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>
34 lines
1.0 KiB
C
34 lines
1.0 KiB
C
// learner_env_box.h - Learning Layer ENV Box
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// Purpose: Decide whether CAP Learner thread should run, based on HAKMEM_MODE
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// and HAKMEM_LEARN, without touchingホットパス。
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//
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// Priority:
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// 1. HAKMEM_LEARN is set → 0/1 で明示的に上書き
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// 2. 未設定の場合:
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// HAKMEM_MODE=learning/research → Learner 有効
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// それ以外(minimal/fast/balanced) → Learner 無効
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#pragma once
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#include "../hakmem_config.h"
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#include <stdlib.h>
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static inline int hak_learner_env_should_run(void) {
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static int g_inited = 0;
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static int g_effective = 0;
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if (__builtin_expect(!g_inited, 0)) {
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const char* e = getenv("HAKMEM_LEARN");
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if (e && *e) {
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int v = atoi(e);
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g_effective = (v != 0) ? 1 : 0;
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} else {
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HakemMode m = g_hakem_config.mode;
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g_effective =
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(m == HAKMEM_MODE_LEARNING || m == HAKMEM_MODE_RESEARCH) ? 1 : 0;
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}
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g_inited = 1;
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}
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return g_effective;
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}
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