File size: 6,918 Bytes
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import json
import os
import shutil
import subprocess
import sys
import tempfile
import zipfile
from pathlib import Path
def extract_whl(whl_file, extract_dir):
with zipfile.ZipFile(whl_file, "r") as zip_ref:
zip_ref.extractall(extract_dir)
def find_binary_files(extract_dir):
binary_files = []
extract_path = Path(extract_dir)
for so_file in extract_path.rglob("*.so"):
binary_files.append(str(so_file))
for cubin_file in extract_path.rglob("*.cubin"):
binary_files.append(str(cubin_file))
return sorted(binary_files)
def run_cubloaty(binary_file):
result = subprocess.run(
["cubloaty", binary_file, "--format", "json"],
capture_output=True,
text=True,
timeout=60,
)
if result.returncode != 0:
if (
"No CUDA binary sections found" in result.stderr
or "does not contain device code" in result.stderr
):
return {}
raise subprocess.CalledProcessError(
result.returncode, result.args, result.stdout, result.stderr
)
return json.loads(result.stdout)
def analyze_whl(whl_file):
temp_dir = tempfile.mkdtemp(prefix="sgl_kernel_analysis_")
try:
extract_whl(whl_file, temp_dir)
binary_files = find_binary_files(temp_dir)
if not binary_files:
print(f"No .so or .cubin files found in {whl_file}")
return []
all_kernels = []
for binary_file in binary_files:
file_name = os.path.basename(binary_file)
data = run_cubloaty(binary_file)
if not data or "kernels" not in data:
continue
for kernel in data["kernels"]:
all_kernels.append(
{
"file": file_name,
"name": kernel.get("name", "unknown"),
"size": kernel.get("size", 0),
"size_kb": kernel.get("size", 0) / 1024,
"size_mb": kernel.get("size", 0) / 1024 / 1024,
}
)
return all_kernels
finally:
shutil.rmtree(temp_dir, ignore_errors=True)
def extract_kernel_prefix(kernel_name):
if "<" in kernel_name:
return kernel_name.split("<")[0]
return kernel_name
def generate_report(all_kernels, output_file):
if not all_kernels:
print("No kernels found")
return
sorted_kernels = sorted(all_kernels, key=lambda x: x["size"], reverse=True)
total_size = sum(k["size"] for k in all_kernels)
total_size_mb = total_size / 1024 / 1024
from collections import defaultdict
kernel_groups = defaultdict(lambda: {"size": 0, "count": 0})
for kernel in all_kernels:
prefix = extract_kernel_prefix(kernel["name"])
kernel_groups[prefix]["size"] += kernel["size"]
kernel_groups[prefix]["count"] += 1
sorted_groups = sorted(
kernel_groups.items(), key=lambda x: x[1]["size"], reverse=True
)
lines = []
lines.append("=" * 140)
lines.append("CUDA Kernel Size Analysis")
lines.append("=" * 140)
lines.append("")
lines.append(f"Total kernels: {len(all_kernels)}")
lines.append(f"Total size: {total_size_mb:.2f} MB ({total_size:,} bytes)")
lines.append(f"Average kernel size: {total_size / len(all_kernels) / 1024:.2f} KB")
lines.append("")
lines.append("=" * 140)
lines.append("Kernel Groups (by name prefix) - Top 20")
lines.append("=" * 140)
lines.append(
f"{'Rank':<6} {'Kernel Prefix':<80} {'Count':<8} {'Total (MB)':<12} {'%':<8}"
)
lines.append("-" * 140)
TOP_N = 20
for i, (prefix, stats) in enumerate(sorted_groups[:TOP_N], 1):
percentage = (stats["size"] / total_size * 100) if total_size > 0 else 0
size_mb = stats["size"] / 1024 / 1024
display_prefix = prefix
if len(display_prefix) > 77:
display_prefix = display_prefix[:74] + "..."
lines.append(
f"{i:<6} {display_prefix:<80} {stats['count']:<8} {size_mb:<12.2f} {percentage:<8.2f}"
)
if len(sorted_groups) > TOP_N:
other_size = sum(stats["size"] for _, stats in sorted_groups[TOP_N:])
other_count = sum(stats["count"] for _, stats in sorted_groups[TOP_N:])
other_percentage = (other_size / total_size * 100) if total_size > 0 else 0
other_size_mb = other_size / 1024 / 1024
lines.append(
f"{'Other':<6} {'(remaining ' + str(len(sorted_groups) - TOP_N) + ' kernel groups)':<80} "
f"{other_count:<8} {other_size_mb:<12.2f} {other_percentage:<8.2f}"
)
lines.append("")
lines.append("=" * 140)
lines.append("Individual Kernels (sorted by size) - Top 20")
lines.append("=" * 140)
lines.append(
f"{'Rank':<6} {'File':<40} {'Kernel Name':<70} {'Size (KB)':<12} {'Size (MB)':<12} {'%':<8}"
)
lines.append("-" * 140)
for i, kernel in enumerate(sorted_kernels[:TOP_N], 1):
percentage = (kernel["size"] / total_size * 100) if total_size > 0 else 0
kernel_name = kernel["name"]
if len(kernel_name) > 67:
kernel_name = kernel_name[:64] + "..."
file_name = kernel["file"]
if len(file_name) > 37:
file_name = file_name[:34] + "..."
lines.append(
f"{i:<6} {file_name:<40} {kernel_name:<70} "
f"{kernel['size_kb']:<12.2f} {kernel['size_mb']:<12.4f} {percentage:<8.2f}"
)
if len(sorted_kernels) > TOP_N:
other_size = sum(k["size"] for k in sorted_kernels[TOP_N:])
other_count = len(sorted_kernels) - TOP_N
other_percentage = (other_size / total_size * 100) if total_size > 0 else 0
other_size_kb = other_size / 1024
other_size_mb = other_size / 1024 / 1024
lines.append(
f"{'Other':<6} {'(remaining ' + str(other_count) + ' kernels)':<40} "
f"{'':<70} {other_size_kb:<12.2f} {other_size_mb:<12.4f} {other_percentage:<8.2f}"
)
report_text = "\n".join(lines)
with open(output_file, "w") as f:
f.write(report_text)
print(f"Report saved to: {output_file}")
def main():
parser = argparse.ArgumentParser(
description="Analyze CUDA kernel sizes in sgl-kernel whl file"
)
parser.add_argument("whl", type=str, help="Path to whl file")
parser.add_argument(
"--output", type=str, default="kernel_analysis.txt", help="Output report file"
)
args = parser.parse_args()
if not os.path.exists(args.whl):
print(f"Error: {args.whl} not found")
sys.exit(1)
all_kernels = analyze_whl(args.whl)
if all_kernels:
generate_report(all_kernels, args.output)
else:
print("No kernel information extracted")
if __name__ == "__main__":
main()
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