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- deep_select.topk on a NeuronCore with k >= 1024 (the sampler's force_topk 4096 over the 129280 vocab) uses nkilib's rotational_topk: torch.topk with that k does not compile on the device (NCC_IXCG857). 8.4 ms on one core, values identical to torch.topk. - EngramBuffer on Neuron: the ranks of a trn2 instance share one host, so the table shards are written into /dev/shm-backed tables (unlinked once mapped) and every rank gathers its own rows: no all-to-all and no host sync on split sizes per fetch. DEEPINFER_NEURON_ENGRAM_SHARED=0 restores the sharded path. Host EP=2 tiny: logits bitwise equal to the sharded path. 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 | ||