}", file=sys.stderr)
sys.exit(1)
return args
def parse_times(input_file):
with open(input_file, 'r') as f:
lines = f.readlines()
ang_time_lines = lines[3::4] # Every 4th line starting from line 3
avg_times = [float(line.strip().split("avg_time: ")[-1]) for line in ang_time_lines]
commnds = lines[0::4] # Every 4th line starting from line 0
# Create a dictionary of commands to their average times
cmd_time_dict = {}
for cmd, time in zip(commnds, avg_times):
cmd_time_dict[cmd.strip()] = time
return cmd_time_dict
def plot_perf(times_int8, times_fp16, output_file):
#n_samples = min(len(times_int8), len(times_fp16))
# From two dictionaries, extract the values where the key is present in both dictionaries
speedup_percentage = []
for cmd in times_int8:
print(cmd)
print(f"Times int8: {times_int8[cmd]}")
# TODO: WE need account for the different data types in the commands
if cmd in times_fp16:
time_int8 = times_int8[cmd]
time_fp16 = times_fp16[cmd]
print(f"int8 time: {time_int8}, fp16 time: {time_fp16}")
if time_fp16 > 0:
speedup = (time_fp16 - time_int8) / time_fp16 * 100
speedup_percentage.append(speedup)
n_samples = len(speedup_percentage)
x = np.arange(n_samples)
plt.figure(figsize=(10, 6))
plt.plot(x, speedup_percentage, marker='o')
plt.title('Speedup of int8 over fp16')
plt.xlabel('Sample Index')
plt.ylabel('Speedup (%)')
plt.grid(True)
plt.savefig(output_file)
plt.close()
def main():
args = parse_cli_args()
times_int8 = parse_times(args.input_file_int8)
times_fp16 = parse_times(args.input_file_fp16)
#avg_times_int8 = np.mean(np.array(times_int8.items()))
#avg_times_fp16 = np.mean(np.array(times_fp16.items()))
print(f"Got {len(times_int8)} int8 samples and {len(times_fp16)} fp16 samples.")
# print(f"Average time for int8: {avg_times_int8} ms")
# print(f"Average time for fp16: {avg_times_fp16} ms")
# print(f"Speedup (int8 over fp16): {avg_times_fp16 / avg_times_int8:.2f}x")
output_plot_file = "navi_perf_int8_vs_fp16.png"
output_path = os.path.join(os.getcwd(), output_plot_file)
plot_perf(times_int8, times_fp16, output_path)
print(f"Performance plot saved to {output_path}")
if __name__ == "__main__":
main()