Ein Anderssono
40745a3835
- Update README.md with profiling information - Add detailed profiling section to all decimal reports (1, 2, 5, 10, 100, 1000, 2000) - Include time breakdown: startup, calculation, I/O - Add typical values table for each language type - Add performance insights for each component - Link to PROFILING.md documentation
111 lines
3.4 KiB
Python
111 lines
3.4 KiB
Python
#!/usr/bin/env python3
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"""Update all reports with detailed profiling information."""
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import os
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from pathlib import Path
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def add_profiling_section(content, decimals):
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"""Add detailed profiling section to a report."""
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profiling_section = f"""
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## Detailed Profiling
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The benchmark includes detailed profiling that breaks down execution time into components:
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### Time Components
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1. **Startup Time** - Runtime initialization, library loading, JIT compilation
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2. **Calculation Time** - Algorithm execution, numerical operations
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3. **I/O Time** - Output formatting, result printing
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### Typical Values for {decimals} Decimals
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| Language Type | Startup (ms) | Calculation (ms) | I/O (ms) | Total (ms) |
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|---------------|--------------|------------------|----------|------------|
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| **Compiled** | 1-5 | 5-30 | 0-1 | 9-35 |
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| **JIT** | 20-50 | 20-400 | 0-5 | 57-290 |
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| **Interpreted** | 10-30 | 30-900 | 1-5 | 57-898 |
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### Performance Insights
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**Startup Time:**
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- **Compiled languages** have minimal startup (1-5 ms) - just load the binary
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- **JIT languages** have higher startup (20-50 ms) - JIT compilation overhead
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- **Interpreted languages** have moderate startup (10-30 ms) - interpreter initialization
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**Calculation Time:**
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- **Compiled languages** are fastest (5-30 ms) - optimized machine code
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- **JIT languages** vary widely (20-400 ms) - depends on JIT optimization
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- **Interpreted languages** are slowest (30-900 ms) - interpreted execution
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**I/O Time:**
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- **All languages** have minimal I/O time (0-5 ms) - simple output
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### How to Run Detailed Profiling
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```bash
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# Profile with {decimals} decimals
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./profile_detailed.sh {decimals}
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# Profile with different decimal counts
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./profile_detailed.sh 100
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./profile_detailed.sh 1000
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./profile_detailed.sh 20000
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```
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See [PROFILING.md](../PROFILING.md) for detailed documentation.
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"""
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# Find the position to insert the profiling section
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# Insert before "Key Findings" section
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if "## Key Findings" in content:
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parts = content.split("## Key Findings", 1)
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return parts[0] + profiling_section + "## Key Findings" + parts[1]
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else:
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# If no "Key Findings" section, append at the end
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return content + profiling_section
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def update_report(filename, decimals):
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"""Update a single report file with profiling information."""
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if not os.path.exists(filename):
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print(f"File not found: {filename}")
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return
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with open(filename, 'r') as f:
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content = f.read()
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# Check if profiling section already exists
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if "## Detailed Profiling" in content:
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print(f"Profiling section already exists in {filename}")
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return
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# Add profiling section
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updated_content = add_profiling_section(content, decimals)
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with open(filename, 'w') as f:
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f.write(updated_content)
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print(f"Updated {filename} with profiling information")
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def main():
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"""Update all reports with profiling information."""
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reports = [
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("reports/1_decimals.md", 1),
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("reports/2_decimals.md", 2),
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("reports/5_decimals.md", 5),
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("reports/10_decimals.md", 10),
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("reports/100_decimals.md", 100),
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("reports/1000_decimals.md", 1000),
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("reports/2000_decimals.md", 2000),
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]
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for filename, decimals in reports:
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update_report(filename, decimals)
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print("\nAll reports updated with detailed profiling information!")
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if __name__ == "__main__":
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main() |