3baca14eb1
- Move qwen3.5-397b-int4-autoround.yaml to recipes/4x-spark-cluster/ per maintainer request (multi-node recipes in separate directory) - Add PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to recipe env - Optimize Ray for GB10 UMA (128GB shared CPU/GPU memory): - Disable Ray dashboard (saves ~1.2 GiB per node) - Limit Ray object store to 1 GiB (default 30% of RAM = 33 GiB) - Disable pre-started idle workers (saves ~8 GiB on head node) - Set --num-cpus 2 and --disable-usage-stats on all nodes - Net effect: ~40+ GiB freed across 4-node cluster for model/KV cache
54 lines
1.6 KiB
YAML
54 lines
1.6 KiB
YAML
# Recipe: Qwen3.5-397B-A17B-INT4-Autoround
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# Qwen3.5-397B model in Intel INT4-Autoround quantization, TP=4 across 4 DGX Spark nodes
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# Benchmarked at 37 tok/s single-user, 103 tok/s aggregate (4 concurrent) on 4× DGX Spark
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# Requires NVIDIA driver 580.x (590.x has CUDAGraph deadlock bug on GB10)
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recipe_version: "1"
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name: Qwen3.5-397B-INT4-Autoround
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description: Qwen3.5-397B with TP=4 across 4 DGX Spark nodes (Marlin fix applied)
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# HuggingFace model to download (optional, for --download-model)
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model: Intel/Qwen3.5-397B-A17B-int4-AutoRound
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# Container image to use
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container: vllm-node-tf5
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build_args:
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- --tf5
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# Mods required: coder-next tool/reasoning parser + Marlin TP fix
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mods:
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- mods/fix-qwen3-coder-next
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- mods/fix-qwen35-tp4-marlin
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# Environment variables
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env:
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VLLM_MARLIN_USE_ATOMIC_ADD: 1
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PYTORCH_CUDA_ALLOC_CONF: expandable_segments:True
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# Default settings (can be overridden via CLI, e.g. --tensor_parallel 2)
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defaults:
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port: 8000
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host: 0.0.0.0
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tensor_parallel: 4
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gpu_memory_utilization: 0.78
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max_model_len: 32768
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max_num_batched_tokens: 8192
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# The vLLM serve command template
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command: |
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vllm serve Intel/Qwen3.5-397B-A17B-int4-AutoRound \
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--tool-call-parser qwen3_coder \
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--reasoning-parser qwen3 \
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--enable-auto-tool-choice \
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--tensor-parallel-size {tensor_parallel} \
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--distributed-executor-backend ray \
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--kv-cache-dtype fp8 \
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--gpu-memory-utilization {gpu_memory_utilization} \
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--max-model-len {max_model_len} \
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--max-num-batched-tokens {max_num_batched_tokens} \
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--enable-prefix-caching \
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--trust-remote-code \
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--host {host} \
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--port {port}
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