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hakmem/core/hakmem_shared_pool_acquire.c

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#include "hakmem_shared_pool_internal.h"
#include "hakmem_debug_master.h"
#include "hakmem_stats_master.h"
#include "box/ss_slab_meta_box.h"
#include "box/ss_hot_cold_box.h"
#include "box/pagefault_telemetry_box.h"
#include "box/tls_sll_drain_box.h"
#include "box/tls_slab_reuse_guard_box.h"
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>
2025-12-04 18:01:25 +09:00
#include "box/ss_tier_box.h" // P-Tier: Tier filtering support
#include "hakmem_policy.h"
#include "hakmem_env_cache.h" // Priority-2: ENV cache
Implement Warm Pool Secondary Prefill Optimization (Phase B-2c Complete) Problem: Warm pool had 0% hit rate (only 1 hit per 3976 misses) despite being implemented, causing all cache misses to go through expensive superslab_refill registry scans. Root Cause Analysis: - Warm pool was initialized once and pushed a single slab after each refill - When that slab was exhausted, it was discarded (not pushed back) - Next refill would push another single slab, which was immediately exhausted - Pool would oscillate between 0 and 1 items, yielding 0% hit rate Solution: Secondary Prefill on Cache Miss When warm pool becomes empty, we now do multiple superslab_refills and prefill the pool with 3 additional HOT superlslabs before attempting to carve. This builds a working set of slabs that can sustain allocation pressure. Implementation Details: - Modified unified_cache_refill() cold path to detect empty pool - Added prefill loop: when pool count == 0, load 3 extra superlslabs - Store extra slabs in warm pool, keep 1 in TLS for immediate carving - Track prefill events in g_warm_pool_stats[].prefilled counter Results (1M Random Mixed 256B allocations): - Before: C7 hits=1, misses=3976, hit_rate=0.0% - After: C7 hits=3929, misses=3143, hit_rate=55.6% - Throughput: 4.055M ops/s (maintained vs 4.07M baseline) - Stability: Consistent 55.6% hit rate at 5M allocations (4.102M ops/s) Performance Impact: - No regression: throughput remained stable at ~4.1M ops/s - Registry scan avoided in 55.6% of cache misses (significant savings) - Warm pool now functioning as intended with strong locality Configuration: - TINY_WARM_POOL_MAX_PER_CLASS increased from 4 to 16 to support prefill - Prefill budget hardcoded to 3 (tunable via env var if needed later) - All statistics always compiled, ENV-gated printing via HAKMEM_WARM_POOL_STATS=1 Next Steps: - Monitor for further optimization opportunities (prefill budget tuning) - Consider adaptive prefill budget based on class-specific hit rates - Validate at larger allocation counts (10M+ pending registry size fix) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 23:31:54 +09:00
#include "front/tiny_warm_pool.h" // Warm Pool: Prefill during registry scans
#include <stdlib.h>
#include <stdio.h>
#include <stdatomic.h>
Performance Measurement Framework: Unified Cache, TLS SLL, Shared Pool Analysis ## Summary Implemented production-grade measurement infrastructure to quantify top 3 bottlenecks: - Unified cache hit/miss rates + refill cost - TLS SLL usage patterns - Shared pool lock contention distribution ## Changes ### 1. Unified Cache Metrics (tiny_unified_cache.h/c) - Added atomic counters: - g_unified_cache_hits_global: successful cache pops - g_unified_cache_misses_global: refill triggers - g_unified_cache_refill_cycles_global: refill cost in CPU cycles (rdtsc) - Instrumented `unified_cache_pop_or_refill()` to count hits - Instrumented `unified_cache_refill()` with cycle measurement - ENV-gated: HAKMEM_MEASURE_UNIFIED_CACHE=1 (default: off) - Added unified_cache_print_measurements() output function ### 2. TLS SLL Metrics (tls_sll_box.h) - Added atomic counters: - g_tls_sll_push_count_global: total pushes - g_tls_sll_pop_count_global: successful pops - g_tls_sll_pop_empty_count_global: empty list conditions - Instrumented push/pop paths - Added tls_sll_print_measurements() output function ### 3. Shared Pool Contention (hakmem_shared_pool_acquire.c) - Added atomic counters: - g_sp_stage2_lock_acquired_global: Stage 2 locks - g_sp_stage3_lock_acquired_global: Stage 3 allocations - g_sp_alloc_lock_contention_global: total lock acquisitions - Instrumented all pthread_mutex_lock calls in hot paths - Added shared_pool_print_measurements() output function ### 4. Benchmark Integration (bench_random_mixed.c) - Called all 3 print functions after benchmark loop - Functions active only when HAKMEM_MEASURE_UNIFIED_CACHE=1 set ## Design Principles - **Zero overhead when disabled**: Inline checks with __builtin_expect hints - **Atomic relaxed memory order**: Minimal synchronization overhead - **ENV-gated**: Single flag controls all measurements - **Production-safe**: Compiles in release builds, no functional changes ## Usage ```bash HAKMEM_MEASURE_UNIFIED_CACHE=1 ./bench_allocators_hakmem bench_random_mixed_hakmem 1000000 256 42 ``` Output (when enabled): ``` ======================================== Unified Cache Statistics ======================================== Hits: 1234567 Misses: 56789 Hit Rate: 95.6% Avg Refill Cycles: 1234 ======================================== TLS SLL Statistics ======================================== Total Pushes: 1234567 Total Pops: 345678 Pop Empty Count: 12345 Hit Rate: 98.8% ======================================== Shared Pool Contention Statistics ======================================== Stage 2 Locks: 123456 (33%) Stage 3 Locks: 234567 (67%) Total Contention: 357 locks per 1M ops ``` ## Next Steps 1. **Enable measurements** and run benchmarks to gather data 2. **Analyze miss rates**: Which bottleneck dominates? 3. **Profile hottest stage**: Focus optimization on top contributor 4. Possible targets: - Increase unified cache capacity if miss rate >5% - Profile if TLS SLL is unused (potential legacy code removal) - Analyze if Stage 2 lock can be replaced with CAS ## Makefile Updates Added core/box/tiny_route_box.o to: - OBJS_BASE (test build) - SHARED_OBJS (shared library) - BENCH_HAKMEM_OBJS_BASE (benchmark) - TINY_BENCH_OBJS_BASE (tiny benchmark) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 18:26:39 +09:00
// ============================================================================
// Performance Measurement: Shared Pool Lock Contention (ENV-gated)
// ============================================================================
// Global atomic counters for lock contention measurement
// ENV: HAKMEM_MEASURE_UNIFIED_CACHE=1 to enable (default: OFF)
_Atomic uint64_t g_sp_stage2_lock_acquired_global = 0;
_Atomic uint64_t g_sp_stage3_lock_acquired_global = 0;
_Atomic uint64_t g_sp_alloc_lock_contention_global = 0;
// Check if measurement is enabled (cached)
static inline int sp_measure_enabled(void) {
static int g_measure = -1;
if (__builtin_expect(g_measure == -1, 0)) {
const char* e = getenv("HAKMEM_MEASURE_UNIFIED_CACHE");
g_measure = (e && *e && *e != '0') ? 1 : 0;
}
return g_measure;
}
// Print statistics function
void shared_pool_print_measurements(void);
// Stage 0.5: EMPTY slab direct scanregistry ベースの EMPTY 再利用)
// Scan existing SuperSlabs for EMPTY slabs (highest reuse priority) to
// avoid Stage 3 (mmap) when freed slabs are available.
Implement Warm Pool Secondary Prefill Optimization (Phase B-2c Complete) Problem: Warm pool had 0% hit rate (only 1 hit per 3976 misses) despite being implemented, causing all cache misses to go through expensive superslab_refill registry scans. Root Cause Analysis: - Warm pool was initialized once and pushed a single slab after each refill - When that slab was exhausted, it was discarded (not pushed back) - Next refill would push another single slab, which was immediately exhausted - Pool would oscillate between 0 and 1 items, yielding 0% hit rate Solution: Secondary Prefill on Cache Miss When warm pool becomes empty, we now do multiple superslab_refills and prefill the pool with 3 additional HOT superlslabs before attempting to carve. This builds a working set of slabs that can sustain allocation pressure. Implementation Details: - Modified unified_cache_refill() cold path to detect empty pool - Added prefill loop: when pool count == 0, load 3 extra superlslabs - Store extra slabs in warm pool, keep 1 in TLS for immediate carving - Track prefill events in g_warm_pool_stats[].prefilled counter Results (1M Random Mixed 256B allocations): - Before: C7 hits=1, misses=3976, hit_rate=0.0% - After: C7 hits=3929, misses=3143, hit_rate=55.6% - Throughput: 4.055M ops/s (maintained vs 4.07M baseline) - Stability: Consistent 55.6% hit rate at 5M allocations (4.102M ops/s) Performance Impact: - No regression: throughput remained stable at ~4.1M ops/s - Registry scan avoided in 55.6% of cache misses (significant savings) - Warm pool now functioning as intended with strong locality Configuration: - TINY_WARM_POOL_MAX_PER_CLASS increased from 4 to 16 to support prefill - Prefill budget hardcoded to 3 (tunable via env var if needed later) - All statistics always compiled, ENV-gated printing via HAKMEM_WARM_POOL_STATS=1 Next Steps: - Monitor for further optimization opportunities (prefill budget tuning) - Consider adaptive prefill budget based on class-specific hit rates - Validate at larger allocation counts (10M+ pending registry size fix) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 23:31:54 +09:00
//
// WARM POOL OPTIMIZATION:
// - During the registry scan, prefill warm pool with HOT SuperSlabs
// - This eliminates future registry scans for cache misses
// - Expected gain: +40-50% by reducing O(N) scan overhead
static inline int
sp_acquire_from_empty_scan(int class_idx, SuperSlab** ss_out, int* slab_idx_out, int dbg_acquire)
{
// Priority-2: Use cached ENV
int empty_reuse_enabled = HAK_ENV_SS_EMPTY_REUSE();
if (!empty_reuse_enabled) {
return -1;
}
extern SuperSlab* g_super_reg_by_class[TINY_NUM_CLASSES][SUPER_REG_PER_CLASS];
extern int g_super_reg_class_size[TINY_NUM_CLASSES];
int reg_size = (class_idx < TINY_NUM_CLASSES) ? g_super_reg_class_size[class_idx] : 0;
// Priority-2: Use cached ENV
int scan_limit = HAK_ENV_SS_EMPTY_SCAN_LIMIT();
if (scan_limit > reg_size) scan_limit = reg_size;
// Stage 0.5 hit counter for visualization
static _Atomic uint64_t stage05_hits = 0;
static _Atomic uint64_t stage05_attempts = 0;
atomic_fetch_add_explicit(&stage05_attempts, 1, memory_order_relaxed);
Implement Warm Pool Secondary Prefill Optimization (Phase B-2c Complete) Problem: Warm pool had 0% hit rate (only 1 hit per 3976 misses) despite being implemented, causing all cache misses to go through expensive superslab_refill registry scans. Root Cause Analysis: - Warm pool was initialized once and pushed a single slab after each refill - When that slab was exhausted, it was discarded (not pushed back) - Next refill would push another single slab, which was immediately exhausted - Pool would oscillate between 0 and 1 items, yielding 0% hit rate Solution: Secondary Prefill on Cache Miss When warm pool becomes empty, we now do multiple superslab_refills and prefill the pool with 3 additional HOT superlslabs before attempting to carve. This builds a working set of slabs that can sustain allocation pressure. Implementation Details: - Modified unified_cache_refill() cold path to detect empty pool - Added prefill loop: when pool count == 0, load 3 extra superlslabs - Store extra slabs in warm pool, keep 1 in TLS for immediate carving - Track prefill events in g_warm_pool_stats[].prefilled counter Results (1M Random Mixed 256B allocations): - Before: C7 hits=1, misses=3976, hit_rate=0.0% - After: C7 hits=3929, misses=3143, hit_rate=55.6% - Throughput: 4.055M ops/s (maintained vs 4.07M baseline) - Stability: Consistent 55.6% hit rate at 5M allocations (4.102M ops/s) Performance Impact: - No regression: throughput remained stable at ~4.1M ops/s - Registry scan avoided in 55.6% of cache misses (significant savings) - Warm pool now functioning as intended with strong locality Configuration: - TINY_WARM_POOL_MAX_PER_CLASS increased from 4 to 16 to support prefill - Prefill budget hardcoded to 3 (tunable via env var if needed later) - All statistics always compiled, ENV-gated printing via HAKMEM_WARM_POOL_STATS=1 Next Steps: - Monitor for further optimization opportunities (prefill budget tuning) - Consider adaptive prefill budget based on class-specific hit rates - Validate at larger allocation counts (10M+ pending registry size fix) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 23:31:54 +09:00
// Initialize warm pool on first use (per-thread, one-time)
tiny_warm_pool_init_once();
// Track SuperSlabs scanned during this acquire call for warm pool prefill
SuperSlab* primary_result = NULL;
int primary_slab_idx = -1;
for (int i = 0; i < scan_limit; i++) {
SuperSlab* ss = g_super_reg_by_class[class_idx][i];
if (!(ss && ss->magic == SUPERSLAB_MAGIC)) continue;
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>
2025-12-04 18:01:25 +09:00
// P-Tier: Skip DRAINING tier SuperSlabs
if (!ss_tier_is_hot(ss)) continue;
if (ss->empty_count == 0) continue; // No EMPTY slabs in this SS
Implement Warm Pool Secondary Prefill Optimization (Phase B-2c Complete) Problem: Warm pool had 0% hit rate (only 1 hit per 3976 misses) despite being implemented, causing all cache misses to go through expensive superslab_refill registry scans. Root Cause Analysis: - Warm pool was initialized once and pushed a single slab after each refill - When that slab was exhausted, it was discarded (not pushed back) - Next refill would push another single slab, which was immediately exhausted - Pool would oscillate between 0 and 1 items, yielding 0% hit rate Solution: Secondary Prefill on Cache Miss When warm pool becomes empty, we now do multiple superslab_refills and prefill the pool with 3 additional HOT superlslabs before attempting to carve. This builds a working set of slabs that can sustain allocation pressure. Implementation Details: - Modified unified_cache_refill() cold path to detect empty pool - Added prefill loop: when pool count == 0, load 3 extra superlslabs - Store extra slabs in warm pool, keep 1 in TLS for immediate carving - Track prefill events in g_warm_pool_stats[].prefilled counter Results (1M Random Mixed 256B allocations): - Before: C7 hits=1, misses=3976, hit_rate=0.0% - After: C7 hits=3929, misses=3143, hit_rate=55.6% - Throughput: 4.055M ops/s (maintained vs 4.07M baseline) - Stability: Consistent 55.6% hit rate at 5M allocations (4.102M ops/s) Performance Impact: - No regression: throughput remained stable at ~4.1M ops/s - Registry scan avoided in 55.6% of cache misses (significant savings) - Warm pool now functioning as intended with strong locality Configuration: - TINY_WARM_POOL_MAX_PER_CLASS increased from 4 to 16 to support prefill - Prefill budget hardcoded to 3 (tunable via env var if needed later) - All statistics always compiled, ENV-gated printing via HAKMEM_WARM_POOL_STATS=1 Next Steps: - Monitor for further optimization opportunities (prefill budget tuning) - Consider adaptive prefill budget based on class-specific hit rates - Validate at larger allocation counts (10M+ pending registry size fix) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 23:31:54 +09:00
// WARM POOL PREFILL: Add HOT SuperSlabs to warm pool (if not already primary result)
// This is low-cost during registry scan and avoids future expensive scans
// Phase 1: Increase threshold from 4 to 12 to match TINY_WARM_POOL_MAX_PER_CLASS
if (ss != primary_result && tiny_warm_pool_count(class_idx) < 12) {
Implement Warm Pool Secondary Prefill Optimization (Phase B-2c Complete) Problem: Warm pool had 0% hit rate (only 1 hit per 3976 misses) despite being implemented, causing all cache misses to go through expensive superslab_refill registry scans. Root Cause Analysis: - Warm pool was initialized once and pushed a single slab after each refill - When that slab was exhausted, it was discarded (not pushed back) - Next refill would push another single slab, which was immediately exhausted - Pool would oscillate between 0 and 1 items, yielding 0% hit rate Solution: Secondary Prefill on Cache Miss When warm pool becomes empty, we now do multiple superslab_refills and prefill the pool with 3 additional HOT superlslabs before attempting to carve. This builds a working set of slabs that can sustain allocation pressure. Implementation Details: - Modified unified_cache_refill() cold path to detect empty pool - Added prefill loop: when pool count == 0, load 3 extra superlslabs - Store extra slabs in warm pool, keep 1 in TLS for immediate carving - Track prefill events in g_warm_pool_stats[].prefilled counter Results (1M Random Mixed 256B allocations): - Before: C7 hits=1, misses=3976, hit_rate=0.0% - After: C7 hits=3929, misses=3143, hit_rate=55.6% - Throughput: 4.055M ops/s (maintained vs 4.07M baseline) - Stability: Consistent 55.6% hit rate at 5M allocations (4.102M ops/s) Performance Impact: - No regression: throughput remained stable at ~4.1M ops/s - Registry scan avoided in 55.6% of cache misses (significant savings) - Warm pool now functioning as intended with strong locality Configuration: - TINY_WARM_POOL_MAX_PER_CLASS increased from 4 to 16 to support prefill - Prefill budget hardcoded to 3 (tunable via env var if needed later) - All statistics always compiled, ENV-gated printing via HAKMEM_WARM_POOL_STATS=1 Next Steps: - Monitor for further optimization opportunities (prefill budget tuning) - Consider adaptive prefill budget based on class-specific hit rates - Validate at larger allocation counts (10M+ pending registry size fix) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 23:31:54 +09:00
tiny_warm_pool_push(class_idx, ss);
// Track prefilled SuperSlabs for metrics
g_warm_pool_stats[class_idx].prefilled++;
}
uint32_t mask = ss->empty_mask;
while (mask) {
int empty_idx = __builtin_ctz(mask);
mask &= (mask - 1); // clear lowest bit
TinySlabMeta* meta = &ss->slabs[empty_idx];
if (meta->capacity > 0 && meta->used == 0) {
tiny_tls_slab_reuse_guard(ss);
ss_clear_slab_empty(ss, empty_idx);
meta->class_idx = (uint8_t)class_idx;
ss->class_map[empty_idx] = (uint8_t)class_idx;
#if !HAKMEM_BUILD_RELEASE
if (dbg_acquire == 1) {
fprintf(stderr,
Implement Warm Pool Secondary Prefill Optimization (Phase B-2c Complete) Problem: Warm pool had 0% hit rate (only 1 hit per 3976 misses) despite being implemented, causing all cache misses to go through expensive superslab_refill registry scans. Root Cause Analysis: - Warm pool was initialized once and pushed a single slab after each refill - When that slab was exhausted, it was discarded (not pushed back) - Next refill would push another single slab, which was immediately exhausted - Pool would oscillate between 0 and 1 items, yielding 0% hit rate Solution: Secondary Prefill on Cache Miss When warm pool becomes empty, we now do multiple superslab_refills and prefill the pool with 3 additional HOT superlslabs before attempting to carve. This builds a working set of slabs that can sustain allocation pressure. Implementation Details: - Modified unified_cache_refill() cold path to detect empty pool - Added prefill loop: when pool count == 0, load 3 extra superlslabs - Store extra slabs in warm pool, keep 1 in TLS for immediate carving - Track prefill events in g_warm_pool_stats[].prefilled counter Results (1M Random Mixed 256B allocations): - Before: C7 hits=1, misses=3976, hit_rate=0.0% - After: C7 hits=3929, misses=3143, hit_rate=55.6% - Throughput: 4.055M ops/s (maintained vs 4.07M baseline) - Stability: Consistent 55.6% hit rate at 5M allocations (4.102M ops/s) Performance Impact: - No regression: throughput remained stable at ~4.1M ops/s - Registry scan avoided in 55.6% of cache misses (significant savings) - Warm pool now functioning as intended with strong locality Configuration: - TINY_WARM_POOL_MAX_PER_CLASS increased from 4 to 16 to support prefill - Prefill budget hardcoded to 3 (tunable via env var if needed later) - All statistics always compiled, ENV-gated printing via HAKMEM_WARM_POOL_STATS=1 Next Steps: - Monitor for further optimization opportunities (prefill budget tuning) - Consider adaptive prefill budget based on class-specific hit rates - Validate at larger allocation counts (10M+ pending registry size fix) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 23:31:54 +09:00
"[SP_ACQUIRE_STAGE0.5_EMPTY] class=%d reusing EMPTY slab (ss=%p slab=%d empty_count=%u warm_pool_size=%d)\n",
class_idx, (void*)ss, empty_idx, ss->empty_count, tiny_warm_pool_count(class_idx));
}
#else
(void)dbg_acquire;
#endif
Implement Warm Pool Secondary Prefill Optimization (Phase B-2c Complete) Problem: Warm pool had 0% hit rate (only 1 hit per 3976 misses) despite being implemented, causing all cache misses to go through expensive superslab_refill registry scans. Root Cause Analysis: - Warm pool was initialized once and pushed a single slab after each refill - When that slab was exhausted, it was discarded (not pushed back) - Next refill would push another single slab, which was immediately exhausted - Pool would oscillate between 0 and 1 items, yielding 0% hit rate Solution: Secondary Prefill on Cache Miss When warm pool becomes empty, we now do multiple superslab_refills and prefill the pool with 3 additional HOT superlslabs before attempting to carve. This builds a working set of slabs that can sustain allocation pressure. Implementation Details: - Modified unified_cache_refill() cold path to detect empty pool - Added prefill loop: when pool count == 0, load 3 extra superlslabs - Store extra slabs in warm pool, keep 1 in TLS for immediate carving - Track prefill events in g_warm_pool_stats[].prefilled counter Results (1M Random Mixed 256B allocations): - Before: C7 hits=1, misses=3976, hit_rate=0.0% - After: C7 hits=3929, misses=3143, hit_rate=55.6% - Throughput: 4.055M ops/s (maintained vs 4.07M baseline) - Stability: Consistent 55.6% hit rate at 5M allocations (4.102M ops/s) Performance Impact: - No regression: throughput remained stable at ~4.1M ops/s - Registry scan avoided in 55.6% of cache misses (significant savings) - Warm pool now functioning as intended with strong locality Configuration: - TINY_WARM_POOL_MAX_PER_CLASS increased from 4 to 16 to support prefill - Prefill budget hardcoded to 3 (tunable via env var if needed later) - All statistics always compiled, ENV-gated printing via HAKMEM_WARM_POOL_STATS=1 Next Steps: - Monitor for further optimization opportunities (prefill budget tuning) - Consider adaptive prefill budget based on class-specific hit rates - Validate at larger allocation counts (10M+ pending registry size fix) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 23:31:54 +09:00
// Store primary result but continue scanning to prefill warm pool
if (primary_result == NULL) {
primary_result = ss;
primary_slab_idx = empty_idx;
*ss_out = ss;
*slab_idx_out = empty_idx;
sp_stage_stats_init();
if (g_sp_stage_stats_enabled) {
atomic_fetch_add(&g_sp_stage1_hits[class_idx], 1);
}
atomic_fetch_add_explicit(&stage05_hits, 1, memory_order_relaxed);
}
}
}
}
Implement Warm Pool Secondary Prefill Optimization (Phase B-2c Complete) Problem: Warm pool had 0% hit rate (only 1 hit per 3976 misses) despite being implemented, causing all cache misses to go through expensive superslab_refill registry scans. Root Cause Analysis: - Warm pool was initialized once and pushed a single slab after each refill - When that slab was exhausted, it was discarded (not pushed back) - Next refill would push another single slab, which was immediately exhausted - Pool would oscillate between 0 and 1 items, yielding 0% hit rate Solution: Secondary Prefill on Cache Miss When warm pool becomes empty, we now do multiple superslab_refills and prefill the pool with 3 additional HOT superlslabs before attempting to carve. This builds a working set of slabs that can sustain allocation pressure. Implementation Details: - Modified unified_cache_refill() cold path to detect empty pool - Added prefill loop: when pool count == 0, load 3 extra superlslabs - Store extra slabs in warm pool, keep 1 in TLS for immediate carving - Track prefill events in g_warm_pool_stats[].prefilled counter Results (1M Random Mixed 256B allocations): - Before: C7 hits=1, misses=3976, hit_rate=0.0% - After: C7 hits=3929, misses=3143, hit_rate=55.6% - Throughput: 4.055M ops/s (maintained vs 4.07M baseline) - Stability: Consistent 55.6% hit rate at 5M allocations (4.102M ops/s) Performance Impact: - No regression: throughput remained stable at ~4.1M ops/s - Registry scan avoided in 55.6% of cache misses (significant savings) - Warm pool now functioning as intended with strong locality Configuration: - TINY_WARM_POOL_MAX_PER_CLASS increased from 4 to 16 to support prefill - Prefill budget hardcoded to 3 (tunable via env var if needed later) - All statistics always compiled, ENV-gated printing via HAKMEM_WARM_POOL_STATS=1 Next Steps: - Monitor for further optimization opportunities (prefill budget tuning) - Consider adaptive prefill budget based on class-specific hit rates - Validate at larger allocation counts (10M+ pending registry size fix) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 23:31:54 +09:00
if (primary_result != NULL) {
// Stage 0.5 hit rate visualization (every 100 hits)
uint64_t hits = atomic_load_explicit(&stage05_hits, memory_order_relaxed);
if (hits % 100 == 1) {
uint64_t attempts = atomic_load_explicit(&stage05_attempts, memory_order_relaxed);
fprintf(stderr, "[STAGE0.5_STATS] hits=%lu attempts=%lu rate=%.1f%% (scan_limit=%d warm_pool=%d)\n",
hits, attempts, (double)hits * 100.0 / attempts, scan_limit, tiny_warm_pool_count(class_idx));
}
return 0;
}
return -1;
}
int
shared_pool_acquire_slab(int class_idx, SuperSlab** ss_out, int* slab_idx_out)
{
// Phase 12: SP-SLOT Box - 3-Stage Acquire Logic
//
// Stage 1: Reuse EMPTY slots from per-class free list (EMPTY→ACTIVE)
// Stage 2: Find UNUSED slots in existing SuperSlabs
// Stage 3: Get new SuperSlab (LRU pop or mmap)
//
// Invariants:
// - On success: *ss_out != NULL, 0 <= *slab_idx_out < total_slots
// - The chosen slab has meta->class_idx == class_idx
if (!ss_out || !slab_idx_out) {
return -1;
}
if (class_idx < 0 || class_idx >= TINY_NUM_CLASSES_SS) {
return -1;
}
shared_pool_init();
// Debug logging / stage stats
#if !HAKMEM_BUILD_RELEASE
// Priority-2: Use cached ENV
int dbg_acquire = HAK_ENV_SS_ACQUIRE_DEBUG();
#else
static const int dbg_acquire = 0;
#endif
sp_stage_stats_init();
stage1_retry_after_tension_drain:
// ========== Stage 0.5 (Phase 12-1.1): EMPTY slab direct scan ==========
// Scan existing SuperSlabs for EMPTY slabs (highest reuse priority) to
// avoid Stage 3 (mmap) when freed slabs are available.
if (sp_acquire_from_empty_scan(class_idx, ss_out, slab_idx_out, dbg_acquire) == 0) {
return 0;
}
// ========== Stage 1 (Lock-Free): Try to reuse EMPTY slots ==========
// P0-4: Lock-free pop from per-class free list (no mutex needed!)
// Best case: Same class freed a slot, reuse immediately (cache-hot)
SharedSSMeta* reuse_meta = NULL;
int reuse_slot_idx = -1;
if (sp_freelist_pop_lockfree(class_idx, &reuse_meta, &reuse_slot_idx)) {
// Found EMPTY slot from lock-free list!
// Now acquire mutex ONLY for slot activation and metadata update
// P0 instrumentation: count lock acquisitions
lock_stats_init();
if (g_lock_stats_enabled == 1) {
atomic_fetch_add(&g_lock_acquire_count, 1);
atomic_fetch_add(&g_lock_acquire_slab_count, 1);
}
pthread_mutex_lock(&g_shared_pool.alloc_lock);
// P0.3: Guard against TLS SLL orphaned pointers before reusing slab
// RACE FIX: Load SuperSlab pointer atomically BEFORE guard (consistency)
SuperSlab* ss_guard = atomic_load_explicit(&reuse_meta->ss, memory_order_relaxed);
if (ss_guard) {
tiny_tls_slab_reuse_guard(ss_guard);
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>
2025-12-04 18:01:25 +09:00
Implement Warm Pool Secondary Prefill Optimization (Phase B-2c Complete) Problem: Warm pool had 0% hit rate (only 1 hit per 3976 misses) despite being implemented, causing all cache misses to go through expensive superslab_refill registry scans. Root Cause Analysis: - Warm pool was initialized once and pushed a single slab after each refill - When that slab was exhausted, it was discarded (not pushed back) - Next refill would push another single slab, which was immediately exhausted - Pool would oscillate between 0 and 1 items, yielding 0% hit rate Solution: Secondary Prefill on Cache Miss When warm pool becomes empty, we now do multiple superslab_refills and prefill the pool with 3 additional HOT superlslabs before attempting to carve. This builds a working set of slabs that can sustain allocation pressure. Implementation Details: - Modified unified_cache_refill() cold path to detect empty pool - Added prefill loop: when pool count == 0, load 3 extra superlslabs - Store extra slabs in warm pool, keep 1 in TLS for immediate carving - Track prefill events in g_warm_pool_stats[].prefilled counter Results (1M Random Mixed 256B allocations): - Before: C7 hits=1, misses=3976, hit_rate=0.0% - After: C7 hits=3929, misses=3143, hit_rate=55.6% - Throughput: 4.055M ops/s (maintained vs 4.07M baseline) - Stability: Consistent 55.6% hit rate at 5M allocations (4.102M ops/s) Performance Impact: - No regression: throughput remained stable at ~4.1M ops/s - Registry scan avoided in 55.6% of cache misses (significant savings) - Warm pool now functioning as intended with strong locality Configuration: - TINY_WARM_POOL_MAX_PER_CLASS increased from 4 to 16 to support prefill - Prefill budget hardcoded to 3 (tunable via env var if needed later) - All statistics always compiled, ENV-gated printing via HAKMEM_WARM_POOL_STATS=1 Next Steps: - Monitor for further optimization opportunities (prefill budget tuning) - Consider adaptive prefill budget based on class-specific hit rates - Validate at larger allocation counts (10M+ pending registry size fix) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 23:31:54 +09:00
// P-Tier: Skip DRAINING tier SuperSlabs
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>
2025-12-04 18:01:25 +09:00
if (!ss_tier_is_hot(ss_guard)) {
// DRAINING SuperSlab - skip this slot and fall through to Stage 2
if (g_lock_stats_enabled == 1) {
atomic_fetch_add(&g_lock_release_count, 1);
}
pthread_mutex_unlock(&g_shared_pool.alloc_lock);
goto stage2_fallback;
}
}
// Activate slot under mutex (slot state transition requires protection)
if (sp_slot_mark_active(reuse_meta, reuse_slot_idx, class_idx) == 0) {
// RACE FIX: Load SuperSlab pointer atomically (consistency)
SuperSlab* ss = atomic_load_explicit(&reuse_meta->ss, memory_order_relaxed);
// RACE FIX: Check if SuperSlab was freed (NULL pointer)
// This can happen if Thread A freed the SuperSlab after pushing slot to freelist,
// but Thread B popped the stale slot before the freelist was cleared.
if (!ss) {
// SuperSlab freed - skip and fall through to Stage 2/3
if (g_lock_stats_enabled == 1) {
atomic_fetch_add(&g_lock_release_count, 1);
}
pthread_mutex_unlock(&g_shared_pool.alloc_lock);
goto stage2_fallback;
}
#if !HAKMEM_BUILD_RELEASE
if (dbg_acquire == 1) {
fprintf(stderr, "[SP_ACQUIRE_STAGE1_LOCKFREE] class=%d reusing EMPTY slot (ss=%p slab=%d)\n",
class_idx, (void*)ss, reuse_slot_idx);
}
#endif
// Update SuperSlab metadata
ss->slab_bitmap |= (1u << reuse_slot_idx);
ss_slab_meta_class_idx_set(ss, reuse_slot_idx, (uint8_t)class_idx);
if (ss->active_slabs == 0) {
// Was empty, now active again
ss->active_slabs = 1;
g_shared_pool.active_count++;
}
// Track per-class active slots (approximate, under alloc_lock)
if (class_idx < TINY_NUM_CLASSES_SS) {
g_shared_pool.class_active_slots[class_idx]++;
}
// Update hint
g_shared_pool.class_hints[class_idx] = ss;
*ss_out = ss;
*slab_idx_out = reuse_slot_idx;
if (g_lock_stats_enabled == 1) {
atomic_fetch_add(&g_lock_release_count, 1);
}
pthread_mutex_unlock(&g_shared_pool.alloc_lock);
if (g_sp_stage_stats_enabled) {
atomic_fetch_add(&g_sp_stage1_hits[class_idx], 1);
}
return 0; // ✅ Stage 1 (lock-free) success
}
// Slot activation failed (race condition?) - release lock and fall through
if (g_lock_stats_enabled == 1) {
atomic_fetch_add(&g_lock_release_count, 1);
}
pthread_mutex_unlock(&g_shared_pool.alloc_lock);
}
stage2_fallback:
// ========== Stage 2 (Lock-Free): Try to claim UNUSED slots ==========
P0 Optimization: Shared Pool fast path with O(1) metadata lookup Performance Results: - Throughput: 2.66M ops/s → 3.8M ops/s (+43% improvement) - sp_meta_find_or_create: O(N) linear scan → O(1) direct pointer - Stage 2 metadata scan: 100% → 10-20% (80-90% reduction via hints) Core Optimizations: 1. O(1) Metadata Lookup (superslab_types.h) - Added `shared_meta` pointer field to SuperSlab struct - Eliminates O(N) linear search through ss_metadata[] array - First access: O(N) scan + cache | Subsequent: O(1) direct return 2. sp_meta_find_or_create Fast Path (hakmem_shared_pool.c) - Check cached ss->shared_meta first before linear scan - Cache pointer after successful linear scan for future lookups - Reduces 7.8% CPU hotspot to near-zero for hot paths 3. Stage 2 Class Hints Fast Path (hakmem_shared_pool_acquire.c) - Try class_hints[class_idx] FIRST before full metadata scan - Uses O(1) ss->shared_meta lookup for hint validation - __builtin_expect() for branch prediction optimization - 80-90% of acquire calls now skip full metadata scan 4. Proper Initialization (ss_allocation_box.c) - Initialize shared_meta = NULL in superslab_allocate() - Ensures correct NULL-check semantics for new SuperSlabs Additional Improvements: - Updated ptr_trace and debug ring for release build efficiency - Enhanced ENV variable documentation and analysis - Added learner_env_box.h for configuration management - Various Box optimizations for reduced overhead Thread Safety: - All atomic operations use correct memory ordering - shared_meta cached under mutex protection - Lock-free Stage 2 uses proper CAS with acquire/release semantics Testing: - Benchmark: 1M iterations, 3.8M ops/s stable - Build: Clean compile RELEASE=0 and RELEASE=1 - No crashes, memory leaks, or correctness issues Next Optimization Candidates: - P1: Per-SuperSlab free slot bitmap for O(1) slot claiming - P2: Reduce Stage 2 critical section size - P3: Page pre-faulting (MAP_POPULATE) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 16:21:54 +09:00
// P0 Optimization: Try class hint FIRST for fast path (same class locality)
// This reduces metadata scan from 100% to ~10% when hints are effective
{
SuperSlab* hint_ss = g_shared_pool.class_hints[class_idx];
if (__builtin_expect(hint_ss != NULL, 1)) {
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>
2025-12-04 18:01:25 +09:00
// P-Tier: Skip DRAINING tier SuperSlabs
if (!ss_tier_is_hot(hint_ss)) {
// Clear stale hint pointing to DRAINING SuperSlab
g_shared_pool.class_hints[class_idx] = NULL;
goto stage2_scan;
}
P0 Optimization: Shared Pool fast path with O(1) metadata lookup Performance Results: - Throughput: 2.66M ops/s → 3.8M ops/s (+43% improvement) - sp_meta_find_or_create: O(N) linear scan → O(1) direct pointer - Stage 2 metadata scan: 100% → 10-20% (80-90% reduction via hints) Core Optimizations: 1. O(1) Metadata Lookup (superslab_types.h) - Added `shared_meta` pointer field to SuperSlab struct - Eliminates O(N) linear search through ss_metadata[] array - First access: O(N) scan + cache | Subsequent: O(1) direct return 2. sp_meta_find_or_create Fast Path (hakmem_shared_pool.c) - Check cached ss->shared_meta first before linear scan - Cache pointer after successful linear scan for future lookups - Reduces 7.8% CPU hotspot to near-zero for hot paths 3. Stage 2 Class Hints Fast Path (hakmem_shared_pool_acquire.c) - Try class_hints[class_idx] FIRST before full metadata scan - Uses O(1) ss->shared_meta lookup for hint validation - __builtin_expect() for branch prediction optimization - 80-90% of acquire calls now skip full metadata scan 4. Proper Initialization (ss_allocation_box.c) - Initialize shared_meta = NULL in superslab_allocate() - Ensures correct NULL-check semantics for new SuperSlabs Additional Improvements: - Updated ptr_trace and debug ring for release build efficiency - Enhanced ENV variable documentation and analysis - Added learner_env_box.h for configuration management - Various Box optimizations for reduced overhead Thread Safety: - All atomic operations use correct memory ordering - shared_meta cached under mutex protection - Lock-free Stage 2 uses proper CAS with acquire/release semantics Testing: - Benchmark: 1M iterations, 3.8M ops/s stable - Build: Clean compile RELEASE=0 and RELEASE=1 - No crashes, memory leaks, or correctness issues Next Optimization Candidates: - P1: Per-SuperSlab free slot bitmap for O(1) slot claiming - P2: Reduce Stage 2 critical section size - P3: Page pre-faulting (MAP_POPULATE) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 16:21:54 +09:00
// P0 Optimization: O(1) lookup via cached pointer (avoids metadata scan)
SharedSSMeta* hint_meta = hint_ss->shared_meta;
if (__builtin_expect(hint_meta != NULL, 1)) {
// Try lock-free claiming on hint SuperSlab first
int claimed_idx = sp_slot_claim_lockfree(hint_meta, class_idx);
if (__builtin_expect(claimed_idx >= 0, 1)) {
// Fast path success! No need to scan all metadata
SuperSlab* ss = atomic_load_explicit(&hint_meta->ss, memory_order_acquire);
if (__builtin_expect(ss != NULL, 1)) {
#if !HAKMEM_BUILD_RELEASE
if (dbg_acquire == 1) {
fprintf(stderr, "[SP_ACQUIRE_STAGE2_HINT] class=%d claimed UNUSED slot from hint (ss=%p slab=%d)\n",
class_idx, (void*)ss, claimed_idx);
}
#endif
// P0 instrumentation: count lock acquisitions
lock_stats_init();
if (g_lock_stats_enabled == 1) {
atomic_fetch_add(&g_lock_acquire_count, 1);
atomic_fetch_add(&g_lock_acquire_slab_count, 1);
}
pthread_mutex_lock(&g_shared_pool.alloc_lock);
Performance Measurement Framework: Unified Cache, TLS SLL, Shared Pool Analysis ## Summary Implemented production-grade measurement infrastructure to quantify top 3 bottlenecks: - Unified cache hit/miss rates + refill cost - TLS SLL usage patterns - Shared pool lock contention distribution ## Changes ### 1. Unified Cache Metrics (tiny_unified_cache.h/c) - Added atomic counters: - g_unified_cache_hits_global: successful cache pops - g_unified_cache_misses_global: refill triggers - g_unified_cache_refill_cycles_global: refill cost in CPU cycles (rdtsc) - Instrumented `unified_cache_pop_or_refill()` to count hits - Instrumented `unified_cache_refill()` with cycle measurement - ENV-gated: HAKMEM_MEASURE_UNIFIED_CACHE=1 (default: off) - Added unified_cache_print_measurements() output function ### 2. TLS SLL Metrics (tls_sll_box.h) - Added atomic counters: - g_tls_sll_push_count_global: total pushes - g_tls_sll_pop_count_global: successful pops - g_tls_sll_pop_empty_count_global: empty list conditions - Instrumented push/pop paths - Added tls_sll_print_measurements() output function ### 3. Shared Pool Contention (hakmem_shared_pool_acquire.c) - Added atomic counters: - g_sp_stage2_lock_acquired_global: Stage 2 locks - g_sp_stage3_lock_acquired_global: Stage 3 allocations - g_sp_alloc_lock_contention_global: total lock acquisitions - Instrumented all pthread_mutex_lock calls in hot paths - Added shared_pool_print_measurements() output function ### 4. Benchmark Integration (bench_random_mixed.c) - Called all 3 print functions after benchmark loop - Functions active only when HAKMEM_MEASURE_UNIFIED_CACHE=1 set ## Design Principles - **Zero overhead when disabled**: Inline checks with __builtin_expect hints - **Atomic relaxed memory order**: Minimal synchronization overhead - **ENV-gated**: Single flag controls all measurements - **Production-safe**: Compiles in release builds, no functional changes ## Usage ```bash HAKMEM_MEASURE_UNIFIED_CACHE=1 ./bench_allocators_hakmem bench_random_mixed_hakmem 1000000 256 42 ``` Output (when enabled): ``` ======================================== Unified Cache Statistics ======================================== Hits: 1234567 Misses: 56789 Hit Rate: 95.6% Avg Refill Cycles: 1234 ======================================== TLS SLL Statistics ======================================== Total Pushes: 1234567 Total Pops: 345678 Pop Empty Count: 12345 Hit Rate: 98.8% ======================================== Shared Pool Contention Statistics ======================================== Stage 2 Locks: 123456 (33%) Stage 3 Locks: 234567 (67%) Total Contention: 357 locks per 1M ops ``` ## Next Steps 1. **Enable measurements** and run benchmarks to gather data 2. **Analyze miss rates**: Which bottleneck dominates? 3. **Profile hottest stage**: Focus optimization on top contributor 4. Possible targets: - Increase unified cache capacity if miss rate >5% - Profile if TLS SLL is unused (potential legacy code removal) - Analyze if Stage 2 lock can be replaced with CAS ## Makefile Updates Added core/box/tiny_route_box.o to: - OBJS_BASE (test build) - SHARED_OBJS (shared library) - BENCH_HAKMEM_OBJS_BASE (benchmark) - TINY_BENCH_OBJS_BASE (tiny benchmark) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 18:26:39 +09:00
// Performance measurement: count Stage 2 lock acquisitions
if (__builtin_expect(sp_measure_enabled(), 0)) {
atomic_fetch_add_explicit(&g_sp_stage2_lock_acquired_global, 1, memory_order_relaxed);
atomic_fetch_add_explicit(&g_sp_alloc_lock_contention_global, 1, memory_order_relaxed);
}
P0 Optimization: Shared Pool fast path with O(1) metadata lookup Performance Results: - Throughput: 2.66M ops/s → 3.8M ops/s (+43% improvement) - sp_meta_find_or_create: O(N) linear scan → O(1) direct pointer - Stage 2 metadata scan: 100% → 10-20% (80-90% reduction via hints) Core Optimizations: 1. O(1) Metadata Lookup (superslab_types.h) - Added `shared_meta` pointer field to SuperSlab struct - Eliminates O(N) linear search through ss_metadata[] array - First access: O(N) scan + cache | Subsequent: O(1) direct return 2. sp_meta_find_or_create Fast Path (hakmem_shared_pool.c) - Check cached ss->shared_meta first before linear scan - Cache pointer after successful linear scan for future lookups - Reduces 7.8% CPU hotspot to near-zero for hot paths 3. Stage 2 Class Hints Fast Path (hakmem_shared_pool_acquire.c) - Try class_hints[class_idx] FIRST before full metadata scan - Uses O(1) ss->shared_meta lookup for hint validation - __builtin_expect() for branch prediction optimization - 80-90% of acquire calls now skip full metadata scan 4. Proper Initialization (ss_allocation_box.c) - Initialize shared_meta = NULL in superslab_allocate() - Ensures correct NULL-check semantics for new SuperSlabs Additional Improvements: - Updated ptr_trace and debug ring for release build efficiency - Enhanced ENV variable documentation and analysis - Added learner_env_box.h for configuration management - Various Box optimizations for reduced overhead Thread Safety: - All atomic operations use correct memory ordering - shared_meta cached under mutex protection - Lock-free Stage 2 uses proper CAS with acquire/release semantics Testing: - Benchmark: 1M iterations, 3.8M ops/s stable - Build: Clean compile RELEASE=0 and RELEASE=1 - No crashes, memory leaks, or correctness issues Next Optimization Candidates: - P1: Per-SuperSlab free slot bitmap for O(1) slot claiming - P2: Reduce Stage 2 critical section size - P3: Page pre-faulting (MAP_POPULATE) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 16:21:54 +09:00
// Update SuperSlab metadata under mutex
ss->slab_bitmap |= (1u << claimed_idx);
ss_slab_meta_class_idx_set(ss, claimed_idx, (uint8_t)class_idx);
if (ss->active_slabs == 0) {
ss->active_slabs = 1;
g_shared_pool.active_count++;
}
if (class_idx < TINY_NUM_CLASSES_SS) {
g_shared_pool.class_active_slots[class_idx]++;
}
// Hint is still good, no need to update
*ss_out = ss;
*slab_idx_out = claimed_idx;
sp_fix_geometry_if_needed(ss, claimed_idx, class_idx);
if (g_lock_stats_enabled == 1) {
atomic_fetch_add(&g_lock_release_count, 1);
}
pthread_mutex_unlock(&g_shared_pool.alloc_lock);
if (g_sp_stage_stats_enabled) {
atomic_fetch_add(&g_sp_stage2_hits[class_idx], 1);
}
return 0; // ✅ Stage 2 (hint fast path) success
}
}
}
}
}
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>
2025-12-04 18:01:25 +09:00
stage2_scan:
// P0-5: Lock-free atomic CAS claiming (no mutex needed for slot state transition!)
// RACE FIX: Read ss_meta_count atomically (now properly declared as _Atomic)
// No cast needed! memory_order_acquire synchronizes with release in sp_meta_find_or_create
uint32_t meta_count = atomic_load_explicit(
&g_shared_pool.ss_meta_count,
memory_order_acquire
);
for (uint32_t i = 0; i < meta_count; i++) {
SharedSSMeta* meta = &g_shared_pool.ss_metadata[i];
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>
2025-12-04 18:01:25 +09:00
// RACE FIX: Load SuperSlab pointer atomically BEFORE claiming
// Use memory_order_acquire to synchronize with release in sp_meta_find_or_create
SuperSlab* ss_preflight = atomic_load_explicit(&meta->ss, memory_order_acquire);
if (!ss_preflight) {
// SuperSlab was freed - skip this entry
continue;
}
// P-Tier: Skip DRAINING tier SuperSlabs
if (!ss_tier_is_hot(ss_preflight)) {
continue;
}
// Try lock-free claiming (UNUSED → ACTIVE via CAS)
int claimed_idx = sp_slot_claim_lockfree(meta, class_idx);
if (claimed_idx >= 0) {
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>
2025-12-04 18:01:25 +09:00
// RACE FIX: Load SuperSlab pointer atomically again after claiming
// Use memory_order_acquire to synchronize with release in sp_meta_find_or_create
SuperSlab* ss = atomic_load_explicit(&meta->ss, memory_order_acquire);
if (!ss) {
// SuperSlab was freed between claiming and loading - skip this entry
continue;
}
#if !HAKMEM_BUILD_RELEASE
if (dbg_acquire == 1) {
fprintf(stderr, "[SP_ACQUIRE_STAGE2_LOCKFREE] class=%d claimed UNUSED slot (ss=%p slab=%d)\n",
class_idx, (void*)ss, claimed_idx);
}
#endif
// P0 instrumentation: count lock acquisitions
lock_stats_init();
if (g_lock_stats_enabled == 1) {
atomic_fetch_add(&g_lock_acquire_count, 1);
atomic_fetch_add(&g_lock_acquire_slab_count, 1);
}
pthread_mutex_lock(&g_shared_pool.alloc_lock);
Performance Measurement Framework: Unified Cache, TLS SLL, Shared Pool Analysis ## Summary Implemented production-grade measurement infrastructure to quantify top 3 bottlenecks: - Unified cache hit/miss rates + refill cost - TLS SLL usage patterns - Shared pool lock contention distribution ## Changes ### 1. Unified Cache Metrics (tiny_unified_cache.h/c) - Added atomic counters: - g_unified_cache_hits_global: successful cache pops - g_unified_cache_misses_global: refill triggers - g_unified_cache_refill_cycles_global: refill cost in CPU cycles (rdtsc) - Instrumented `unified_cache_pop_or_refill()` to count hits - Instrumented `unified_cache_refill()` with cycle measurement - ENV-gated: HAKMEM_MEASURE_UNIFIED_CACHE=1 (default: off) - Added unified_cache_print_measurements() output function ### 2. TLS SLL Metrics (tls_sll_box.h) - Added atomic counters: - g_tls_sll_push_count_global: total pushes - g_tls_sll_pop_count_global: successful pops - g_tls_sll_pop_empty_count_global: empty list conditions - Instrumented push/pop paths - Added tls_sll_print_measurements() output function ### 3. Shared Pool Contention (hakmem_shared_pool_acquire.c) - Added atomic counters: - g_sp_stage2_lock_acquired_global: Stage 2 locks - g_sp_stage3_lock_acquired_global: Stage 3 allocations - g_sp_alloc_lock_contention_global: total lock acquisitions - Instrumented all pthread_mutex_lock calls in hot paths - Added shared_pool_print_measurements() output function ### 4. Benchmark Integration (bench_random_mixed.c) - Called all 3 print functions after benchmark loop - Functions active only when HAKMEM_MEASURE_UNIFIED_CACHE=1 set ## Design Principles - **Zero overhead when disabled**: Inline checks with __builtin_expect hints - **Atomic relaxed memory order**: Minimal synchronization overhead - **ENV-gated**: Single flag controls all measurements - **Production-safe**: Compiles in release builds, no functional changes ## Usage ```bash HAKMEM_MEASURE_UNIFIED_CACHE=1 ./bench_allocators_hakmem bench_random_mixed_hakmem 1000000 256 42 ``` Output (when enabled): ``` ======================================== Unified Cache Statistics ======================================== Hits: 1234567 Misses: 56789 Hit Rate: 95.6% Avg Refill Cycles: 1234 ======================================== TLS SLL Statistics ======================================== Total Pushes: 1234567 Total Pops: 345678 Pop Empty Count: 12345 Hit Rate: 98.8% ======================================== Shared Pool Contention Statistics ======================================== Stage 2 Locks: 123456 (33%) Stage 3 Locks: 234567 (67%) Total Contention: 357 locks per 1M ops ``` ## Next Steps 1. **Enable measurements** and run benchmarks to gather data 2. **Analyze miss rates**: Which bottleneck dominates? 3. **Profile hottest stage**: Focus optimization on top contributor 4. Possible targets: - Increase unified cache capacity if miss rate >5% - Profile if TLS SLL is unused (potential legacy code removal) - Analyze if Stage 2 lock can be replaced with CAS ## Makefile Updates Added core/box/tiny_route_box.o to: - OBJS_BASE (test build) - SHARED_OBJS (shared library) - BENCH_HAKMEM_OBJS_BASE (benchmark) - TINY_BENCH_OBJS_BASE (tiny benchmark) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 18:26:39 +09:00
// Performance measurement: count Stage 2 scan lock acquisitions
if (__builtin_expect(sp_measure_enabled(), 0)) {
atomic_fetch_add_explicit(&g_sp_stage2_lock_acquired_global, 1, memory_order_relaxed);
atomic_fetch_add_explicit(&g_sp_alloc_lock_contention_global, 1, memory_order_relaxed);
}
// Update SuperSlab metadata under mutex
ss->slab_bitmap |= (1u << claimed_idx);
ss_slab_meta_class_idx_set(ss, claimed_idx, (uint8_t)class_idx);
if (ss->active_slabs == 0) {
ss->active_slabs = 1;
g_shared_pool.active_count++;
}
if (class_idx < TINY_NUM_CLASSES_SS) {
g_shared_pool.class_active_slots[class_idx]++;
}
// Update hint
g_shared_pool.class_hints[class_idx] = ss;
*ss_out = ss;
*slab_idx_out = claimed_idx;
sp_fix_geometry_if_needed(ss, claimed_idx, class_idx);
if (g_lock_stats_enabled == 1) {
atomic_fetch_add(&g_lock_release_count, 1);
}
pthread_mutex_unlock(&g_shared_pool.alloc_lock);
if (g_sp_stage_stats_enabled) {
atomic_fetch_add(&g_sp_stage2_hits[class_idx], 1);
}
return 0; // ✅ Stage 2 (lock-free) success
}
// Claim failed (no UNUSED slots in this meta) - continue to next SuperSlab
}
// ========== Tension-Based Drain: Try to create EMPTY slots before Stage 3 ==========
// If TLS SLL has accumulated blocks, drain them to enable EMPTY slot detection
// This can avoid allocating new SuperSlabs by reusing EMPTY slots in Stage 1
// ENV: HAKMEM_TINY_TENSION_DRAIN_ENABLE=0 to disable (default=1)
// ENV: HAKMEM_TINY_TENSION_DRAIN_THRESHOLD=N to set threshold (default=1024)
{
// Priority-2: Use cached ENV
int tension_drain_enabled = HAK_ENV_TINY_TENSION_DRAIN_ENABLE();
uint32_t tension_threshold = (uint32_t)HAK_ENV_TINY_TENSION_DRAIN_THRESHOLD();
if (tension_drain_enabled) {
extern __thread TinyTLSSLL g_tls_sll[TINY_NUM_CLASSES];
extern uint32_t tiny_tls_sll_drain(int class_idx, uint32_t batch_size);
uint32_t sll_count = (class_idx < TINY_NUM_CLASSES) ? g_tls_sll[class_idx].count : 0;
if (sll_count >= tension_threshold) {
// Drain all blocks to maximize EMPTY slot creation
uint32_t drained = tiny_tls_sll_drain(class_idx, 0); // 0 = drain all
if (drained > 0) {
// Retry Stage 1 (EMPTY reuse) after drain
// Some slabs might have become EMPTY (meta->used == 0)
goto stage1_retry_after_tension_drain;
}
}
}
}
// ========== Stage 3: Mutex-protected fallback (new SuperSlab allocation) ==========
// All existing SuperSlabs have no UNUSED slots → need new SuperSlab
// P0 instrumentation: count lock acquisitions
lock_stats_init();
if (g_lock_stats_enabled == 1) {
atomic_fetch_add(&g_lock_acquire_count, 1);
atomic_fetch_add(&g_lock_acquire_slab_count, 1);
}
pthread_mutex_lock(&g_shared_pool.alloc_lock);
Performance Measurement Framework: Unified Cache, TLS SLL, Shared Pool Analysis ## Summary Implemented production-grade measurement infrastructure to quantify top 3 bottlenecks: - Unified cache hit/miss rates + refill cost - TLS SLL usage patterns - Shared pool lock contention distribution ## Changes ### 1. Unified Cache Metrics (tiny_unified_cache.h/c) - Added atomic counters: - g_unified_cache_hits_global: successful cache pops - g_unified_cache_misses_global: refill triggers - g_unified_cache_refill_cycles_global: refill cost in CPU cycles (rdtsc) - Instrumented `unified_cache_pop_or_refill()` to count hits - Instrumented `unified_cache_refill()` with cycle measurement - ENV-gated: HAKMEM_MEASURE_UNIFIED_CACHE=1 (default: off) - Added unified_cache_print_measurements() output function ### 2. TLS SLL Metrics (tls_sll_box.h) - Added atomic counters: - g_tls_sll_push_count_global: total pushes - g_tls_sll_pop_count_global: successful pops - g_tls_sll_pop_empty_count_global: empty list conditions - Instrumented push/pop paths - Added tls_sll_print_measurements() output function ### 3. Shared Pool Contention (hakmem_shared_pool_acquire.c) - Added atomic counters: - g_sp_stage2_lock_acquired_global: Stage 2 locks - g_sp_stage3_lock_acquired_global: Stage 3 allocations - g_sp_alloc_lock_contention_global: total lock acquisitions - Instrumented all pthread_mutex_lock calls in hot paths - Added shared_pool_print_measurements() output function ### 4. Benchmark Integration (bench_random_mixed.c) - Called all 3 print functions after benchmark loop - Functions active only when HAKMEM_MEASURE_UNIFIED_CACHE=1 set ## Design Principles - **Zero overhead when disabled**: Inline checks with __builtin_expect hints - **Atomic relaxed memory order**: Minimal synchronization overhead - **ENV-gated**: Single flag controls all measurements - **Production-safe**: Compiles in release builds, no functional changes ## Usage ```bash HAKMEM_MEASURE_UNIFIED_CACHE=1 ./bench_allocators_hakmem bench_random_mixed_hakmem 1000000 256 42 ``` Output (when enabled): ``` ======================================== Unified Cache Statistics ======================================== Hits: 1234567 Misses: 56789 Hit Rate: 95.6% Avg Refill Cycles: 1234 ======================================== TLS SLL Statistics ======================================== Total Pushes: 1234567 Total Pops: 345678 Pop Empty Count: 12345 Hit Rate: 98.8% ======================================== Shared Pool Contention Statistics ======================================== Stage 2 Locks: 123456 (33%) Stage 3 Locks: 234567 (67%) Total Contention: 357 locks per 1M ops ``` ## Next Steps 1. **Enable measurements** and run benchmarks to gather data 2. **Analyze miss rates**: Which bottleneck dominates? 3. **Profile hottest stage**: Focus optimization on top contributor 4. Possible targets: - Increase unified cache capacity if miss rate >5% - Profile if TLS SLL is unused (potential legacy code removal) - Analyze if Stage 2 lock can be replaced with CAS ## Makefile Updates Added core/box/tiny_route_box.o to: - OBJS_BASE (test build) - SHARED_OBJS (shared library) - BENCH_HAKMEM_OBJS_BASE (benchmark) - TINY_BENCH_OBJS_BASE (tiny benchmark) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 18:26:39 +09:00
// Performance measurement: count Stage 3 lock acquisitions
if (__builtin_expect(sp_measure_enabled(), 0)) {
atomic_fetch_add_explicit(&g_sp_stage3_lock_acquired_global, 1, memory_order_relaxed);
atomic_fetch_add_explicit(&g_sp_alloc_lock_contention_global, 1, memory_order_relaxed);
}
// ========== Stage 3: Get new SuperSlab ==========
// Try LRU cache first, then mmap
SuperSlab* new_ss = NULL;
// Stage 3a: Try LRU cache
extern SuperSlab* hak_ss_lru_pop(uint8_t size_class);
new_ss = hak_ss_lru_pop((uint8_t)class_idx);
int from_lru = (new_ss != NULL);
// Stage 3b: If LRU miss, allocate new SuperSlab
if (!new_ss) {
// Release the alloc_lock to avoid deadlock with registry during superslab_allocate
if (g_lock_stats_enabled == 1) {
atomic_fetch_add(&g_lock_release_count, 1);
}
pthread_mutex_unlock(&g_shared_pool.alloc_lock);
WIP: Add TLS SLL validation and SuperSlab registry fallback ChatGPT's diagnostic changes to address TLS_SLL_HDR_RESET issue. Current status: Partial mitigation, but root cause remains. Changes Applied: 1. SuperSlab Registry Fallback (hakmem_super_registry.h) - Added legacy table probe when hash map lookup misses - Prevents NULL returns for valid SuperSlabs during initialization - Status: ✅ Works but may hide underlying registration issues 2. TLS SLL Push Validation (tls_sll_box.h) - Reject push if SuperSlab lookup returns NULL - Reject push if class_idx mismatch detected - Added [TLS_SLL_PUSH_NO_SS] diagnostic message - Status: ✅ Prevents list corruption (defensive) 3. SuperSlab Allocation Class Fix (superslab_allocate.c) - Pass actual class_idx to sp_internal_allocate_superslab - Prevents dummy class=8 causing OOB access - Status: ✅ Root cause fix for allocation path 4. Debug Output Additions - First 256 push/pop operations traced - First 4 mismatches logged with details - SuperSlab registration state logged - Status: ✅ Diagnostic tool (not a fix) 5. TLS Hint Box Removed - Deleted ss_tls_hint_box.{c,h} (Phase 1 optimization) - Simplified to focus on stability first - Status: ⏳ Can be re-added after root cause fixed Current Problem (REMAINS UNSOLVED): - [TLS_SLL_HDR_RESET] still occurs after ~60 seconds of sh8bench - Pointer is 16 bytes offset from expected (class 1 → class 2 boundary) - hak_super_lookup returns NULL for that pointer - Suggests: Use-After-Free, Double-Free, or pointer arithmetic error Root Cause Analysis: - Pattern: Pointer offset by +16 (one class 1 stride) - Timing: Cumulative problem (appears after 60s, not immediately) - Location: Header corruption detected during TLS SLL pop Remaining Issues: ⚠️ Registry fallback is defensive (may hide registration bugs) ⚠️ Push validation prevents symptoms but not root cause ⚠️ 16-byte pointer offset source unidentified Next Steps for Investigation: 1. Full pointer arithmetic audit (Magazine ⇔ TLS SLL paths) 2. Enhanced logging at HDR_RESET point: - Expected vs actual pointer value - Pointer provenance (where it came from) - Allocation trace for that block 3. Verify Headerless flag is OFF throughout build 4. Check for double-offset application in conversions Technical Assessment: - 60% root cause fixes (allocation class, validation) - 40% defensive mitigation (registry fallback, push rejection) Performance Impact: - Registry fallback: +10-30 cycles on cold path (negligible) - Push validation: +5-10 cycles per push (acceptable) - Overall: < 2% performance impact estimated Related Issues: - Phase 1 TLS Hint Box removed temporarily - Phase 2 Headerless blocked until stability achieved 🤖 Generated with Claude Code (https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-03 20:42:28 +09:00
SuperSlab* allocated_ss = sp_internal_allocate_superslab(class_idx);
// Re-acquire the alloc_lock
if (g_lock_stats_enabled == 1) {
atomic_fetch_add(&g_lock_acquire_count, 1);
atomic_fetch_add(&g_lock_acquire_slab_count, 1); // This is part of acquisition path
}
pthread_mutex_lock(&g_shared_pool.alloc_lock);
if (!allocated_ss) {
// Allocation failed; return now.
if (g_lock_stats_enabled == 1) {
atomic_fetch_add(&g_lock_release_count, 1);
}
pthread_mutex_unlock(&g_shared_pool.alloc_lock);
return -1; // Out of memory
}
new_ss = allocated_ss;
// Add newly allocated SuperSlab to the shared pool's internal array
if (g_shared_pool.total_count >= g_shared_pool.capacity) {
shared_pool_ensure_capacity_unlocked(g_shared_pool.total_count + 1);
if (g_shared_pool.total_count >= g_shared_pool.capacity) {
// Pool table expansion failed; leave ss alive (registry-owned),
// but do not treat it as part of shared_pool.
// This is a critical error, return early.
if (g_lock_stats_enabled == 1) {
atomic_fetch_add(&g_lock_release_count, 1);
}
pthread_mutex_unlock(&g_shared_pool.alloc_lock);
return -1;
}
}
g_shared_pool.slabs[g_shared_pool.total_count] = new_ss;
g_shared_pool.total_count++;
}
#if !HAKMEM_BUILD_RELEASE
if (dbg_acquire == 1 && new_ss) {
fprintf(stderr, "[SP_ACQUIRE_STAGE3] class=%d new SuperSlab (ss=%p from_lru=%d)\n",
class_idx, (void*)new_ss, from_lru);
}
#endif
if (!new_ss) {
if (g_lock_stats_enabled == 1) {
atomic_fetch_add(&g_lock_release_count, 1);
}
pthread_mutex_unlock(&g_shared_pool.alloc_lock);
return -1; // ❌ Out of memory
}
// Before creating a new SuperSlab, consult learning-layer soft cap.
// Phase 9-2: Soft Cap removed to allow Shared Pool to fully replace Legacy Backend.
// We now rely on LRU eviction and EMPTY recycling to manage memory pressure.
// Create metadata for this new SuperSlab
SharedSSMeta* new_meta = sp_meta_find_or_create(new_ss);
if (!new_meta) {
if (g_lock_stats_enabled == 1) {
atomic_fetch_add(&g_lock_release_count, 1);
}
pthread_mutex_unlock(&g_shared_pool.alloc_lock);
return -1; // ❌ Metadata allocation failed
}
// Assign first slot to this class
int first_slot = 0;
if (sp_slot_mark_active(new_meta, first_slot, class_idx) != 0) {
if (g_lock_stats_enabled == 1) {
atomic_fetch_add(&g_lock_release_count, 1);
}
pthread_mutex_unlock(&g_shared_pool.alloc_lock);
return -1; // ❌ Should not happen
}
// Update SuperSlab metadata
new_ss->slab_bitmap |= (1u << first_slot);
ss_slab_meta_class_idx_set(new_ss, first_slot, (uint8_t)class_idx);
new_ss->active_slabs = 1;
g_shared_pool.active_count++;
if (class_idx < TINY_NUM_CLASSES_SS) {
g_shared_pool.class_active_slots[class_idx]++;
}
// Update hint
g_shared_pool.class_hints[class_idx] = new_ss;
*ss_out = new_ss;
*slab_idx_out = first_slot;
sp_fix_geometry_if_needed(new_ss, first_slot, class_idx);
if (g_lock_stats_enabled == 1) {
atomic_fetch_add(&g_lock_release_count, 1);
}
pthread_mutex_unlock(&g_shared_pool.alloc_lock);
if (g_sp_stage_stats_enabled) {
atomic_fetch_add(&g_sp_stage3_hits[class_idx], 1);
}
return 0; // ✅ Stage 3 success
}
Performance Measurement Framework: Unified Cache, TLS SLL, Shared Pool Analysis ## Summary Implemented production-grade measurement infrastructure to quantify top 3 bottlenecks: - Unified cache hit/miss rates + refill cost - TLS SLL usage patterns - Shared pool lock contention distribution ## Changes ### 1. Unified Cache Metrics (tiny_unified_cache.h/c) - Added atomic counters: - g_unified_cache_hits_global: successful cache pops - g_unified_cache_misses_global: refill triggers - g_unified_cache_refill_cycles_global: refill cost in CPU cycles (rdtsc) - Instrumented `unified_cache_pop_or_refill()` to count hits - Instrumented `unified_cache_refill()` with cycle measurement - ENV-gated: HAKMEM_MEASURE_UNIFIED_CACHE=1 (default: off) - Added unified_cache_print_measurements() output function ### 2. TLS SLL Metrics (tls_sll_box.h) - Added atomic counters: - g_tls_sll_push_count_global: total pushes - g_tls_sll_pop_count_global: successful pops - g_tls_sll_pop_empty_count_global: empty list conditions - Instrumented push/pop paths - Added tls_sll_print_measurements() output function ### 3. Shared Pool Contention (hakmem_shared_pool_acquire.c) - Added atomic counters: - g_sp_stage2_lock_acquired_global: Stage 2 locks - g_sp_stage3_lock_acquired_global: Stage 3 allocations - g_sp_alloc_lock_contention_global: total lock acquisitions - Instrumented all pthread_mutex_lock calls in hot paths - Added shared_pool_print_measurements() output function ### 4. Benchmark Integration (bench_random_mixed.c) - Called all 3 print functions after benchmark loop - Functions active only when HAKMEM_MEASURE_UNIFIED_CACHE=1 set ## Design Principles - **Zero overhead when disabled**: Inline checks with __builtin_expect hints - **Atomic relaxed memory order**: Minimal synchronization overhead - **ENV-gated**: Single flag controls all measurements - **Production-safe**: Compiles in release builds, no functional changes ## Usage ```bash HAKMEM_MEASURE_UNIFIED_CACHE=1 ./bench_allocators_hakmem bench_random_mixed_hakmem 1000000 256 42 ``` Output (when enabled): ``` ======================================== Unified Cache Statistics ======================================== Hits: 1234567 Misses: 56789 Hit Rate: 95.6% Avg Refill Cycles: 1234 ======================================== TLS SLL Statistics ======================================== Total Pushes: 1234567 Total Pops: 345678 Pop Empty Count: 12345 Hit Rate: 98.8% ======================================== Shared Pool Contention Statistics ======================================== Stage 2 Locks: 123456 (33%) Stage 3 Locks: 234567 (67%) Total Contention: 357 locks per 1M ops ``` ## Next Steps 1. **Enable measurements** and run benchmarks to gather data 2. **Analyze miss rates**: Which bottleneck dominates? 3. **Profile hottest stage**: Focus optimization on top contributor 4. Possible targets: - Increase unified cache capacity if miss rate >5% - Profile if TLS SLL is unused (potential legacy code removal) - Analyze if Stage 2 lock can be replaced with CAS ## Makefile Updates Added core/box/tiny_route_box.o to: - OBJS_BASE (test build) - SHARED_OBJS (shared library) - BENCH_HAKMEM_OBJS_BASE (benchmark) - TINY_BENCH_OBJS_BASE (tiny benchmark) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 18:26:39 +09:00
// ============================================================================
// Performance Measurement: Print Statistics
// ============================================================================
void shared_pool_print_measurements(void) {
if (!sp_measure_enabled()) {
return; // Measurement disabled
}
uint64_t stage2 = atomic_load_explicit(&g_sp_stage2_lock_acquired_global, memory_order_relaxed);
uint64_t stage3 = atomic_load_explicit(&g_sp_stage3_lock_acquired_global, memory_order_relaxed);
uint64_t total_locks = atomic_load_explicit(&g_sp_alloc_lock_contention_global, memory_order_relaxed);
if (total_locks == 0) {
fprintf(stderr, "\n========================================\n");
fprintf(stderr, "Shared Pool Contention Statistics\n");
fprintf(stderr, "========================================\n");
fprintf(stderr, "No lock acquisitions recorded\n");
fprintf(stderr, "========================================\n\n");
return;
}
double stage2_pct = (100.0 * stage2) / total_locks;
double stage3_pct = (100.0 * stage3) / total_locks;
fprintf(stderr, "\n========================================\n");
fprintf(stderr, "Shared Pool Contention Statistics\n");
fprintf(stderr, "========================================\n");
fprintf(stderr, "Stage 2 Locks: %llu (%.1f%%)\n",
(unsigned long long)stage2, stage2_pct);
fprintf(stderr, "Stage 3 Locks: %llu (%.1f%%)\n",
(unsigned long long)stage3, stage3_pct);
fprintf(stderr, "Total Contention: %llu lock acquisitions\n",
(unsigned long long)total_locks);
fprintf(stderr, "========================================\n\n");
}