hakmem/PHASE4_STEP1_COMPLETE.md

# Phase 4-Step1: PGO Workflow - COMPLETE ✓

**Date**: 2025-11-29
**Status**: ✅ Complete
**Performance Gain**: +6.25% (57.0 → 60.6 M ops/s)

---

## Summary

Phase 4-Step1 implemented a fully automated PGO (Profile-Guided Optimization) workflow for the HAKMEM Tiny Front using the Box pattern. The implementation achieved a **+6.25% performance improvement** (within the expected +5-10% range) with zero code changes - pure compiler optimization.

---

## Implementation

### Box 1: PGO Profile Collection Box

**Purpose**: Automated, reproducible profile data collection
**Contract**: Execute representative workloads → Generate .gcda files

**Components**:
1. `scripts/box/pgo_tiny_profile_config.sh` - Workload configuration
2. `scripts/box/pgo_tiny_profile_box.sh` - Profile collection automation
3. Makefile PGO targets - Workflow orchestration

**Design Principles**:
- ✅ **Deterministic**: Fixed seeds (42) for reproducibility
- ✅ **Representative**: 5 workloads covering diverse allocation patterns
- ✅ **Automated**: Single command (`make pgo-tiny-full`) for complete workflow
- ✅ **Safe**: Validation checks, error detection, timeout protection
- ✅ **Observable**: Clear progress reporting, .gcda file verification

---

## Workload Design

The PGO profile collection uses **5 representative workloads** to capture diverse allocation patterns:

| Workload | Purpose | Key Characteristics |
|----------|---------|---------------------|
| `bench_random_mixed 5M 256 42` | Common case | Medium working set, balanced cache pressure |
| `bench_random_mixed 5M 128 42` | Hot path bias | Smaller working set, higher TLS cache hit rate |
| `bench_random_mixed 5M 512 42` | Cold path bias | Larger working set, more SuperSlab allocations |
| `bench_tiny_hot 16 100 60000` | Class 0 intensive | Smallest size class (16B) |
| `bench_tiny_hot 64 100 60000` | Class 3 intensive | Common small object size (64B) |

**Coverage**: The workloads exercise:
- Hot TLS SLL pop path (high-frequency allocations)
- Cold refill path (SuperSlab allocations)
- Multiple size classes (0, 3, and mixed)
- Varied cache pressure scenarios

---

## Makefile Targets

```makefile
# Step 1: Build instrumented binaries (-fprofile-generate)
make pgo-tiny-profile

# Step 2: Collect profile data (run workloads → .gcda files)
make pgo-tiny-collect

# Step 3: Build optimized binaries (-fprofile-use)
make pgo-tiny-build

# Full workflow: profile → collect → build → test
make pgo-tiny-full
```

**Default Goal**: The Makefile help target now includes PGO instructions (lines 18-23)

---

## Performance Results

### Baseline (No PGO)
```
Run 1: 57.04 M ops/s
Run 2: 57.14 M ops/s
Run 3: 56.95 M ops/s
Average: 57.04 M ops/s
```

### PGO-Optimized
```
Run 1: 60.49 M ops/s
Run 2: 60.68 M ops/s
Run 3: 60.66 M ops/s
Average: 60.61 M ops/s
```

### Improvement
```
Absolute: +3.57 M ops/s
Relative: +6.25%
Expected: +5-10% ✓
```

**Verification**: Latest test (after Makefile fix) confirmed **60.75 M ops/s** - consistent with expected performance.

---

## Technical Details

### Profile Data Collection

The `pgo_tiny_profile_box.sh` script implements a robust collection workflow:

1. **Binary Validation**
   - Checks binaries exist and are executable
   - Auto-fixes permissions if needed

2. **Profile Cleanup**
   - Removes old .gcda files to prevent stale data
   - Reports cleanup statistics

3. **Workload Execution**
   - Runs each workload with 30s timeout
   - Detects timeouts and failures
   - Fails fast on errors

4. **Profile Verification**
   - Confirms .gcda files were generated
   - Reports profile file count and locations
   - Detects missing -fprofile-generate flag

**Output**: 33 .gcda files (confirmed in latest run)

### Compiler Flags

```makefile
# Profile Generation (Step 1)
PROFILE_GEN_FLAGS = -fprofile-generate -flto

# Profile Use (Step 3)
PROFILE_USE_FLAGS = -fprofile-use -flto
```

**LTO**: Link-Time Optimization is enabled for both phases to maximize PGO effectiveness.

---

## Workflow Fix (2025-11-29)

**Issue**: Initial implementation had `pgo-tiny-build` calling the profile collection script, causing:
- Duplicate script execution
- Unclear separation of concerns
- Skipped `pgo-tiny-collect` in dependency chain

**Fix**: Cleaned up the workflow:
```makefile
# Before (broken):
pgo-tiny-full: pgo-tiny-profile pgo-tiny-build  # Missing collect!

# After (correct):
pgo-tiny-full: pgo-tiny-profile pgo-tiny-collect pgo-tiny-build
```

**Result**: Each target now has a single responsibility:
- `pgo-tiny-profile`: Build only
- `pgo-tiny-collect`: Collect only
- `pgo-tiny-build`: Build only
- `pgo-tiny-full`: Orchestrate all steps

---

## Help Target Update

The Makefile `help` target (lines 8-37) now includes:

```
Benchmarking (PGO-optimized, +6% faster):
  make pgo-tiny-full                - Full PGO workflow (~5-10 min)
                                      = Profile + Optimize + Test
  make pgo-tiny-profile             - Step 1: Build profile binaries
  make pgo-tiny-collect             - Step 2: Collect profile data
  make pgo-tiny-build               - Step 3: Build optimized

Phase 4 Performance:
  Baseline:      57.0 M ops/s
  PGO-optimized: 60.6 M ops/s (+6.25%)

TIP: For best performance, use 'make pgo-tiny-full'
```

This ensures developers won't forget how to use PGO builds.

---

## Artifacts

### New Files
- `scripts/box/pgo_tiny_profile_config.sh` - Workload definitions
- `scripts/box/pgo_tiny_profile_box.sh` - Collection automation
- `PHASE4_STEP1_COMPLETE.md` - This completion report

### Modified Files
- `Makefile` (lines 8-37) - Help target with PGO instructions
- `Makefile` (lines 1305-1356) - PGO workflow targets

### Documentation
- `CURRENT_TASK.md` - Phase 4 roadmap
- `docs/design/PHASE4_TINY_FRONT_BOX_DESIGN.md` - Complete Box design

---

## Box Pattern Compliance

✅ **Single Responsibility**: Profile collection is a separate Box
✅ **Clear Contract**: Workloads → .gcda files → Optimized binaries
✅ **Observable**: Progress reporting, error detection, summary statistics
✅ **Safe**: Validation, timeouts, fail-fast on errors
✅ **Testable**: Deterministic seeds for reproducibility

---

## Next Steps

### Phase 4-Step2: Hot/Cold Path Box
- **Target**: +10-15% improvement (60.6 → 70.0 M ops/s)
- **Approach**: Separate hot (inline, likely) and cold (noinline, unlikely) paths
- **Design**: Already specified in `PHASE4_TINY_FRONT_BOX_DESIGN.md`

### Phase 4-Step3: Front Config Box
- **Target**: +5-8% improvement (70.0 → 76.0 M ops/s)
- **Approach**: Compile-time config optimization
- **Design**: Already specified in design doc

**Overall Phase 4 Target**: 73-83 M ops/s (vs current 60.6 M ops/s)

---

## Lessons Learned

1. **PGO is high ROI**: +6.25% with zero code changes, ~30 minutes of work
2. **Representative workloads matter**: 5 diverse workloads > 1 simple workload
3. **Automation is critical**: Manual PGO workflows are error-prone
4. **Box pattern scales**: Profile collection fits the Box pattern naturally
5. **Help targets prevent forgetting**: Make workflows discoverable

---

## Conclusion

Phase 4-Step1 successfully implemented PGO optimization using the Box pattern, achieving **+6.25% performance improvement** (57.0 → 60.6 M ops/s) with:
- ✅ Fully automated workflow (`make pgo-tiny-full`)
- ✅ Reproducible results (deterministic seeds)
- ✅ Clear documentation (help target, design doc)
- ✅ Robust error handling (validation, timeouts)
- ✅ Within expected range (+5-10%)

**Status**: Ready to proceed to Phase 4-Step2 (Hot/Cold Path Box)

---

**Signed**: Claude (2025-11-29)
**Commit**: TBD (pending git commit)