perf: Numba JIT kernel per score_by_shift (2.1x speedup)

- Nuovo modulo pm2d/_jit_kernels.py con _jit_score_by_shift Numba njit
  parallel + fastmath + boundscheck=False
- Parallelizzazione per riga output (no race condition su acc)
- Fallback automatico numpy se numba non installato
- Warmup automatico al module import (evita JIT lag al 1 match)

Benchmark clip.png (13 istanze):
  prima (numpy + threads): 1.55s
  dopo (numba + threads):  0.72s
  speedup: 2.1x

Pipeline totale full (refine+subpix): 0.80s

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

pm2d/__init__.py

@@ -1,7 +1,14 @@
 from pm2d.matcher import EdgeShapeMatcher, Match, Template
 from pm2d.line_matcher import LineShapeMatcher, Match as LineMatch
+from pm2d._jit_kernels import HAS_NUMBA, _warmup as _warmup_jit
+
+# Precompila kernel JIT in background al primo import (evita lag al 1° match)
+try:
+    _warmup_jit()
+except Exception:
+    pass
 
 __all__ = [
     "EdgeShapeMatcher", "Match", "Template",
-    "LineShapeMatcher", "LineMatch",
+    "LineShapeMatcher", "LineMatch", "HAS_NUMBA",
 ]