865c18f8528eafe69fca1bcd91f54a62e5a14414
xllm_moe.so provides 3 fused CUDA kernels compiled for ivcore10: - moe_fused_topk: CUB topk + softmax (replaces corex_moe_topk_softmax) - moe_compute_index: histogram + prefix_sum + place (replaces corex_moe_index_combine) - moe_combine_result: reorder + weighted sum (available but not yet wired to output) Dispatch priority in _pure_pytorch_experts(): Tier 0: xllm_moe (if available) Tier 1: corex_moe_* individual .so Tier 2: PyTorch fallback Integration points: 1. Topk routing: xllm_moe.moe_fused_topk → corex_moe_topk_softmax → torch.topk 2. Index computation: xllm_moe.moe_compute_index → corex_moe_index_combine → torch.argsort 3. Expert loop: still Python F.linear (next target: batch GEMM) patch_ops.sh already deploys all prebuilt/*.so including xllm_moe.so
project_6
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