EX Engine
f955dd127e
feat(EX): ix_full_bridge — all 14 ixformer::infer functions bridged
...
Upstream source: xllm/core/kernels/ilu/ixformer.h (Apache 2.0)
Wrapper patterns: xllm/core/kernels/ilu/{attention,norm,rope,activation,fused_moe,group_gemm}.cpp
Complete bridge (ix_full_bridge.cpp, 331 lines):
MoE: topk_softmax, gen_idx, expand, group_gemm, silu_mul, combine, fused_forward
Attention: paged_attention (decode), flash_attn_prefill (prefill)
Norm: rms_norm, fused_add_rms_norm
RoPE: rotary_embedding
Cache: reshape_and_cache
Linear: ixformer_linear
ix_bridge.py: tries ix_full_bridge first, falls back to ix_moe_bridge
patch_ops.sh: deploys both .cpp files to all JIT search paths
Copied ixformer.h + utils.h headers for reference
2026-08-10 04:01:42 +00:00
project6-dev
5efb0fcc35
feat(EX): corex_fa2.py — third dlopen module from comp 168 AST chain
...
Log analysis from dockerrizhi.txt (07-23 Sub168 run) reveals THREE
corex modules, not two:
1. corex_gdn.py — GatedDeltaNet fused kernel (already implemented)
2. corex_moe.py — MoE routing + expert GEMM (already implemented)
3. corex_fa2.py — FlashAttention2 dispatch (NEW)
corex_fa2.py handles 32/36 attention layers with three modes:
:333 → FA2 packed prefill (B=2 Hq=4 Hkv=1 D=256 max_q=2048)
:507 → FA2 paged chunked prefill (B=1 max_q=17 cache_blocks=2)
:225 → FA2 paged decode (B=1 max_k=45455 partition=256)
Wraps ixformer.contrib.vllm_flash_attn + ixf_F.vllm_single_query_cached_kv_attention.
These .so files EXIST in the base image (libixattn.so).
Also: wired corex_fa2 import into qwen3_5.py + deploy script.
2026-08-10 04:01:21 +00:00
EX Engine
388f6b2d1a
feat(MoE): wire full ix_fused_moe_forward as Tier 0 dispatch
...
ix_bridge.py: expose all 6 ixformer::infer functions + fused_moe_forward()
qwen3_5.py: 4-tier MoE dispatch (fused C++ → CUB topk → ix topk → PyTorch)
patch_ops.sh: deploy ix_moe_bridge.cpp to 4 search paths for JIT
2026-08-10 03:38:46 +00:00
project6-dev
1be9449883
feat(EX): corex_gdn + corex_moe — dlopen dispatch chain from comp 168 log analysis
...
From 2d5232c5
2026-08-10 03:37:15 +00:00
EngineX
7839982707
feat(EX): wire xllm CUB topk_softmax kernel into MoE routing
...
Upstream: xllm/kernels/cuda/moe/moe_topk_softmax_kernels.cuh (Apache 2.0)
Adapted: CHECK→TORCH_CHECK, include path fix, cuda/functional guard, pybind11
Call chain now:
qwen3_5.py:_pure_pytorch_experts()
→ _ex_moe_topk_softmax (fused CUB kernel, 1 launch)
→ fallback: torch.softmax + torch.topk (3 launches)
Files:
ex_engine/csrc/moe/moe_topk_softmax_kernels.cuh — xllm kernel (adapted)
ex_engine/csrc/moe/device_utils.cuh — xllm device utils
ex_engine/csrc/moe/moe_topk_softmax_ext.cu — pybind11 wrapper
ex_engine/python/moe_topk.py — JIT loader (same pattern as flash_qla_sm70)
qwen3_5.py — import + use in _pure_pytorch_experts()
patch_ops.sh — deploy kernel sources for JIT
2026-08-10 03:10:58 +00:00
EX Engine
e04a3bace9
fix: fail-fast on ix_bridge failure + probe script for real machine
...
1. ix_bridge.py: RuntimeError instead of silent PyTorch fallback
If JIT compile fails, crash immediately with diagnostic message.
0 score with no error log is worse than a visible crash.
2. qwen3_5.py: explicit WARNING log on import failure (not silent)
Shows exact error so we can diagnose from docker log.
3. probe_ixformer_symbols.py: definitive test for real machine
- Finds all ixformer .so files
- nm/objdump for topk_softmax C++ symbol
- Checks Python bindings
- Attempts JIT compile + link (the real test)
- Prints PASS/FAIL with next-step instructions
Run on real machine: python3 probe_ixformer_symbols.py
2026-08-10 03:04:50 +00:00
EX Engine
d21b2505bb
fix: wire MoE topk via ixformer C++ bridge + disable broken flash_qla GDN
...
Two call chain breaks fixed:
1. MoE routing (2304 calls/token):
BEFORE: torch.softmax + torch.topk (3 Python GPU ops, no ixformer)
AFTER: ix_bridge.py → ix_moe_bridge.cpp → ixformer::infer::topk_softmax()
Source: upstream_ref/xllm/xllm/core/kernels/ilu/fused_moe.cpp line 46
The C++ API exists in base image SDK (ixformer.h declares it),
only the Python binding (ixformer.functions) was missing.
2. GDN prefill (4 layers, 99.98% NaN):
BEFORE: flash_qla SM70 kernel → abs mean=inf → nan_to_num → zeros
AFTER: skip flash_qla, use _pytorch_forward directly
Source: upstream_ref/xllm qwen3_gated_delta_net_base.cpp uses
identical PyTorch chunked logic (no flash_qla).
Sub168 (working build) never deployed flash_qla either.
Files:
- ex_engine/csrc/ix_moe_bridge.cpp: torch C++ extension calling ixformer C++ API
- ex_engine/python/ix_bridge.py: JIT-compile loader with PyTorch fallback
- qwen3_5.py: import ix_bridge for MoE, disable flash_qla for GDN
- patch_ops.sh: deploy ix_bridge .cpp + .py into vllm model dir
2026-08-10 03:00:35 +00:00
EX Engine
8e6adf20e6
refactor(EX): upstream-aligned kernels + FlashQLA GDN backend
...
Major changes based on upstream_ref analysis:
1. factor_moe_topk_softmax.cu v2.0: Rewritten using ds_vllm/TRT-LLM
warp shuffle pattern (from topk_softmax_kernels.cu). Key differences:
- Zero shared memory (all butterfly __shfl_xor_sync)
- VPT=2, THREADS_PER_ROW=32 (1 warp per token row)
- 4 warps per CTA (4 tokens per block)
- Iterative argmax with winner suppression for top-K
- NaN/Inf clamping to 0 (prevents duplicate expert IDs)
2. GDN: FlashQLA backend (PROVEN on real BI-V100):
- Compiles with corex clang/16 --cuda-gpu-arch=ivcore10
- Real test: NaN=False on gdn_forward(B=1, T=64, H=4, K=128)
- Replaces custom factor_gdn_chunk_fwd.cu (archived to .ref)
- patch_model.py now JIT-loads FlashQLA extension at runtime
3. build.sh: Correct corex flags from real compile log:
--cuda-gpu-arch=ivcore10 (NOT sm_70)
-D__ILUVATAR__ -D__ILUVATAR_WORKAROUND__ -D__ILUVATAR_DIAG__
-cl-single-precision-constant -mllvm --bonus-inst-threshold=0
Key insight from xllm/kernels/ilu/ixformer.h:
ixformer::infer::topk_softmax() EXISTS at C++ level but Python
ixformer.functions binding is missing. Our .so factor bypasses
the missing Python binding entirely via dlopen/ctypes.
2026-08-10 02:55:58 +00:00
EX Engine
b75965d4ea
fix(EX): corex ivcore10 build flags + deploy pipeline + topk kernel cleanup
...
Real machine log (2d5232c
2026-08-10 02:31:55 +00:00
EX Engine
fcfb764560
feat(EX): Algorithm Factor Replacement Engine — dlopen-based CUDA kernel dispatch
...
Factors: 0 (moe_topk_softmax), 2 (moe_fused_gemm), 5 (gdn_chunk_fwd)
Fixes: topk_softmax fallback (2304x/token), GDN NaN (frac=0.9998-1.0)
2026-08-10 02:25:23 +00:00
