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For a prefill chunk the per-row path decoded rows x topk KV records (128 x 640 a layer: 31.8 ms of a 49.6 ms attention region at TP=64). The chunk path now decodes each cache scope once into a bf16 table (pages x page slots, NaN-free) and the gathered_attn_idx kernel gathers each row's slots in SBUF, as vllm-neuron#71 does. Used while the caches hold <= 32768 slots (DEEPINFER_NEURON_ATTN_TABLE_SLOTS); size the pool with --num_kv_blocks. Tiny V4.1 on a NeuronCore: short 8/9, long 9/9, cos >= 0.9979. 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 | ||