819850c4a1
- Add all H200 experiments: TP/DP matrix, adaptive concurrency, custom bench, MTP vs default, long context matrix, 64k/256k probes - Add RTX 6000D platform and experiments (sglang/vllm TP/DP adaptive) - Update environment requirements section with RTX 6000D details - Update platforms directory description to include RTX 6000D
191 lines
7.9 KiB
Markdown
191 lines
7.9 KiB
Markdown
# DSV4 / DeepSeek-V4-Flash 推理测速项目
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> 记录 vllm-dspark、SGLang、vLLM 等后端在 DeepSeek-V4-Flash 上的 benchmark 脚本与最终结果。
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> H200 快速上手指南见 [`docs/H200_QUICKSTART.md`](docs/H200_QUICKSTART.md)。
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## 目录说明
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| 目录/文件 | 说明 |
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| `platforms/` | 芯片/加速器平台配置（`*.env`），如 P800、H200、RTX 6000D |
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| `scripts/common/` | 跨实验复用的 orchestration 组件（server 启停、health check、元数据生成、结果解析） |
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| `scripts/` | 仅保留仍在使用的 legacy DSpark 脚本与 SLO 标准 |
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| `experiments/` | 以实验为单位的自包含目录（脚本 + 配置 + 结果） |
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| `experiments/legacy_bench_results/` | 历史归档的实验产物（只读），从原 `bench_results/` 迁移而来 |
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| `BENCHMARK_WORKFLOW.md` | benchmark 目录与命名规范 |
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| `docs/SLO_STANDARDS.md` | 推理服务 SLO 标准（TTFT/TPOT） |
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> 注：`.gitignore` 已排除 `envs/`、`deps/`、`tmp/`、`datasets/`、`logs/`、`*.zip`、原始 `raw_outputs/*.jsonl` 等大文件/中间文件。
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## 实验索引
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### 新结构（experiments/）
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| 实验 | 脚本 | 说明 |
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| DSV4 P800 SGLang | `experiments/dsv4_p800_sglang/run_bench.sh` | Kunlun P800 + SGLang + DeepSeek-V4-Flash-INT8 |
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| DSV4 H200 DSpark | `experiments/dsv4_h200_dspark/run_bench.sh` | NVIDIA H200 + vllm-dspark + DeepSeek-V4-Flash-DSpark |
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| DSV4 H200 vLLM baseline | `experiments/dsv4_h200_vllm/run_bench.sh` | NVIDIA H200 + vLLM + DeepSeek-V4-Flash |
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| DSV4 H200 SGLang baseline | `experiments/dsv4_h200_sglang/run_bench.sh` | NVIDIA H200 + native SGLang + DeepSeek-V4-Flash |
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| DSV4 H200 SGLang vs vLLM | `experiments/dsv4_h200_sglang_vs_vllm/run_bench.sh` | NVIDIA H200 上 SGLang 与 vLLM 控制变量对比（TP=8，最长 200k 上下文） |
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| DSV4 H200 vLLM DSpark vs default | `experiments/dsv4_h200_vllm_dspark_vs_default/run_bench.sh` | vLLM 开启 DSpark 投机解码 vs 默认配置，验证 TTFT 差异 |
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| DSV4 H200 max context length | `experiments/dsv4_h200_max_context_length/run_bench.sh` | 探索 SGLang / vLLM 在 H200 上能支持的最大输入长度 |
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| DSV4 H200 SGLang TP/DP Matrix | `experiments/dsv4_h200_sglang_tp_dp_matrix/run_bench.sh` | H200 上 SGLang 不同 TP×DP 配置的固定并发矩阵测试 |
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| DSV4 H200 SGLang TP/DP Adaptive | `experiments/dsv4_h200_sglang_tp_dp_matrix/run_adaptive_concurrency.sh` | H200 上 SGLang 不同 TP×DP 配置的自适应并发饱和点搜索 |
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| DSV4 H200 vLLM TP/DP Matrix | `experiments/dsv4_h200_vllm_tp_dp_matrix/run_bench.sh` | H200 上 vLLM 不同 TP×DP 配置的固定并发矩阵测试 |
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| DSV4 H200 vLLM TP/DP Adaptive | `experiments/dsv4_h200_vllm_tp_dp_matrix/run_adaptive_concurrency.sh` | H200 上 vLLM 不同 TP×DP 配置的自适应并发饱和点搜索 |
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| DSV4 H200 64k SGLang vs vLLM | `experiments/dsv4_h200_64k_sglang_vs_vllm/run_bench.sh` | H200 上 64k 上下文 SGLang 与 vLLM 对比 |
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| DSV4 H200 256k 4k Probe | `experiments/dsv4_h200_256k_4k_probe/run_bench.sh` | H200 上 256k 输入/4k 输出长上下文探测 |
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| DSV4 H200 vLLM TP2 Custom Bench | `experiments/dsv4_h200_vllm_tp2_custom_bench/run_bench.sh` | H200 上 vLLM TP=2 自定义压测客户端（多服务负载均衡） |
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| DSV4 H200 vLLM TP4 Custom Bench | `experiments/dsv4_h200_vllm_tp4_custom_bench/run_bench.sh` | H200 上 vLLM TP=4 自定义压测客户端 |
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| DSV4 H200 vLLM TP8 Custom Bench | `experiments/dsv4_h200_vllm_tp8_custom_bench/run_bench.sh` | H200 上 vLLM TP=8 自定义压测客户端 |
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| DSV4 H200 vLLM MTP vs Default | `experiments/dsv4_h200_vllm_mtp_vs_default/run_bench.sh` | H200 上 vLLM MTP（Multi-Token Prediction）vs 默认配置对比 |
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| DSV4 H200 Long Context Matrix | `experiments/dsv4_h200_long_context_matrix/run_bench.sh` | H200 上长上下文矩阵测试（多后端对比） |
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| **DSV4 RTX 6000D SGLang TP/DP Adaptive** | `experiments/dsv4_pro6000_sglang_tp_dp_matrix/run_adaptive_concurrency.sh` | **RTX 6000D 上 SGLang 自适应并发饱和点搜索** |
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| **DSV4 RTX 6000D vLLM TP/DP Adaptive** | `experiments/dsv4_pro6000_vllm_tp_dp_matrix/run_adaptive_concurrency.sh` | **RTX 6000D 上 vLLM 自适应并发饱和点搜索** |
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### 旧结构（scripts/ + bench_results/）
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仅保留还在被 `experiments/dsv4_h200_dspark/` 引用的 legacy DSpark 脚本，其余旧脚本已删除。
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| 实验 | 脚本 | 最终报告 | 说明 |
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| DSpark grid benchmark | `scripts/benchmark_dspark_0707/run_dspark_benchmark_grid.sh` | `experiments/legacy_bench_results/dspark_grid_20260707-132641/report.md` | P1/P2/P3 全量网格 |
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| DSpark spec-tokens 对比 | `scripts/benchmark_dspark_0707/run_dspark_st_comparison.sh` | `experiments/legacy_bench_results/dspark_st_comparison_20260707-150649/comparison_report.md` | `--spec-tokens 3` vs `5` |
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## 快速复现
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### P800 SGLang
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```bash
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bash experiments/dsv4_p800_sglang/run_bench.sh
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```
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### H200 DSpark
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```bash
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bash experiments/dsv4_h200_dspark/run_bench.sh
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```
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### H200 SGLang baseline
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```bash
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bash experiments/dsv4_h200_sglang/run_bench.sh
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```
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### H200 SGLang vs vLLM 对比
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```bash
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bash experiments/dsv4_h200_sglang_vs_vllm/run_bench.sh
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```
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### H200 vLLM DSpark vs default
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```bash
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bash experiments/dsv4_h200_vllm_dspark_vs_default/run_bench.sh
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```
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### H200 SGLang TP/DP Matrix
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```bash
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bash experiments/dsv4_h200_sglang_tp_dp_matrix/run_bench.sh
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```
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### H200 SGLang TP/DP 自适应并发搜索
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```bash
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bash experiments/dsv4_h200_sglang_tp_dp_matrix/run_adaptive_concurrency.sh
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```
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### H200 vLLM TP/DP Matrix
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```bash
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bash experiments/dsv4_h200_vllm_tp_dp_matrix/run_bench.sh
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```
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### H200 vLLM TP/DP 自适应并发搜索
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```bash
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bash experiments/dsv4_h200_vllm_tp_dp_matrix/run_adaptive_concurrency.sh
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```
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### H200 64k SGLang vs vLLM
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```bash
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bash experiments/dsv4_h200_64k_sglang_vs_vllm/run_bench.sh
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```
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### H200 256k 4k Probe
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```bash
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bash experiments/dsv4_h200_256k_4k_probe/run_bench.sh
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```
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### H200 vLLM TP2/TP4/TP8 Custom Bench
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```bash
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bash experiments/dsv4_h200_vllm_tp2_custom_bench/run_bench.sh
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bash experiments/dsv4_h200_vllm_tp4_custom_bench/run_bench.sh
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bash experiments/dsv4_h200_vllm_tp8_custom_bench/run_bench.sh
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```
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### H200 vLLM MTP vs Default
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```bash
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bash experiments/dsv4_h200_vllm_mtp_vs_default/run_bench.sh
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```
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### H200 Long Context Matrix
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```bash
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bash experiments/dsv4_h200_long_context_matrix/run_bench.sh
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```
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### RTX 6000D SGLang TP/DP 自适应并发搜索
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```bash
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bash experiments/dsv4_pro6000_sglang_tp_dp_matrix/run_adaptive_concurrency.sh
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```
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### RTX 6000D vLLM TP/DP 自适应并发搜索
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```bash
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bash experiments/dsv4_pro6000_vllm_tp_dp_matrix/run_adaptive_concurrency.sh
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```
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### DSpark grid / spec-tokens（旧结构）
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```bash
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bash scripts/benchmark_dspark_0707/run_dspark_benchmark_grid.sh
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bash scripts/benchmark_dspark_0707/run_dspark_st_comparison.sh
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```
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### 解析已有结果
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```bash
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# 新结构
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python3 experiments/dsv4_h200_dspark/parse_results.py \
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experiments/dsv4_h200_dspark/results/<run_id>
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# 旧结构
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/data/user1/yy/envs/sglang/bin/python scripts/benchmark_dspark_0707/parse_results.py \
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/data/user1/yy/experiments/legacy_bench_results/dspark_grid_20260707-132641
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```
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## SLO 参考
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详见 `docs/SLO_STANDARDS.md`。
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主要关注指标：
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- **TTFT P95**：S2（DeepSeek-V4-Flash 所在层）目标 `< 3s`
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- **TPOT**：S2 目标 `< 50ms`
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## 环境要求
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- **NVIDIA H200**：Python env `/data/user1/yy/envs/vllm-dspark`（服务端）、`/data/user1/yy/envs/sglang`（压测客户端）；模型 `/data/models/DeepSeek-V4-Flash`、`/data/models/DeepSeek-V4-Flash-DSpark`。
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- **NVIDIA RTX 6000D**：Python env `/root/.miniconda3/envs/sglang`（压测客户端）；模型 `/data/hf_models/DeepSeek-V4-Flash`；Docker 镜像 `lmsysorg/sglang:latest`、`vllm/vllm-openai:latest`。
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- **Kunlun P800**：Docker 镜像 `iregistry.baidu-int.com/xpu/sglang-p800-pd-disagg-0510:20260511_4202`；模型 `/data1/models/DeepSeek-V4-Flash-INT8`；压测客户端在容器内运行。
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平台相关常量见 `platforms/*.env`。
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