feat: LOD 网格分级——meshopt 解析期简化 + 按距离/级联选级

vendored meshoptimizer 1.2（submodule 环境故障改直接 vendor）。Mesh
多 LOD：各级索引连续拼进同一 index buffer（共享顶点，LodRange 区间
选择），解析期 meshopt_simplify 生成链（LOD0=原始，每级目标减半，
相对误差 1e-2，小网格复用上级）；都在 worker 线程，加载零额外卡顿。

SceneRenderer 按 (mesh, LOD) 聚合 batch（lookup key = 指针<<8|lod）：
主视图按屏占比近似 radius/dist 选级（阈值 10/20 倍半径）；阴影级联
按级联序降级（越远越简）。Draw 按 batch.lod 选索引区间。

A/B 对比（100 背包 10×10，RTX 5060 Laptop，vsync off）：
- 纯背包：LOD 开 93-95 fps / 关 90-107 fps —— 无显著差异
- 加 SunTemple：LOD 开 52-56 / 关 51-55 —— 无显著差异
结论：当前场景瓶颈不在顶点数（5060 顶点吞吐富余），LOD 基础设施
保留（几何复杂资产/低端 GPU/更大场景生效），帧率问题转向 Tracy
GPU 时间线定位真实瓶颈。

坑：LodRange 记录"LOD 不足复用最后一级"时 first 不得继续累加
（buffer 无重复数据，累加必越界——VUID-08798 抓的）。

Lib/meshoptimizer/tools/gltfbasis.py

@@ -0,0 +1,77 @@
+#!/usr/bin/python3
+
+import argparse
+import concurrent.futures
+import matplotlib.pyplot as plt
+import os
+import os.path
+import re
+import subprocess
+
+argp = argparse.ArgumentParser()
+argp.add_argument('--basisu', type=str, required=True)
+argp.add_argument('--graph', type=str, default="basisu.png")
+argp.add_argument('--etcbase', action='store_true')
+argp.add_argument('files', type=str, nargs='+')
+args = argp.parse_args()
+
+def compress(path, flags):
+    temp_path = "/dev/null" if os.name == "posix" else "NUL"
+    output = subprocess.check_output([args.basisu, "-file", path, "-output_file", temp_path, "-stats", "-ktx2"] + flags)
+    for line in output.splitlines():
+        if m := re.match(r".*source image.*?(\d+)x(\d+)", line.decode()):
+            pixels = int(m.group(1)) * int(m.group(2))
+        elif m := re.match(r".*Compression succeeded.*size (\d+) bytes", line.decode()):
+            bytes = int(m.group(1))
+        elif m := re.match(r"\.basis RGB Avg:.*RMS: (\d+\.\d+) PSNR: (\d+\.\d+)", line.decode()):
+            rms = float(m.group(1))
+            psnr = float(m.group(2))
+
+    return {'path': path, 'bpp': bytes * 8 / pixels, 'rms': rms, 'psnr': psnr}
+
+def stats(path):
+    with concurrent.futures.ThreadPoolExecutor(16) as executor:
+        futures = []
+        for i in range(0, 26):
+            rdo_l = i / 5
+            flags = ["-uastc", "-uastc_level", "1", "-uastc_rdo_l", str(rdo_l), "-uastc_rdo_d", "1024"]
+            futures.append((executor.submit(compress, path, flags), rdo_l))
+        concurrent.futures.wait([f for (f, r) in futures])
+        results = []
+        bppbase = 0
+        for future, rdo_l in futures:
+            res = future.result()
+            if rdo_l == 0:
+                bppbase = res['bpp']
+            res['rdo_l'] = rdo_l
+            res['ratio'] = res['bpp'] / bppbase
+            results.append(res)
+        return results
+
+fields = ['bpp', 'rms', 'psnr', 'ratio']
+fig, axs = plt.subplots(1, len(fields) + 1, layout='constrained')
+fig.set_figwidth(5 * (len(fields) + 1))
+lines = []
+
+for path in args.files:
+    print('Processing', path)
+    results = stats(path)
+    etcbase = compress(path, ["-q", "192"]) if args.etcbase else None
+
+    for idx, field in enumerate(fields):
+        line, = axs[idx].plot([r['rdo_l'] for r in results], [r[field] for r in results])
+        if etcbase and field in etcbase:
+            axs[idx].axhline(etcbase[field], color=line.get_color(), linestyle='dotted')
+        if idx == 0:
+            lines.append(line)
+
+    axs[len(fields)].scatter([r['ratio'] for r in results], [r['psnr'] for r in results], color=line.get_color())
+
+for idx, field in enumerate(fields):
+    axs[idx].set_title(field)
+
+axs[len(fields)].set_title('psnr vs ratio')
+
+fig.legend(lines, [os.path.basename(path) for path in args.files], loc='outside right upper')
+
+plt.savefig(args.graph)