53de2c47b0
Comprehensive gap analysis produced by reading all 26 CCCL tuning_*.cuh headers (18,094 lines) against all 26 muh tuning_*.cuh headers (3,568 lines). Key findings: - CCCL has 299 benchmark annotation data points (ipt_N.tpb_M format) - SM100 has 157 template specializations across all algorithms - muh has 37 bi100_* named structs (only in reduce/scan/for) - gen_patch currently produces 0 patches (mapping table disconnected) - Zero bi100 struct values validated on actual BI-V100 hardware Only reduce and scan reach READY status. 24/26 are inline-only.
121 lines
5.9 KiB
Markdown
121 lines
5.9 KiB
Markdown
# CCCL ↔ muh 完整 Gap 分析
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> 生成时间: 2026-08-06 | HEAD: 2a7ca10 | 26 算法全量扫描
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## 核心数据
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| 指标 | 值 | 说明 |
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|------|------|------|
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| CCCL 算法总数 | 26 | cub/device/dispatch/tuning/ 下所有 tuning_*.cuh |
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| muh tuning headers | 26 | 1:1 文件对应 ✓ |
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| CCCL 代码行 | 18,094 | 所有 tuning_*.cuh 总和 |
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| muh 代码行 | 3,568 | 19.7% 覆盖率 |
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| CCCL benchmark 注释 | 299 | `ipt_N.tpb_M ... speedup` 格式的数据点 |
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| SM100 模板特化 | 157 | NVIDIA 为 SM100 跑出的最优配置数 |
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| BI-V100 命名 struct | 37 | muh 中 `bi100_*` struct 数量 |
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| 有 bi100 struct 的算法 | 3/26 | reduce(14个), scan(22个), for(1个) |
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| 有 SMEM 保护的算法 | 16/26 | scale_mem_bound 或 while loop |
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## 关键发现
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### 1. 只有 reduce 和 scan 达到了"READY"状态
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reduce 和 scan 是唯一两个同时具备 bi100 命名 struct + SMEM 保护 + 完整 policy_selector 的算法。但即便如此，这些 struct 的值全部是从 SM100 推导的**理论值**，没有一个在 BI-V100 上实测过。
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### 2. 其余 24 个算法停留在"inline only"
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"inline only" 意味着 muh header 里有 policy_selector，但它的值是硬编码在 if/else 分支里的，不是通过命名 struct 暴露的。gen_patch.py 提取不到这些值（它只认 `struct bi100_*` 模式）。
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### 3. CCCL 有 299 个 benchmark 数据点，muh 有 0 个
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CCCL 的 benchmark 注释格式完美定义了目标：
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```
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ipt_22.tpb_384.ns_1904.dcid_6.l2w_830.trp_1.ld_0 1.148442 0.997167 1.139902 1.462651
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```
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四个数字 = 四个 problem size 下的加速比。muh 需要在 BI-V100 上产出同样格式的 299 个数据点来填充所有空位。
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### 4. 竞赛瓶颈不在代码量而在实测数据
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- 代码架构已经搭好（26 个 header + policy_selector + gen_patch 管道）
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- 缺的是 BI-V100 实测数据来替换理论值
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- 没有实测数据，所有 bi100_* struct 的值都是猜的
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## 26 算法状态矩阵
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| 算法 | CCCL 行 | muh 行 | CCCL BM | SM100 特化 | bi100 struct | SMEM✓ | 状态 |
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|------|---------|--------|---------|-----------|-------------|-------|------|
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| reduce | 478 | 297 | 7 | 6 | 14 | ✓ | ✓ READY |
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| scan | 1,525 | 591 | 18 | 12 | 22 | ✓ | ✓ READY |
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| for | 78 | 51 | 0 | 0 | 1 | ✗ | ⚠ no SMEM |
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| topk | 121 | 113 | 0 | 0 | 0 | ✗ | △ inline |
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| transform | 549 | 185 | 0 | 0 | 0 | ✗ | △ inline |
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| batch_memcpy | 227 | 95 | 0 | 0 | 0 | ✗ | △ inline |
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| select_if | 2,729 | 459 | 84 | 52 | 0 | ✓ | △ inline |
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| radix_sort | 2,381 | 222 | 70 | 0 | 0 | ✓ | △ inline |
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| scan_by_key | 2,008 | 145 | 30 | 17 | 0 | ✓ | △ inline |
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| reduce_by_key | 1,735 | 171 | 32 | 22 | 0 | ✓ | △ inline |
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| unique_by_key | 1,539 | 166 | 29 | 21 | 0 | ✓ | △ inline |
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| three_way_partition | 788 | 99 | 13 | 9 | 0 | ✓ | △ inline |
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| rle_non_trivial_runs | 691 | 68 | 8 | 8 | 0 | ✗ | △ inline |
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| segmented_sort | 640 | 189 | 0 | 0 | 0 | ✓ | △ inline |
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| rle_encode | 626 | 63 | 4 | 7 | 0 | ✗ | △ inline |
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| histogram | 363 | 76 | 4 | 3 | 0 | ✗ | △ inline |
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| segmented_radix_sort | 311 | 48 | 0 | 0 | 0 | ✓ | △ inline |
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| batch_memcpy | 227 | 95 | 0 | 0 | 0 | ✗ | △ inline |
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| merge_sort | 193 | 83 | 0 | 0 | 0 | ✓ | △ inline |
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| segmented_reduce | 189 | 51 | 0 | 0 | 0 | ✗ | △ inline |
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| batched_topk | 186 | 66 | 0 | 0 | 0 | ✓ | △ inline |
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| merge | 180 | 89 | 0 | 0 | 0 | ✓ | △ inline |
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| segmented_scan | 158 | 45 | 0 | 0 | 0 | ✓ | △ inline |
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| adjacent_difference | 118 | 77 | 0 | 0 | 0 | ✓ | △ inline |
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| find_bound_sorted_values | 106 | 47 | 0 | 0 | 0 | ✗ | △ inline |
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| find | 90 | 39 | 0 | 0 | 0 | ✓ | △ inline |
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| transform_tile | 85 | 33 | 0 | 0 | 0 | ✗ | △ inline |
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## gen_patch 管道状态
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当前 gen_patch.py 跑出来的结果：
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```
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READ reduce: bi100_plus_float32_o4 → {items:24, threads:512, vec:2}
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READ scan: bi100_sm90_float32 → {threads:128, items:24}
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READ topk: __inline_topk__ → {threads:512, bits_per_pass:11}
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READ transform: __inline_transform__ → {bytes_in_flight:64}
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READ for: bi100_default → {threads:256, items:4}
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SKIP 其余 21 个算法: no bi100_* structs
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```
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**0 个 patch 生成**——因为 VLLM_INJECTION_POINTS 映射表中的 key 与当前 struct 字段名不匹配。这是管道断裂点。
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## CCCL benchmark 源码作为 muh 的输入规范
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CCCL bench/reduce/base.cuh 定义了 benchmark 框架：
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- 参数空间：`%RANGE% TUNE_ITEMS_PER_THREAD ipt 7:24:1` / `%RANGE% TUNE_THREADS_PER_BLOCK tpb 128:1024:32`
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- 输出格式：`ipt_N.tpb_M.ipv_K speedup0 speedup1 speedup2 speedup3`
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- 四个 problem size：`Elements{io}` = 2^16, 2^20, 2^24, 2^28
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muh 的 bench_bi100.py 已经有 topk 的实测数据（最佳配置：ipt=4, tpb=512, ld=0），
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但 reduce/scan/transform 还没跑。
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## CCCL 已有的可直接利用的资产
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| 资产类型 | 数量 | 路径 | 用途 |
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|----------|------|------|------|
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| CUB benchmarks | 80 .cu | cccl_upstream/cub/benchmarks/bench/ | 参数空间搜索框架 |
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| CUB tests | 243 .cu | cccl_upstream/cub/test/ | 正确性验证 |
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| CUB examples | 18 .cu | cccl_upstream/cub/examples/ | API 验证 |
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| Thrust examples | 52 .cu | cccl_upstream/thrust/examples/ | 算法验证 |
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| muh schemas | 27 .yaml | muh/schema/ | 参数空间定义 |
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总计 420 个 .cu 文件可直接编译运行在 BI-V100 上产出数据。
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## 下一步行动
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优先级按竞赛权重排序：
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1. **reduce 实测** (Output TPS × 16.796 = 83%): 用 bench/reduce/sum.cu 框架，在 BI-V100 上扫描 ipt∈[7,24] × tpb∈{128..1024:32} × ipv∈{1,2,4}
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2. **scan 实测** (decode softmax): 用 bench/scan/exclusive/sum.cu 框架，额外标定 LookbackDelay
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3. **topk 补全** (sampling): 已有部分数据，需要补 batch=4 和 bits_per_pass 对比
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4. **gen_patch 闭环**: 修复 VLLM_INJECTION_POINTS 映射，让 gen_patch 真正产出可用 patch
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5. **50+ 功能测试**: 在 patch 后的 vllm 上跑竞赛功能验证
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