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- serve/: the minimal OpenAI-compatible server of deepseek-ai/DeepInfer#147, with a Neuron worker setup (basic mode env, per-rank NeuronCore, fixed KV pool via --num-kv-blocks, no MTP lookahead) and a /v1/completions endpoint (prompt text or token ids, no chat template): what vllm bench serve --backend openai drives, as vllm-neuron#71's run_bench.py does. - examples/neuron/bench_neuron.py: the same TTFT/TPOT matrix offline. - static MoE: one packed fp32 all-gather instead of three (each 64-rank collective is ~2 ms of fixed latency a layer); a capacity-grouped expert path for prefill chunks (DEEPINFER_NEURON_MOE_CAPACITY, dense rerun on overflow; not yet validated on device). - Sub-region timings at split() boundaries under DEEPINFER_NEURON_REGION_TIMING. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> |
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| .. | ||
| _C | ||
| distributed | ||
| engine | ||
| entrypoints | ||
| hugging_face | ||
| model_executor | ||
| neuron_ops | ||
| npu_ops | ||
| structure_output | ||
| ve | ||
| worker | ||
| __init__.py | ||
| attrdict.py | ||
| config.py | ||
| environ.py | ||
| load_class.py | ||
| logger.py | ||
| model_config_loader.py | ||
| multimodal_tokens.py | ||
| platform.py | ||
| py.typed | ||
| sampling_params.py | ||
| sequence.py | ||
| shared_memory.py | ||
| testing.py | ||
| timer.py | ||
| utils.py | ||