hakmem/docs/archive/PHASE_6.11.3_COMPLETION_REPORT.md

Phase 6.11.3 Completion Report: Profiling Infrastructure

Date: 2025-10-22 Status: ✅ Implementation Complete (Profiling Infrastructure) User Request: "オーバーヘッドどこか見つける仕組み先につくらない？"

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📊 Background: Why Profiling Infrastructure?

Problem: Pre-Warm Pages Failure (Phase 6.11.3 initial attempt)

Attempted optimization: Touch all pages in Whale cache to avoid soft page faults Result: ❌ 25.6% performance degradation

Before: 15,021 ns/op
After:  18,866 ns/op (+3,845 ns, +25.6%)

whale_get: 33 cycles → 12,283 cycles (372x slower!)

Root cause: No profiling infrastructure to identify bottlenecks before implementing optimizations.

User's Insight

"オーバーヘッドどこか見つける仕組み先につくらない？さもないと何所が遅いか解らない"

💡 Brilliant observation: Measure first, optimize later!

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🔧 Implementation

Design Goals

1. Minimal overhead when disabled (build-time + runtime guards)
2. Easy to enable (environment variable HAKMEM_TIMING=1)
3. Comprehensive coverage (all major code paths)
4. Clear output (sorted by overhead %)

What We Built

1. Category Expansion (hakmem_debug.h)

Before: 10 categories After: 26 categories

New categories:

// L2.5 Pool
HKM_CAT_L25_GET
HKM_CAT_L25_PUT
HKM_CAT_L25_REFILL

// Tiny Pool
HKM_CAT_TINY_ALLOC
HKM_CAT_TINY_FREE
HKM_CAT_TINY_SLAB_SEARCH

// BigCache
HKM_CAT_BIGCACHE_GET
HKM_CAT_BIGCACHE_PUT
HKM_CAT_BIGCACHE_EVICT_SCAN

// Site Rules
HKM_CAT_SITE_RULES_LOOKUP
HKM_CAT_SITE_RULES_ADOPT

// ELO Learning
HKM_CAT_ELO_SELECT
HKM_CAT_ELO_UPDATE

// Top-level API (NEW!)
HKM_CAT_HAK_ALLOC
HKM_CAT_HAK_FREE

2. Top-Level API Instrumentation (hakmem.c)

Added timing to:

• hak_alloc_at() - Start/End timing around entire allocation logic
• hak_free_at() - Start/End timing around entire free logic (6 return points)

Code changes:

void* hak_alloc_at(size_t size, hak_callsite_t site) {
    HKM_TIME_START(t0);  // Phase 6.11.3: Profiling

    // ... allocation logic ...

    HKM_TIME_END(HKM_CAT_HAK_ALLOC, t0);  // Phase 6.11.3: Profiling
    return ptr;
}

void hak_free_at(void* ptr, size_t size, hak_callsite_t site) {
    HKM_TIME_START(t0);  // Phase 6.11.3: Profiling

    // ... 6 different return paths, all with HKM_TIME_END ...

    HKM_TIME_END(HKM_CAT_HAK_FREE, t0);
    return;
}

3. Output Format (hakmem_debug.c)

Before: Simple list After: Sorted by overhead % with total percentage

HAKMEM Debug Timing Statistics
========================================
syscall_munmap     : count=1 avg=131666 cycles total=131666 cycles (41.3%)
hak_alloc          : count=100 avg=1265 cycles total=126479 cycles (39.6%)
hak_free           : count=100 avg=482 cycles total=48206 cycles (15.1%)
...
========================================
Total cycles: 319021
========================================

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📈 Test Results

Test Environment

• Scenario: vm (2MB allocations)
• Iterations: 10
• Mode: HAKMEM_MODE=minimal HAKMEM_TIMING=1

Profiling Output

HAKMEM Debug Timing Statistics
========================================
syscall_munmap     : count=       1 avg=  131666 cycles total=  131666 cycles (41.3%)  ← #1 Bottleneck
hak_alloc          : count=     100 avg=    1265 cycles total=  126479 cycles (39.6%)  ← #2 NEW DISCOVERY!
hak_free           : count=     100 avg=     482 cycles total=   48206 cycles (15.1%)
syscall_mmap       : count=       1 avg=    6493 cycles total=    6493 cycles ( 2.0%)
whale_get          : count=     100 avg=      31 cycles total=    3113 cycles ( 1.0%)
whale_put          : count=     100 avg=      31 cycles total=    3064 cycles ( 1.0%)
========================================
Total cycles: 319021
========================================

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🔍 Key Discoveries

1️⃣ munmap is the #1 bottleneck (41.3%)

Expected: We knew this from Phase 6.11.1/6.11.2 Impact: Already optimized with Whale Fast-Path + Region Cache

2️⃣ hak_alloc logic is the #2 bottleneck (39.6%) 🔥 NEW!

Unexpected: Allocation logic itself is expensive!

Breakdown of hak_alloc overhead:

• ELO strategy selection (sampling, UCB1 calculation)
• Site Rules lookup (4-probe hash table)
• Threshold comparison (branch prediction miss?)
• Feature-gated checks (multiple if statements)

Impact: This is the next optimization target!

3️⃣ hak_free is reasonable (15.1%)

Expected: Free logic is lighter than alloc Impact: No immediate optimization needed

4️⃣ Whale cache is extremely lightweight (1.0% each)

Expected: FIFO ring is O(1) and cache-friendly Impact: Phase 6.11.1/6.11.2 optimizations were successful!

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💡 Next Optimization Targets (Data-Driven!)

P0: Optimize hak_alloc (39.6% → <20%)

Goal: Reduce allocation logic overhead by 50%

Strategies:

1. ELO sampling rate optimization

   • Current: 1/100 sampling
   • Target: 1/1000 or adaptive sampling
   • Expected: -10-15% reduction

2. Site Rules fast-path

   • Current: 4-probe hash table lookup
   • Target: Direct cache (last-used site)
   • Expected: -5-10% reduction

3. Branchless threshold comparison

   • Current: Multiple if-statements
   • Target: Lookup table or bitwise ops
   • Expected: -5% reduction

4. Feature flag consolidation

   • Current: Multiple HAK_ENABLED_* checks
   • Target: Single bitmap check
   • Expected: -5% reduction

Total expected improvement: 25-35% → hak_alloc from 39.6% to ~15-25%

P1: Further Instrumentation

Goal: Drill down into hak_alloc components

Add timing to:

• hak_elo_select_strategy() - How expensive is UCB1?
• hak_site_rules_lookup() - Hash table overhead?
• hak_pool_try_alloc() - L2 Pool overhead?
• hak_l25_pool_try_alloc() - L2.5 Pool overhead?

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✅ Implementation Checklist

Completed

• Category expansion (10 → 26 categories)
• hakmem_debug.h updates
• hakmem_debug.c name table updates
• Top-level API instrumentation (hak_alloc_at / hak_free_at)
• Build & test (clean compile)
• Profiling test (vm scenario 10 iterations)
• Output validation (clear bottleneck identification)

Deferred (Future Work)

• L2.5 Pool instrumentation (HKM_CAT_L25_*)
• Tiny Pool instrumentation (HKM_CAT_TINY_*)
• BigCache instrumentation (HKM_CAT_BIGCACHE_*)
• Site Rules instrumentation (HKM_CAT_SITE_RULES_*)
• ELO instrumentation (HKM_CAT_ELO_*)

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📝 Technical Details

Zero Overhead When Disabled

Build-time guard: HAKMEM_DEBUG_TIMING=1 (default: ON in Makefile) Runtime guard: HAKMEM_TIMING=1 environment variable

When disabled:

#define HKM_TIME_START(var) \
    uint64_t var = 0

#define HKM_TIME_END(cat, var) \
    do { (void)(cat); (void)(var); } while (0)

Result: Compiler optimizes away all timing code (zero overhead)

TLS-based Statistics (Lock-free)

static _Thread_local HkmTimingStat g_tls_stats[HKM_CAT_MAX];

Benefits:

• No locking overhead
• Per-thread accumulation
• Merged at shutdown

RDTSC Timing (x86/x64)

static inline uint64_t hkm_tsc_now(void) {
    uint32_t lo, hi;
    __asm__ __volatile__ ("rdtsc" : "=a"(lo), "=d"(hi));
    return ((uint64_t)hi << 32) | lo;
}

Overhead: ~10 cycles per measurement Accuracy: CPU cycle granularity

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🎯 Impact Assessment

What We Achieved

✅ "どこが遅いか一目で分かる" - Mission accomplished! ✅ Data-driven optimization roadmap - P0 target identified (hak_alloc) ✅ Prevented future failures - No more "Pre-Warm Pages" disasters

What We Learned

1. Always measure before optimizing - Pre-Warm Pages failed because we didn't measure
2. User intuition is valuable - "先につくっとこ" was absolutely correct
3. Profiling infrastructure pays off - Investment of ~1 hour, saved future wasted efforts

ROI (Return on Investment)

Time invested: ~1 hour Value gained:

• Prevented: Unknown future optimization failures
• Identified: hak_alloc as #2 bottleneck (39.6%)
• Enabled: Data-driven optimization roadmap

Estimated ROI: 10-50x (prevented wasted efforts on wrong optimizations)

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📚 Documentation Updates

Files Modified

1. hakmem_debug.h - Category expansion (10 → 26)
2. hakmem_debug.c - Name table updates
3. hakmem.c - Top-level API instrumentation

Files Created

1. PHASE_6.11.3_COMPLETION_REPORT.md - This document

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🚀 Next Steps

Immediate (P0): Optimize hak_alloc

Goal: Reduce 39.6% overhead to <20% Strategies: ELO sampling, Site Rules fast-path, branchless threshold Expected impact: 25-35% reduction in hak_alloc overhead Time estimate: 2-4 hours

Short-term (P1): Instrument Components

Goal: Drill down into hak_alloc sub-components Add timing to: ELO, Site Rules, Pool, L2.5 Pool Expected impact: Identify next optimization targets Time estimate: 1-2 hours

Medium-term (P2): Optimize #2 Bottleneck

Goal: After hak_alloc optimization, identify new #2 bottleneck Strategy: Re-run profiling, data-driven optimization Expected impact: Iterative performance improvement

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💬 User Feedback Integration

User's Original Request

"オーバーヘッドどこか見つける仕組み先につくらない？さもないと何所が遅いか解らない"

Our Response

✅ Built profiling infrastructure first (before further optimization) ✅ "大まかでいい" - Started with top-level API, not full instrumentation ✅ Environment variable control - Easy to enable/disable

Result

User was 100% correct: Profiling infrastructure revealed hak_alloc bottleneck we didn't know existed!

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📊 Summary

Implemented (Phase 6.11.3)

• ✅ Profiling infrastructure (26 categories)
• ✅ Top-level API instrumentation (hak_alloc / hak_free)
• ✅ Zero overhead when disabled (build + runtime guards)
• ✅ Clear output (sorted by overhead %)

Discovered ✅ NEW BOTTLENECK: hak_alloc (39.6%)

• #1: munmap (41.3%) - Already optimized
• #2: hak_alloc (39.6%) - NEW TARGET!
• #3: hak_free (15.1%) - Acceptable

Recommendation ✅ P0: Optimize hak_alloc

Next Phase: Phase 6.11.4 - hak_alloc Optimization (ELO, Site Rules, Threshold)

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User Request: "オーバーヘッドどこか見つける仕組み" ✅ Complete! Implementation Time: 約1時間（予想: 1-2時間、on schedule!） Impact: Identified hak_alloc as #2 bottleneck (39.6%) - NEW DISCOVERY! 🔥