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https://github.com/ROCm/composable_kernel.git
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Improve benchmarking scripts.
This commit is contained in:
Ville Pietilä
118
benchmarking/demangle-names.py
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118
benchmarking/demangle-names.py
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@@ -0,0 +1,118 @@
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#!/usr/bin/env python3
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import subprocess
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import sys
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from bs4 import BeautifulSoup
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import re
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import json
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def get_mangled_kernel_names_from_html(html_file):
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with open(html_file, 'r') as f:
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html_content = f.read()
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# Parse with BeautifulSoup to find the right script tag
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soup = BeautifulSoup(html_content, 'html.parser')
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script_tags = soup.find_all('script')
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for i, script in enumerate(script_tags):
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if script.string:
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# Look for scripts containing our kernel signature strings
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if 'tensor_operation' in script.string and 'device' in script.string:
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print(f"Found kernel data in script tag {i}")
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# Now extract the data array from this specific script
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match = re.search(r'var\s+data\s*=\s*(\[.*?\]);', script.string, re.DOTALL)
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if match:
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try:
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data_str = match.group(1)
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data = json.loads(data_str)
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# Extract kernel names
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kernel_names = [item['name'] for item in data]
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print(f"Found {len(kernel_names)} kernel names:")
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for name in kernel_names:
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print(f" {name}")
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return kernel_names
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except json.JSONDecodeError as e:
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print(f"Error parsing JSON: {e}")
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# Continue to next script tag
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print("Could not find kernel data in any script tag")
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return []
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def de_mangle_name(mangled):
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demangler = '/opt/rocm/llvm/bin/llvm-cxxfilt'
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try:
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result = subprocess.run(
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[demangler],
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input=mangled,
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text=True,
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capture_output=True,
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check=True
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)
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demangled = result.stdout.strip()
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if demangled and demangled != mangled:
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return demangled
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except (FileNotFoundError, subprocess.CalledProcessError) as e:
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print(f"Error using {demangler}: {e}")
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return None
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def extract_instance_name(demangled, prefix, prefix_instance):
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if not demangled.startswith(prefix + prefix_instance):
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return None
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# Start after the prefix
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start = len(prefix + prefix_instance)
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# Track angle bracket depth to find matching closing bracket
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depth = 1 # We already counted the opening '<' from prefix
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i = start
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while i < len(demangled) and depth > 0:
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if demangled[i] == '<':
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depth += 1
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elif demangled[i] == '>':
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depth -= 1
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i += 1
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if depth == 0:
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# Extract from start to just before the matching '>'
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return prefix_instance + demangled[start:i]
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return None
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def extract_GridwiseGemmMultiD_xdl_cshuffle_v3(demangled):
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prefix = "void ck::tensor_operation::device::(anonymous namespace)::kernel_grouped_conv_fwd_xdl_cshuffle_v3<"
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prefix_instance = "ck::GridwiseGemmMultiD_xdl_cshuffle_v3<"
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return extract_instance_name(demangled, prefix, prefix_instance)
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def extract_GridwiseGemmMultiD_xdl_cshuffle(demangled):
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prefix = "void ck::tensor_operation::device::(anonymous namespace)::kernel_grouped_conv_fwd_xdl_cshuffle<"
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prefix_instance = "ck::GridwiseGemmMultiD_xdl_cshuffle<"
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return extract_instance_name(demangled, prefix, prefix_instance)
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if __name__ == "__main__":
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# get_mangled_kernel_names_from_html(sys.argv[1])
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# Mangled name is the first argument
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if len(sys.argv) > 1:
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mangled = sys.argv[1]
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demangled = de_mangle_name(mangled)
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print()
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print("Demangled name:")
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print(demangled)
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v3_instance_name = extract_GridwiseGemmMultiD_xdl_cshuffle_v3(demangled)
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if v3_instance_name:
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print()
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print("Extracted GridwiseGemmMultiD_xdl_cshuffle_v3 instance name:")
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print(v3_instance_name)
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v1_instance_name = extract_GridwiseGemmMultiD_xdl_cshuffle(demangled)
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if v1_instance_name:
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print()
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print("Extracted GridwiseGemmMultiD_xdl_cshuffle instance name:")
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print(v1_instance_name)
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else:
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print("Please provide a mangled name as an argument.")
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@@ -5,12 +5,16 @@ import subprocess
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import sys
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import argparse
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# Run under rocprof-compute
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# HIP_VISIBLE_DEVICES=7 rockprof-compute profile -n grouped_conv_fwd --roofline-data-type FP16 -- ./run-best-instances.py --profiler-path ../build-improved-convs/bin/ckProfiler
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# Set no verify, and timing of the kernel. Multiple calls of the same kernel inside the script will confuse the profiler.
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profiler_commands = [
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"1 1 1 0 1 0 1 2 32 32 4 4 3 3 200 200 1 1 1 1 1 1 1 1",
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"1 1 1 0 1 0 1 2 32 32 8 8 3 3 200 200 2 2 1 1 1 1 1 1",
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#"1 1 1 0 1 0 1 2 32 32 8 8 3 3 100 100 1 2 1 1 1 1 1 1",
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"1 1 1 0 1 0 1 2 1 32 2376 256 3 3 100 100 1 1 1 1 1 1 1 1",
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#"1 1 1 0 1 0 1 2 1 32 256 256 3 3 100 100 1 1 1 1 1 1 1 1"
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"1 1 1 0 1 0 0 2 32 32 4 4 3 3 200 200 1 1 1 1 1 1 1 1",
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"1 1 1 0 1 0 0 2 32 32 8 8 3 3 200 200 2 2 1 1 1 1 1 1",
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#"1 1 1 0 1 0 0 2 32 32 8 8 3 3 100 100 1 2 1 1 1 1 1 1",
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"1 1 1 0 1 0 0 2 1 32 2376 256 3 3 100 100 1 1 1 1 1 1 1 1",
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#"1 1 1 0 1 0 0 2 1 32 256 256 3 3 100 100 1 1 1 1 1 1 1 1"
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]
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baseline_instances = [
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