- Created performance charts for all decimal levels (1, 2, 5, 10, 100, 1000, 2000)
- Added 4 charts per report: execution time, memory usage, IPC efficiency, and time vs memory trade-off
- Updated all reports to include visualizations
- Charts show top 20 languages for each metric
- Color-coded by language type (Compiled=green, JIT=blue, Interpreted=red)
- Added instructions, cycles, and IPC metrics to all reports
- Created CSV data files for each language with detailed metrics
- Added timeline data (memory and CPU over time) for each run
- Updated all reports with new metrics
- Created analysis script to analyze collected data
- Generated reports for all decimal levels (1, 2, 5, 10, 100, 1000, 2000)
Key findings:
- D has highest IPC (4.00) - most efficient CPU usage
- Crystal is fastest (22ms) - faster than C and C++
- Assembly is most memory efficient (1.4MB)
- Rust and Fortran have IPC 3.11 - good optimization
- Updated update_reports.sh to remove Performance Analysis section
- Regenerated all reports (1, 2, 5, 10, 100, 1000, 2000 decimals)
- All reports now have identical structure for 100% comparability
- No language-specific observations or commentary
- Only raw data tables remain
- Fixed incorrect data in all report files
- Now using actual test results from run_*_output.txt
- Proper ranking sorted by time, then memory
- All languages included with correct values
- Fixed memory values (no more 0 bytes for Rust, Nim, Odin)
- Consistent formatting across all reports
Reports updated:
- 1_decimals.md
- 2_decimals.md
- 5_decimals.md
- 10_decimals.md
- 100_decimals.md
- 1000_decimals.md
- 2000_decimals.md
All reports now show:
- Correct execution times
- Correct memory usage in bytes
- Proper ranking (1-32, no duplicates)
- Language type classification
- Create improved profiling script with realistic startup estimates
- Generate Gantt charts for each language showing time breakdown
- Update reports with actual profiling measurements
- Show startup, calculation, and I/O time percentages
- Use real data from profiling runs (100 decimals)
- 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
- Create detailed reports for 1, 2, 5, 10, 100, 1000, 2000 decimals
- Include all languages in summary table
- Add performance charts by category (compiled, JIT, interpreted)
- Add individual language analysis with memory usage over time charts
- Use actual data from timeline files
- Identical structure across all decimal levels
- Create reports/ directory with detailed performance reports
- Simplify README.md to provide overview and summary
- Add links to detailed reports for each decimal level (1, 2, 5, 10, 100, 1000, 2000)
- Keep summary table and key findings in main README
- Remove verbose charts from main README to reduce noise
Ein Anderssono