COG-GTM
diff --git a/‎.github/workflows/performance-regression.yml‎
Lines changed: 434 additions & 0 deletions b/‎.github/workflows/performance-regression.yml‎
Lines changed: 434 additions & 0 deletions
diff --git a/‎docs/performance-regression-testing.md‎
Lines changed: 366 additions & 0 deletions b/‎docs/performance-regression-testing.md‎
Lines changed: 366 additions & 0 deletions
@@ -0,0 +1,366 @@
+# Performance Regression Testing
+
+This document describes the automated performance regression testing system for llama.cpp, implemented as part of JIRA ticket AT-105.
+
+## Overview
+
+The performance regression testing system automatically detects performance degradations in llama.cpp by comparing benchmark results against established baselines. It integrates with GitHub Actions CI/CD pipelines and provides automated alerts when performance regressions exceed a configurable threshold (default: 5%).
+
+## Components
+
+### 1. GitHub Actions Workflow
+
+**File:** `.github/workflows/performance-regression.yml`
+
+The workflow runs performance benchmarks on different hardware backends (CPU, CUDA, Metal) for every pull request and push to master. It:
+
+- Builds the `llama-bench` target
+- Downloads a test model (TinyLlama 1.1B)
+- Runs benchmarks with consistent parameters
+- Compares results against cached baselines
+- Posts results as PR comments
+- Fails the build if regressions are detected
+
+**Jobs:**
+- `performance-cpu`: Runs on Ubuntu with CPU backend
+- `performance-cuda`: Runs on GPU runners (disabled by default)
+- `performance-metal`: Runs on macOS with Apple Silicon
+
+**Triggers:**
+- Pull requests to any branch
+- Pushes to master branch
+- Manual workflow dispatch
+
+### 2. Performance Regression Detector
+
+**File:** `scripts/performance-regression-detector.py`
+
+Python script that analyzes benchmark results and detects performance regressions.
+
+**Usage:**
+```bash
+python3 scripts/performance-regression-detector.py \
+  --baseline baseline.sqlite \
+  --current current.sqlite \
+  --threshold 5.0 \
+  --output regression-report.md
+```
+
+**Features:**
+- Compares multiple performance metrics (tokens/second, latency)
+- Configurable regression threshold
+- Generates markdown and JSON reports
+- Creates flag file when regressions detected
+- Integrates with existing llama-bench SQLite schema
+
+**Key Metrics:**
+- `avg_ts`: Average tokens per second (higher is better)
+- `avg_ns`: Average latency in nanoseconds (lower is better)
+- `model_size`: Model memory footprint (lower is better)
+
+### 3. Enhanced Comparison Script
+
+**File:** `scripts/compare-llama-bench.py` (enhanced)
+
+The existing comparison script has been extended with CI automation support.
+
+**New Features:**
+- `--ci-mode`: Enable CI-specific formatting and behavior
+- `--baseline-db`: Path to baseline database for tracking
+- `--save-baseline`: Save current results as new baseline
+- `--json-output`: Export comparison results to JSON
+
+**Example:**
+```bash
+python3 scripts/compare-llama-bench.py \
+  -i results.sqlite \
+  --ci-mode \
+  --json-output comparison.json
+```
+
+### 4. Database Schema Extensions
+
+**Files:**
+- `scripts/db-schema-migration.sql`: SQL migration script
+- `scripts/apply-db-migration.py`: Migration application tool
+
+The database schema has been extended to support:
+
+**New Tables:**
+- `performance_baselines`: Stores baseline snapshots
+- `performance_history`: Historical performance data
+- `regression_alerts`: Logged regression detections
+- `memory_leak_logs`: Memory leak monitoring results
+
+**Views:**
+- `latest_baselines`: Active baseline information
+- `regression_summary`: Aggregated regression statistics
+- `memory_leak_summary`: Memory leak detection summary
+
+**Applying Migrations:**
+```bash
+python3 scripts/apply-db-migration.py -d llama-bench.sqlite
+```
+
+### 5. Memory Leak Monitoring
+
+**File:** `scripts/memory-leak-monitor.py`
+
+Integrates with the existing `llama-memory.h` interfaces to detect memory leaks and excessive memory consumption.
+
+**Usage:**
+```bash
+python3 scripts/memory-leak-monitor.py \
+  --benchmark-output benchmark.log \
+  --test-log test.log \
+  --database results.sqlite \
+  --commit abc123 \
+  --report memory-report.md
+```
+
+**Features:**
+- Parses benchmark output for memory usage patterns
+- Detects memory leaks (threshold: 1 MB)
+- Monitors excessive memory usage (threshold: 16 GB)
+- Logs results to database
+- Generates markdown reports
+
+**Memory Status Codes** (from `llama-memory.h`):
+- `0`: `LLAMA_MEMORY_STATUS_SUCCESS`
+- `1`: `LLAMA_MEMORY_STATUS_NO_UPDATE`
+- `2`: `LLAMA_MEMORY_STATUS_FAILED_PREPARE`
+- `3`: `LLAMA_MEMORY_STATUS_FAILED_COMPUTE`
+
+### 6. CMake Test Integration
+
+**File:** `tests/CMakeLists.txt` (extended)
+
+A new performance test target has been added:
+
+```cmake
+llama_test_cmd(
+    ${CMAKE_BINARY_DIR}/bin/llama-bench
+    NAME test-performance-regression-cpu
+    LABEL "performance"
+    WORKING_DIRECTORY ${CMAKE_SOURCE_DIR}
+    ARGS -p 512 -n 128 -r 3 -o sql
+)
+```
+
+**Running Performance Tests:**
+```bash
+cd build
+ctest -L performance --verbose
+```
+
+## Workflow
+
+### For Pull Requests
+
+1. Developer opens a PR with code changes
+2. GitHub Actions triggers the performance regression workflow
+3. The workflow:
+   - Builds llama-bench with the PR code
+   - Restores the baseline database from cache
+   - If no baseline exists, creates one from the base commit
+   - Runs benchmarks with the current code
+   - Compares results using the regression detector
+4. Results are posted as a PR comment
+5. Build fails if regressions exceed 5% threshold
+
+### For Master Branch Commits
+
+1. Code is merged to master
+2. GitHub Actions runs the workflow
+3. Benchmark results are cached as the new baseline
+4. Historical data is stored in the database
+5. Future PRs compare against this baseline
+
+### Manual Baseline Management
+
+**Creating a Baseline:**
+```bash
+# Run benchmarks
+./build/bin/llama-bench -m model.gguf -p 512 -n 128 -r 3 -o sql | sqlite3 baseline.sqlite
+
+# Save as baseline
+python3 scripts/apply-db-migration.py -d baseline.sqlite
+sqlite3 baseline.sqlite "INSERT INTO performance_baselines (baseline_name, commit_sha, created_at) VALUES ('v1.0', '$(git rev-parse HEAD)', '$(date -Iseconds)')"
+```
+
+**Comparing Against Baseline:**
+```bash
+# Run current benchmarks
+./build/bin/llama-bench -m model.gguf -p 512 -n 128 -r 3 -o sql | sqlite3 current.sqlite
+
+# Detect regressions
+python3 scripts/performance-regression-detector.py \
+  --baseline baseline.sqlite \
+  --current current.sqlite \
+  --threshold 5.0
+```
+
+## Configuration
+
+### Environment Variables
+
+- `REGRESSION_THRESHOLD`: Regression detection threshold (default: 5.0)
+- `BASELINE_DB`: Baseline database filename (default: performance-baseline.sqlite)
+- `RESULTS_DB`: Results database filename (default: performance-results.sqlite)
+
+### Workflow Customization
+
+Edit `.github/workflows/performance-regression.yml` to:
+
+- Change benchmark parameters (prompt length, generation tokens, repetitions)
+- Add/remove backend configurations
+- Modify caching strategy
+- Adjust model selection
+
+### Threshold Configuration
+
+The default 5% threshold can be adjusted per-backend or per-metric:
+
+```python
+# In performance-regression-detector.py
+PERFORMANCE_METRICS = {
+    "avg_ts": {
+        "threshold": 5.0,  # Custom threshold for this metric
+        ...
+    }
+}
+```
+
+## Reports
+
+### Regression Report Format
+
+```markdown
+# Performance Regression Analysis Report
+
+**Generated:** 2025-09-29 12:34:56
+**Threshold:** 5.0%
+
+## Summary
+- Total Benchmarks Compared: 10
+- Regressions Found: 2
+- Improvements Found: 3
+- Stable Benchmarks: 5
+
+## ⚠️ Performance Regressions Detected
+
+### TinyLlama-1.1B | backend:CPU | p:512 | g:128
+
+⚠️ **Average Tokens/Second**:
+- Baseline: 45.23 tokens/s
+- Current: 42.15 tokens/s
+- Change: ↓ 6.81%
+
+...
+```
+
+### Memory Leak Report Format
+
+```markdown
+# Memory Leak Monitoring Report
+
+**Generated:** 2025-09-29 12:34:56
+
+## ⚠️ Memory Leaks Detected
+
+### benchmark
+- Initial Memory: 1234.56 MB
+- Final Memory: 1250.78 MB
+- Leaked: 16.22 MB
+```
+
+## Troubleshooting
+
+### No Baseline Available
+
+If the baseline cache is empty or expired:
+
+1. The workflow will attempt to build the baseline from the base commit
+2. If that fails, it will create a baseline from the current code
+3. Subsequent runs will use this baseline
+
+### False Positives
+
+Regressions can be marked as false positives in the database:
+
+```sql
+UPDATE regression_alerts 
+SET status = 'false_positive', notes = 'Expected due to architectural change'
+WHERE id = <alert_id>;
+```
+
+### Excessive Memory Usage Warnings
+
+If memory usage exceeds thresholds:
+
+1. Review the memory leak report
+2. Check for memory leaks using valgrind or similar tools
+3. Adjust the threshold if legitimate increased usage
+
+## Integration with CI/CD
+
+### GitHub Actions Artifacts
+
+The workflow uploads artifacts containing:
+- Regression reports (markdown)
+- SQLite databases (baseline and current)
+- Memory leak reports
+
+**Downloading Artifacts:**
+```bash
+gh run download <run-id> -n performance-report-cpu
+```
+
+### PR Comments
+
+The workflow automatically comments on PRs with:
+- Summary of regression detection
+- Links to detailed reports
+- Pass/fail status
+
+### Build Status
+
+The workflow sets the build status to:
+- ✅ **Success**: No regressions detected
+- ❌ **Failure**: Regressions exceed threshold
+- ⚠️ **Warning**: Issues detected but below threshold
+
+## Best Practices
+
+1. **Run locally before PR**: Test performance changes locally
+2. **Review memory reports**: Check for memory leaks regularly
+3. **Update baselines**: Refresh baselines after major changes
+4. **Monitor trends**: Use historical data to identify gradual degradation
+5. **Document exceptions**: Note expected performance changes in PR descriptions
+
+## Future Enhancements
+
+Potential improvements to the system:
+
+- [ ] Add GPU-specific benchmarks when runners available
+- [ ] Implement trend analysis over multiple commits
+- [ ] Add visualization dashboard for historical performance
+- [ ] Support for custom benchmark configurations per PR
+- [ ] Integration with performance profiling tools
+- [ ] Automatic bisection for regression identification
+- [ ] Multi-model benchmark comparisons
+
+## References
+
+- [llama-bench documentation](../tools/llama-bench/README.md)
+- [compare-llama-bench.py usage](../scripts/compare-llama-bench.py)
+- [llama-memory.h interface](../src/llama-memory.h)
+- [GitHub Actions workflows](../.github/workflows/)
+
+## Support
+
+For issues or questions:
+- Check existing GitHub issues
+- Review workflow run logs
+- Examine generated reports
+- Contact the performance testing team