32ee28122e
来源: Deep-Spark/xllm core/kernels/ilu/ + core/layers/ilu/
ixformer.h: 14个ixformer::infer API完整声明
kernel wrappers: activation(32) attention(162) fused_moe(99) group_gemm(39)
matmul(73) norm(50) rope(31) + headers
layer dispatch: fused_moe.cpp(797行) attention.cpp(189行) + headers
覆盖状态 (ix_moe_bridge.cpp vs ixformer.h 14个API):
已覆盖 13/14: silu_and_mul, rms_norm, residual_rms_norm, ixformer_linear,
ixformer_linear_ex, topk_softmax, moe_compute_token_index, moe_expand_input,
moe_w16a16_group_gemm, moe_output_reduce_sum, xllm_paged_attention,
xllm_reshape_and_cache, xllm_rotary_embedding
缺失 1/14: ixinfer_flash_attn_unpad_with_block_tables
dlopen 调用链验证:
12个 prebuilt .so → 9个 qwen3_5.py + 2个 paged_attn.py + 1个 block_major_kv_cache.py
辅助模块: bi100_env, bi100_profile, gdn_prefix, block_major_kv_cache 全部到位
Upstream Reference: Deep-Spark xllm + vllm (FULL TREE)
Source repos (cloned 2026-08-09, Apache 2.0):
Deep-Spark/xllm— Iluvatar official C++ LLM inference engine (1470 files)Deep-Spark/vllm— Iluvatar official vllm fork (703 files, csrc + model layer)
What's here
xllm/ (complete source minus git/binaries/submodules)
天数智芯官方下一代推理引擎，C++ 原生，多平台(CUDA/ILU/MLU/NPU)。 包含 kernels → layers → models → runtime → scheduler → api_service 完整栈。
Key subtrees:
xllm/core/kernels/ilu/— ixformer API wrappers (ixformer.h是金矿)xllm/core/kernels/cuda/moe/— MoE CUDA kernels (topk_softmax, fused_topk)xllm/core/kernels/cuda/— activation, norm, rope, attention CUDA kernelsxllm/core/layers/ilu/— Iluvatar FusedMoE完整pipelinexllm/core/layers/npu_torch/— GatedDeltaNet C++ implementationxllm/models/llm/qwen3_5.h— Qwen3.5 model definitionxllm/compiler/tilelang/— GDN kernel code generation
ds_vllm/ (csrc + model layers + fused_moe)
天数智芯官方vllm fork，Python + CUDA torch extension。
csrc/— ALL CUDA source (attention, moe, quantization, cache)csrc/libtorch_stable/moe/topk_softmax_kernels.cu— vllm topk_softmaxvllm/_custom_ops.py— Python → torch.ops._moe_C bridgevllm/model_executor/models/qwen3_5.py— ds_vllm的qwen3_5实现vllm/model_executor/layers/fused_moe/— vllm FusedMoE Python layer