Add FlagGems single-op perf benchmark harness

pytest plugin set + driver script for compiler A/B perf comparison:
- reproducible runs: fixed seed, yaml-driven shapes, autotune record/replay
- per-shape ttgir dump of actually-used variants with readable naming
- cudagraph-based timing with documented fallback semantics

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

_seed_plugin.py

@@ -0,0 +1,39 @@
+"""pytest plugin: seed random/numpy/torch RNG for reproducible benchmark inputs.
+
+Data-dependent kernels (sort, topk, nonzero, ...) have value-dependent latency;
+a fixed seed makes every run generate byte-identical inputs, so the latency
+delta between two runs reflects the change under test, not the input data.
+"""
+
+from __future__ import annotations
+
+import sys
+
+_SEED = 0
+
+
+def pytest_configure(config):
+    seed = _SEED
+    # random.seed too: some kits (cutlass_scaled_mm) pick cases via random.shuffle.
+    import random
+    random.seed(seed)
+    seeded = ["random"]
+    try:
+        import numpy as _np
+        _np.random.seed(seed)
+        seeded.append("numpy")
+    except Exception:
+        pass
+    try:
+        import torch
+    except Exception as exc:  # torch missing should never happen here, stay safe
+        print(f"[seed-plugin] torch unavailable, seeded {'+'.join(seeded)} only: {exc}",
+              file=sys.stderr)
+        return
+    torch.manual_seed(seed)
+    if torch.cuda.is_available():
+        torch.cuda.manual_seed_all(seed)
+    seeded.append("torch")
+    print(f"[seed-plugin] manual_seed({seed}) for {'+'.join(seeded)} "
+          "— reproducible benchmark inputs/cases",
+          file=sys.stderr, flush=True)