d1c5e992aa08f5779b7252d255da93aedf52788c
THE CORE .so: ix_moe_bridge.cpp compiles to ix_moe_bridge.so which:
- Links against base image's libixformer.so at load time
- Exposes 12 functions to Python via pybind11:
MoE pipeline (7 steps):
topk_softmax() → ixformer::infer::topk_softmax
moe_gen_idx() → ixformer::infer::moe_compute_token_index_api
moe_expand_input() → ixformer::infer::moe_expand_input
moe_group_gemm() → ixformer::infer::moe_w16a16_group_gemm
silu_and_mul() → ixformer::infer::silu_and_mul
moe_combine_result()→ ixformer::infer::moe_output_reduce_sum
Inference ops (5 functions):
paged_attention() → ixformer::infer::xllm_paged_attention
rms_norm() → ixformer::infer::rms_norm
linear() → ixformer::infer::ixformer_linear
reshape_and_cache() → ixformer::infer::xllm_reshape_and_cache
rotary_embedding() → ixformer::infer::xllm_rotary_embedding
Build chain:
Dockerfile → build.sh → precompile_ix_bridge.py
→ torch.utils.cpp_extension.load(ix_moe_bridge.cpp, -lixformer)
→ ix_moe_bridge.cpython-310.so
Load chain:
Python: from ex_engine.python.ix_bridge import topk_softmax
→ ix_bridge.py loads ix_moe_bridge.so
→ dlopen links to libixformer.so
→ CUDA kernel on BI-V100
Interface source: upstream_ref/xllm_latest/core/kernels/ilu/ixformer.h
project_6
Description
Languages
C++
41.8%
Cuda
31.6%
Python
22.2%
C
2.1%
CMake
1.1%
Other
1.1%