`unpack_sequence` benchmark runs slower under JIT
還沒有人認領這個 Issue。
- 主要語言
- Python
- 星號
- 77.2k
- 分支
- 36k
- PR 合併指標
- PR 指標待擷取
描述
Bug report
Bug description:
The pyperformance unpack_sequence benchmark is the worst-performing JIT benchmark on https://www.doesjitgobrrr.com — geomean speedup 0.586× (JIT ~1.7× slower).
The benchmark is a single function with 400 inlined a,b,c,d,e,f,g,h,i,j = to_unpack statements inside a for loop. to_unpack = tuple(range(10)) is reused (refcount > 1, so _UNPACK_SEQUENCE_UNIQUE_TUPLE never fires).
Analysis of the slowdown
The JIT covers all 400 unpacks via ~22 sequential traces (~775 uops, ~19 unpacks each), linked tail-to-tail through _EXIT_TRACE → _START_EXECUTOR, totalling ~18 MB of JIT code. This is a consequence of trace length / fitness limits ([UOP_MAX_TRACE_LENGTH] https://github.com/python/cpython/blob/main/Include/internal/pycore_uop.h#L42), EXIT_QUALITY_* from gh-146073) and is arguably fine - 400 inline statements isn't realistic code. Inter-trace transition cost alone would not produce a 1.7× slowdown. Nevertheless, longer traces would help here.
Per unpack: ~33 uops vs tier 1's ~12 bytecodes — ~2.7× more dispatches. The trace recorder unconditionally emits a _CHECK_VALIDITY + _SET_IP pair before every source bytecode at Python/optimizer.c:902-906. Per unpack:
LOAD_FAST_BORROW t (1)
UNPACK_SEQUENCE 10 (1)
STORE_FAST_STORE_FAST × 5 (5; pair-fused by the compiler)
── 7 source bytecodes → 6 _CHECK_VALIDITY+_SET_IP pairs steady state
Tier 1 has no analog. Each _CHECK_VALIDITY issues a load+branch on current_executor->vm_data.valid; each _SET_IP issues a store to frame->instr_ptr. 12 such uops × 400 unpacks × 20000 iterations is the bulk of the regression.
A naive elimination pass cannot drop them because every gap contains at least one uop with HAS_ESCAPES_FLAG — typically _POP_TOP, conservatively flagged as escaping (its Py_DECREF could run __del__).
CPython versions tested on:
CPython main branch
Operating systems tested on:
Linux
貢獻指南
從這裡開始
- 先讀完整個 Issue,再讀專案的貢獻指南。
- 在 Issue 下留言說明你要接手 —— 這能避免兩個人做同樣的事。
- Fork 儲存庫,在一個分支上完成修改。
- 送出 Pull Request,並在描述裡引用這個 Issue 編號。
研究方向
首先重現 pyperformance unpack_sequence 的結果,並閱讀 Python/optimizer.c 中 902-906 行附近的 trace recorder 邏輯。檢查 Include/internal/pycore_uop.h 中的 UOP_MAX_TRACE_LENGTH,並檢視報告中描述的產生 trace 與有效性檢查。此 issue 未定義特定的修正方案或驗收測試,因此請在變更程式碼前確認預期的最佳化以及以 benchmark 為基礎的成功標準。
由索引模型根據 Issue 內容生成。
評估
- 技術堆疊
- python
- 領域
- compilers, performance
- Issue 類型
- 缺陷
- 難度
- 4/5
- 預估耗時
- 3-5 天
- 活躍度
- 冷清
- 描述清晰度
- 需要釐清
- 新手友好度
- 42/100