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c24574bfd6
- Layer-major KV / state layout so per-layer views are contiguous graph inputs (the executor copied non-contiguous inputs every call). - One compiled entry per (class, method), rank as a registered buffer, no layer_idx guard: every layer reuses the same graphs and loaded NEFFs. - fp8 weight rescale on the host (numpy LUT, ~2 min instead of 35+ min of eager per-shape compiles); engram sf packing on the host. - int16 ue8m0 packing in fp32 (int32 interleaved slices narrowed to int16 crash neuronx-cc, NCC_IBCG902). - Token embedding and the text model's vision tower stay in host memory on Neuron (2.5 GiB of HBM a rank). - offline example: --max_num_seqs. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> |
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| .. | ||
| compile | ||
| deep_ep | ||
| deep_gemm | ||
| device | ||
| flash_mla | ||
| sampling | ||
| tile_kernels | ||
| nie_skip.py | ||
| run_all.sh | ||
| setup_trn2.sh | ||