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- NUMA: each worker sees one core, so which_numa(local_rank) failed on all but local rank 0 and every worker inherited its MPOL_BIND to node 1: all host memory landed on one node and a run could be OOM-killed. - DEEPINFER_NEURON_WHOLE_ATTN_MIN_ROWS=512: no cuts inside the attention half of a >=512-row step, only before the MoE (its collectives are another group kind). - MALLOC_TRIM_THRESHOLD_/MALLOC_TOP_PAD_ defaults: compile-time host memory per rank stops growing ~15 GB. (MALLOC_ARENA_MAX=2 bounds it too but costs ~50 ms TTFT.) 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 | ||