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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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| .. | ||
| eplb | ||
| input_metadata | ||
| layers | ||
| models | ||
| parallel_utils | ||
| __init__.py | ||
| layer_utils.py | ||
| model_loader.py | ||
| model_metadata_utils.py | ||
| model_output.py | ||
| sampling_inputs.py | ||
| utils.py | ||