9acf9fdfdb
- sskj.deploy runtime 支持 NODE_HOSTS 多节点编排(ssh 分发/本地 rank/LOCAL_NODE_RANK)
与 ENGINE=vllm 启动(SERVER_CMD)，容器名按 rank 自动唯一
- scripts/common/deploy_cli.sh 新增 deploy_stop/status/multinode helper 与 node-rank 透传
- src/sskj/common/env.py 修复嵌套 ${VAR:-${OTHER}/path} 展开(平衡花括号扫描)
- deploy/profiles/pro6000/ 新增 6 个 profile: tp16/tp16_eagle/glm52(多节点)、
sglang/vllm tp_dp_matrix、qwen3(单节点)
- 6 个实验 start/stop 脚本改为 deploy 薄包装，run_bench/adaptive 的 server 启停走
deploy_render_args/deploy_start/deploy_stop，tp16 新增 matrix.json
- 首次入库 glm52_pro6000_sglang_multinode_tp16 实验目录；ops/README.md 补 pro6000 章节
- 实测通过: 单节点 dsv4 sglang/vllm 链路 + tp16 双节点启动/bench/清理
38 lines
2.4 KiB
Bash
38 lines
2.4 KiB
Bash
# GLM-5.2-FP8 SGLang multi-node TP=16 deployment profile (2x RTX 6000D).
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# node0 = 174.1.51.5 (pro6000D.1, HTTP API), node1 = 174.1.51.7 (pro6000D.3,
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# compute-only). Model ~700GB fp8 so 2-node TP=16 is mandatory.
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# Requires the tilelang/dsa patch mounts below (experiment-dir sources).
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PLATFORM=pro6000
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EXPERIMENT=glm52_pro6000_sglang_multinode_tp16
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MODEL_NAME=GLM-5.2-FP8
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ENGINE=sglang
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RUNTIME=docker
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DOCKER_IMAGE=lmsysorg/sglang:nightly-dev-cu13-20260720-b3570a45
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CONTAINER_NAME=${EXPERIMENT}_sglang_tp${TP}_dp${DP}_node${NODE_RANK}
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MODEL_PATH=/data/hf_models/GLM-5.2-FP8
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SERVED_MODEL_NAME=GLM-5.2-FP8
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PORT=30031
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HEALTH_PATH=/health
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HEALTH_HOST=174.1.51.5
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HEALTH_WAIT_S=2400
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CONTAINER_PYTHON=python3
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TP=16
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DP=1
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# ---- Multi-node topology (rank order; rank 0 exposes the HTTP API) ----
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NNODES=2
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NODE_HOSTS="174.1.51.5 174.1.51.7"
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NODE_SSH_USER=root
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MASTER_IP=174.1.51.5
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DIST_PORT=50000
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DEVICE_VARS="CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7"
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ENGINE_ENV="PYTHONUNBUFFERED=1 HF_HUB_OFFLINE=1 TRANSFORMERS_OFFLINE=1 PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True,max_split_size_mb:256 NCCL_IB_HCA=mlx5_0,mlx5_3 NCCL_MIN_NCHANNELS=8 NCCL_IB_QPS_PER_CONNECTION=4 NCCL_NET_GDR_LEVEL=PHB NCCL_SOCKET_IFNAME=eth1 NCCL_IB_RETRY_CNT=14 NCCL_IB_TIMEOUT=16"
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DOCKER_FLAGS="--gpus all --privileged --ipc=host --network host --ulimit memlock=-1 --ulimit stack=67108864"
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VOLUMES="${MODEL_PATH}:${MODEL_PATH}:ro ${ROOT_DIR}/sglang_nightly_cu13_cache:/root/.cache"
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PATCH_MOUNTS="${ROOT_DIR}/experiments/pro6000/glm52_pro6000_sglang_multinode_tp16/tilelang_kernel_sm120.py:/sgl-workspace/sglang/python/sglang/kernels/ops/attention/dsa/tilelang_kernel.py:ro ${ROOT_DIR}/experiments/pro6000/glm52_pro6000_sglang_multinode_tp16/dsa_backend.py:/sgl-workspace/sglang/python/sglang/srt/layers/attention/dsa_backend.py:ro ${ROOT_DIR}/experiments/pro6000/glm52_pro6000_sglang_multinode_tp16/dsa_indexer.py:/sgl-workspace/sglang/python/sglang/srt/layers/attention/dsa/dsa_indexer.py:ro"
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LAUNCH_ARGS="--model-path ${MODEL_PATH} --trust-remote-code --tp-size ${TP} --dp-size ${DP} --quantization fp8 --kv-cache-dtype bfloat16 --moe-runner-backend auto --mem-fraction-static 0.80 --context-length 131072 --max-running-requests 64 --cuda-graph-backend-decode disabled --dsa-prefill-backend tilelang --dsa-decode-backend tilelang --host 0.0.0.0 --port ${PORT} --dist-init-addr ${MASTER_IP}:${DIST_PORT} --nnodes ${NNODES} --node-rank ${NODE_RANK}"
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