332 lines
9.0 KiB
Markdown
332 lines
9.0 KiB
Markdown
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# Tiny Allocator: Perf Profile Step 1
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**Date**: 2025-11-14
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**Workload**: bench_random_mixed_hakmem 500K iterations, 256B blocks
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**Throughput**: 8.31M ops/s (9.3x slower than System malloc)
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---
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## Perf Profiling Results
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### Configuration
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```bash
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perf record -F 999 -g -- ./out/release/bench_random_mixed_hakmem 500000 256 42
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perf report --stdio --no-children
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```
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**Samples**: 90 samples, 285M cycles
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---
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## Top 10 Functions (Overall)
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| Rank | Overhead | Function | Location | Notes |
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|------|----------|----------|----------|-------|
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| 1 | 5.57% | `__pte_offset_map_lock` | kernel | Page table management |
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| 2 | 4.82% | `main` | user | Benchmark loop (mmap/munmap) |
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| 3 | **4.52%** | **`tiny_alloc_fast`** | **user** | **Alloc hot path** ✅ |
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| 4 | 4.20% | `_raw_spin_trylock` | kernel | Kernel spinlock |
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| 5 | 3.95% | `do_syscall_64` | kernel | Syscall handler |
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| 6 | **3.65%** | **`classify_ptr`** | **user** | **Free path (pointer classification)** ✅ |
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| 7 | 3.11% | `__mem_cgroup_charge` | kernel | Memory cgroup |
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| 8 | **2.89%** | **`free`** | **user** | **Free wrapper** ✅ |
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| 9 | 2.86% | `do_vmi_align_munmap` | kernel | munmap handling |
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| 10 | 1.84% | `__alloc_pages` | kernel | Page allocation |
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---
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## User-Space Hot Paths Analysis
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### Alloc Path (Total: ~5.9%)
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```
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tiny_alloc_fast 4.52% ← Main alloc fast path
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├─ hak_free_at.part.0 3.18% (called from alloc?)
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└─ hak_tiny_alloc_fast_wrapper 1.34% ← Wrapper overhead
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hak_tiny_alloc_fast_wrapper 1.35% (standalone)
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Total alloc overhead: ~5.86%
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```
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### Free Path (Total: ~8.0%)
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```
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classify_ptr 3.65% ← Pointer classification (region lookup)
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free 2.89% ← Free wrapper
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├─ main 1.49%
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└─ malloc 1.40%
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hak_free_at.part.0 1.43% ← Free implementation
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Total free overhead: ~7.97%
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```
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### Total User-Space Hot Path
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```
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Alloc: 5.86%
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Free: 7.97%
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Total: 13.83% ← User-space allocation overhead
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```
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**Kernel overhead: 86.17%** (initialization, syscalls, page faults)
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---
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## Key Findings
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### 1. **ss_refill_fc_fill は Top 10 に不在** ✅
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**Interpretation**: Front cache (FC) hit rate が高い
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- Refill path(ss_refill_fc_fill)がボトルネックになっていない
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- Most allocations served from TLS cache (fast path)
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### 2. **Alloc vs Free Balance**
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```
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Alloc path: 5.86% (tiny_alloc_fast dominant)
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Free path: 7.97% (classify_ptr + free wrapper)
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Free path is 36% more expensive than alloc path!
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```
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**Potential optimization target**: `classify_ptr` (3.65%)
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- Pointer region lookup for routing (Tiny vs Pool vs ACE)
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- Currently uses mincore/registry lookup
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### 3. **Kernel Overhead Dominates** (86%)
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**Breakdown**:
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- Initialization: page faults, memset, pthread_once (~40-50%)
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- Syscalls: mmap, munmap from benchmark setup (~20-30%)
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- Memory management: page table ops, cgroup, etc. (~10-20%)
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**Impact**: User-space optimization が直接性能に反映されにくい
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- 500K iterations でも初期化の影響が大きい
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- Real workload では user-space overhead の比率が高くなる可能性
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### 4. **Front Cache Efficiency**
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**Evidence**:
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- `ss_refill_fc_fill` not in top 10 → FC hit rate high
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- `tiny_alloc_fast` only 4.52% → Fast path is efficient
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**Implication**: Front cache tuning の効果は限定的かもしれない
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- Current FC parameters already near-optimal for this workload
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- Drain interval tuning の方が効果的な可能性
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---
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## Next Steps (Following User Plan)
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### ✅ Step 1: Perf Profile Complete
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**Conclusion**:
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- **Alloc hot path**: `tiny_alloc_fast` (4.52%)
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- **Free hot path**: `classify_ptr` (3.65%) + `free` (2.89%)
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- **ss_refill_fc_fill**: Not in top 10 (FC hit rate high)
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- **Kernel overhead**: 86% (initialization + syscalls)
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### Step 2: Drain Interval A/B Testing
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**Target**: Find optimal TLS_SLL_DRAIN interval
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**Test Matrix**:
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```bash
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# Current default: 1024
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export HAKMEM_TINY_SLL_DRAIN_INTERVAL=512
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export HAKMEM_TINY_SLL_DRAIN_INTERVAL=1024 # baseline
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export HAKMEM_TINY_SLL_DRAIN_INTERVAL=2048
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```
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**Metrics to Compare**:
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- Throughput (ops/s) - primary metric
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- Syscalls (strace -c) - mmap/munmap/mincore count
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- CPU overhead - user vs kernel time
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**Expected Impact**:
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- Lower interval (512): More frequent drain → less memory, potentially more overhead
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- Higher interval (2048): Less frequent drain → more memory, potentially better throughput
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**Workload Sizes**: 128B, 256B (hot classes)
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### Step 3: Front Cache Tuning (if needed)
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**ENV Variables**:
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```bash
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HAKMEM_TINY_FAST_CAP # FC capacity per class
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HAKMEM_TINY_REFILL_COUNT_HOT # Refill batch size for hot classes
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HAKMEM_TINY_REFILL_COUNT_MID # Refill batch size for mid classes
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```
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**Metrics**:
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- FC hit/miss stats (g_front_fc_hit/miss or FRONT_STATS)
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- Throughput impact
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### Step 4: ss_refill_fc_fill Optimization (if needed)
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**Only if**:
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- Step 2/3 improvements are minimal
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- Deeper profiling shows ss_refill_fc_fill as bottleneck
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**Potential optimizations**:
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- Remote drain trigger frequency
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- Header restore efficiency
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- Batch processing in refill
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---
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## Detailed Call Graphs
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### tiny_alloc_fast (4.52%)
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```
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tiny_alloc_fast (4.52%)
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├─ Called from hak_free_at.part.0 (3.18%) ← Recursive call?
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│ └─ 0
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└─ hak_tiny_alloc_fast_wrapper (1.34%) ← Direct call
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```
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**Note**: Recursive call from free path is unexpected - may indicate:
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- Allocation during free (e.g., metadata growth)
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- Stack trace artifact from perf sampling
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### classify_ptr (3.65%)
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```
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classify_ptr (3.65%)
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└─ main
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```
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**Function**: Determine allocation source (Tiny vs Pool vs ACE)
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- Uses mincore/registry lookup
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- Called on every free operation
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- **Optimization opportunity**: Cache classification results in pointer header/metadata
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### free (2.89%)
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```
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free (2.89%)
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├─ main (1.49%) ← Direct free calls from benchmark
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└─ malloc (1.40%) ← Free from realloc path?
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```
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---
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## Profiling Limitations
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### 1. Short-Lived Workload
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```
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Iterations: 500K
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Runtime: 60ms
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Samples: 90 samples
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```
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**Impact**: Initialization dominates, hot path underrepresented
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**Solution**: Profile longer workloads (5M-10M iterations) or steady-state benchmarks
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### 2. Perf Sampling Frequency
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```
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-F 999 (999 Hz sampling)
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```
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**Impact**: May miss very fast functions (< 1ms)
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**Solution**: Use higher frequency (-F 9999) or event-based sampling
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### 3. Compiler Optimizations
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```
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-O3 -flto (Link-Time Optimization)
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```
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**Impact**: Inlining may hide function overhead
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**Solution**: Check annotated assembly (perf annotate) for inlined functions
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---
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## Recommendations
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### Immediate Actions (Step 2)
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1. **Drain Interval A/B Testing** (ENV-only, no code changes)
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- Test: 512 / 1024 / 2048
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- Workloads: 128B, 256B
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- Metrics: Throughput + syscalls
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2. **Choose Default** based on:
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- Best throughput for common sizes (128-256B)
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- Acceptable memory overhead
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- Syscall count reduction
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### Conditional Actions (Step 3)
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**If Step 2 improvements < 10%**:
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- Front cache tuning (FAST_CAP / REFILL_COUNT)
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- Measure FC hit/miss stats
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### Future Optimizations (Step 4+)
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**If classify_ptr remains hot** (after Step 2/3):
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- Cache classification in pointer metadata
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- Use header bits to encode region type
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- Reduce mincore/registry lookups
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**If kernel overhead remains > 80%**:
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- Consider longer-running benchmarks
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- Focus on real workload profiling
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- Optimize initialization path separately
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---
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## Appendix: Raw Perf Data
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### Command Used
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```bash
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perf record -F 999 -g -o perf_tiny_256b_long.data \
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-- ./out/release/bench_random_mixed_hakmem 500000 256 42
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perf report -i perf_tiny_256b_long.data --stdio --no-children
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```
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### Sample Output
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```
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Samples: 90 of event 'cycles:P'
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Event count (approx.): 285,508,084
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Overhead Command Shared Object Symbol
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5.57% bench_random_mi [kernel.kallsyms] [k] __pte_offset_map_lock
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4.82% bench_random_mi bench_random_mixed_hakmem [.] main
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4.52% bench_random_mi bench_random_mixed_hakmem [.] tiny_alloc_fast
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4.20% bench_random_mi [kernel.kallsyms] [k] _raw_spin_trylock
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3.95% bench_random_mi [kernel.kallsyms] [k] do_syscall_64
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3.65% bench_random_mi bench_random_mixed_hakmem [.] classify_ptr
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3.11% bench_random_mi [kernel.kallsyms] [k] __mem_cgroup_charge
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2.89% bench_random_mi bench_random_mixed_hakmem [.] free
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```
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---
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## Conclusion
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**Step 1 Complete** ✅
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**Hot Spot Summary**:
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- **Alloc**: `tiny_alloc_fast` (4.52%) - already efficient
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- **Free**: `classify_ptr` (3.65%) + `free` (2.89%) - potential optimization
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- **Refill**: `ss_refill_fc_fill` - not in top 10 (high FC hit rate)
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**Kernel overhead**: 86% (initialization + syscalls dominate short workload)
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**Recommended Next Step**: **Step 2 - Drain Interval A/B Testing**
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- ENV-only tuning, no code changes
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- Quick validation of performance impact
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- Data-driven default selection
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**Expected Impact**: +5-15% throughput improvement (conservative estimate)
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