hakmem/docs/analysis/OVERHEAD_ANALYSIS_PLAN.md

hakmem Overhead Analysis Plan (Phase 6.7 準備)

Gap: hakmem-evolving (37,602 ns) vs mimalloc (19,964 ns) = +88.3%

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🎯 Overhead 候補（優先度順）

P0: Critical Path Overhead

1. BigCache lookup (毎回実行)

   • Hash table lookup for site_id
   • Size class matching
   • Slot iteration
   • 推定コスト: 50-100 ns

2. ELO strategy selection (LEARN mode)

   • hak_elo_select_strategy(): softmax calculation
   • 12 strategies の確率計算
   • Random number generation
   • 推定コスト: 100-200 ns

3. Header read/write

   • AllocHeader (32 bytes) の read/write
   • Magic verification
   • 推定コスト: 10-20 ns

4. Atomic tick counter

   • atomic_fetch_add(&tick_counter, 1)
   • Every allocation
   • 推定コスト: 5-10 ns

P1: Syscall Overhead

5. mmap/munmap

   • System call overhead
   • TLB flush
   • Page table updates
   • 推定コスト: 1,000-5,000 ns (syscall dependent)

6. Page faults

   • First touch of mmap'd memory
   • Soft page faults
   • 推定コスト: 100-500 ns per page

P2: Other Overhead

7. Evolution lifecycle

   • hak_evo_tick() (every 1024 allocs)
   • hak_evo_record_size() (every alloc)
   • 推定コスト: 5-10 ns

8. Batch madvise

   • Batch add/flush overhead
   • 推定コスト: Amortized, should be near-zero

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🔬 Measurement Strategy

Phase 1: Feature Isolation

Test configurations (environment variables):

1. Baseline: All features ON (current)
2. No BigCache: HAKMEM_DISABLE_BIGCACHE=1
3. No ELO: HAKMEM_DISABLE_ELO=1 (use fixed threshold)
4. Frozen mode: HAKMEM_EVO_POLICY=frozen (skip learning)
5. Minimal: BigCache + ELO + Evolution すべて OFF

Expected results:

• If "No BigCache" → -100ns: BigCache overhead = 100ns
• If "No ELO" → -200ns: ELO overhead = 200ns
• If "Minimal" → -500ns: Total feature overhead = 500ns
• Remaining gap (~17,000 ns) → syscall/page fault overhead

Phase 2: Profiling

# Compile with debug symbols
make clean && make CFLAGS="-g -O2"

# Run with perf
perf record -g ./bench_allocators --allocator hakmem-evolving --scenario vm --iterations 100
perf report

# Look for:
- hak_alloc_at() time breakdown
- hak_bigcache_try_get() cost
- hak_elo_select_strategy() cost
- mmap/munmap syscall time

Phase 3: Syscall Analysis

# Count syscalls
strace -c ./bench_allocators --allocator hakmem-evolving --scenario vm --iterations 10

# Compare with mimalloc
strace -c -o hakmem.strace ./bench_allocators --allocator hakmem-evolving --scenario vm --iterations 10
strace -c -o mimalloc.strace ./bench_allocators --allocator mimalloc --scenario vm --iterations 10

diff hakmem.strace mimalloc.strace

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🎯 Expected Findings

Hypothesis 1: BigCache overhead = 5-10%

• Hash lookup + slot iteration
• Negligible compared to total gap

Hypothesis 2: ELO overhead = 5-10%

• Softmax calculation
• Can be eliminated in FROZEN mode

Hypothesis 3: mmap/munmap overhead = 60-70%

• System call overhead
• Page fault overhead
• This is the main gap
• Solution: Reduce mmap/munmap calls (already doing with BigCache)

Hypothesis 4: Remaining gap = mimalloc's slab allocator

• mimalloc uses slab allocator for 2MB
• Pre-allocated, no syscalls
• hakmem uses mmap per allocation (first miss)
• Can't compete without similar architecture

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💡 Optimization Ideas (Phase 6.7+)

1. FROZEN mode by default (after learning)

   • Zero ELO overhead
   • -5% improvement

2. BigCache optimization

   • Direct indexing instead of linear search
   • -5% improvement

3. Pre-allocated arena (Phase 7?)

   • mmap large arena once
   • Suballocate from arena
   • Avoid per-allocation syscalls
   • Target: -50% improvement

4. Header optimization

   • Reduce AllocHeader size (32 → 16 bytes?)
   • Use bit packing
   • -2% improvement

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📊 Success Metrics

Phase 6.7 Goal: Identify top 3 overhead sources Phase 7 Goal: Reduce gap to +40% (vs +88% now) Phase 8 Goal: Reduce gap to +20% (competitive)

Realistic limit: Cannot beat mimalloc without slab allocator

• mimalloc: Industry-standard, 10+ years of optimization
• hakmem: Research PoC, 2 months of development
• Target: Within 20-30% is acceptable for PoC