P-Tier + Tiny Route Policy: Aggressive Superslab Management + Safe Routing

## Phase 1: Utilization-Aware Superslab Tiering (案B実装済)

- Add ss_tier_box.h: Classify SuperSlabs into HOT/DRAINING/FREE based on utilization
  - HOT (>25%): Accept new allocations
  - DRAINING (≤25%): Drain only, no new allocs
  - FREE (0%): Ready for eager munmap

- Enhanced shared_pool_release_slab():
  - Check tier transition after each slab release
  - If tier→FREE: Force remaining slots to EMPTY and call superslab_free() immediately
  - Bypasses LRU cache to prevent registry bloat from accumulating DRAINING SuperSlabs

- Test results (bench_random_mixed_hakmem):
  - 1M iterations: ✅ ~1.03M ops/s (previously passed)
  - 10M iterations: ✅ ~1.15M ops/s (previously: registry full error)
  - 50M iterations: ✅ ~1.08M ops/s (stress test)

## Phase 2: Tiny Front Routing Policy (新規Box)

- Add tiny_route_box.h/c: Single 8-byte table for class→routing decisions
  - ROUTE_TINY_ONLY: Tiny front exclusive (no fallback)
  - ROUTE_TINY_FIRST: Try Tiny, fallback to Pool if fails
  - ROUTE_POOL_ONLY: Skip Tiny entirely

- Profiles via HAKMEM_TINY_PROFILE ENV:
  - "hot": C0-C3=TINY_ONLY, C4-C6=TINY_FIRST, C7=POOL_ONLY
  - "conservative" (default): All TINY_FIRST
  - "off": All POOL_ONLY (disable Tiny)
  - "full": All TINY_ONLY (microbench mode)

- A/B test results (ws=256, 100k ops random_mixed):
  - Default (conservative): ~2.90M ops/s
  - hot: ~2.65M ops/s (more conservative)
  - off: ~2.86M ops/s
  - full: ~2.98M ops/s (slightly best)

## Design Rationale

### Registry Pressure Fix (案B)
- Problem: DRAINING tier SS occupied registry indefinitely
- Solution: When total_active_blocks→0, immediately free to clear registry slot
- Result: No more "registry full" errors under stress

### Routing Policy Box (新)
- Problem: Tiny front optimization scattered across ENV/branches
- Solution: Centralize routing in single table, select profiles via ENV
- Benefit: Safe A/B testing without touching hot path code
- Future: Integrate with RSS budget/learning layers for dynamic profile switching

## Next Steps (性能最適化)
- Profile Tiny front internals (TLS SLL, FastCache, Superslab backend latency)
- Identify bottleneck between current ~2.9M ops/s and mimalloc ~100M ops/s
- Consider:
  - Reduce shared pool lock contention
  - Optimize unified cache hit rate
  - Streamline Superslab carving logic

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

core/box/ss_allocation_box.c

@@ -184,6 +184,9 @@ SuperSlab* superslab_allocate(uint8_t size_class) {
     ss->magic = SUPERSLAB_MAGIC;
     ss->active_slabs = 0;
     ss->lg_size = lg;  // Phase 8.3: Use ACE-determined lg_size (20=1MB, 21=2MB)
+
+    // P-Tier: Initialize tier to HOT (normal operation, eligible for allocation)
+    atomic_store_explicit(&ss->tier, SS_TIER_HOT, memory_order_relaxed);
     ss->slab_bitmap = 0;
     ss->nonempty_mask = 0;  // Phase 6-2.1: ChatGPT Pro P0 - init nonempty mask
     ss->freelist_mask = 0;  // P1.1 FIX: Initialize freelist_mask