project_6

Author SHA1 Message Date

Author	SHA1	Message	Date
project6-dev	f32ef97013	feat(MoE): verified CUDA topk_softmax kernel — zero fallback moe_topk_softmax_v3.cu: BI-V100 verified (2026-08-10) - 64 experts, topk=8, warp shuffle, zero shared memory - renormalize: sum=1.0 ✓, no NaN ✓, no duplicate ids ✓ - 881 token batch ✓ - Compiler: corex clang/16, --cuda-gpu-arch=ivcore10 - Stream: c10::cuda::getCurrentCUDAStream() corex_moe.py: loads CUDA kernel, NO Python fallback - Searches pre-compiled .so → JIT compile from source → error - MoE pipeline: CUDA topk → cublas expert GEMM → ixformer silu_and_mul precompile_moe_topk.py: Docker build-time compilation + verification Key finding from real machine probing: ixformer::infer::topk_softmax is DECLARED in ixformer.h but NOT IMPLEMENTED in any .so in the base image (nm -D scan: zero hits). Must compile our own kernel.	2026-08-10 04:21:43 +00:00
project6-dev	1be9449883	feat(EX): corex_gdn + corex_moe — dlopen dispatch chain from comp 168 log analysis From `2d5232c5` docker log analysis: 07-23 (168's docker): corex_gdn.py + corex_moe.py → full fused kernels 08-07 (our docker): missing both → NaN GDN + PyTorch MoE fallback corex_gdn.py: GDN fused kernel dispatch - FlashQLA .so loading (gdn_forward.cu pre-compiled) - PyTorch chunked delta rule with fp32 accum + clamp (no NaN) - Decode single-step recurrent with state clamping corex_moe.py: MoE fused pipeline - topk_softmax: replaces MISSING ixf_F.vllm_moe_topk_softmax - Per-expert GEMM via torch.matmul (cublas under the hood) - ixformer.silu_and_mul for activation when available DLOPEN_DISPATCH_CHAIN.md: complete .so loading chain map deploy_corex_modules.sh: wire into VLLM/model_executor/models/	2026-08-10 03:37:15 +00:00

project6-dev

f32ef97013

feat(MoE): verified CUDA topk_softmax kernel — zero fallback

moe_topk_softmax_v3.cu: BI-V100 verified (2026-08-10)
  - 64 experts, topk=8, warp shuffle, zero shared memory
  - renormalize: sum=1.0 ✓, no NaN ✓, no duplicate ids ✓
  - 881 token batch ✓
  - Compiler: corex clang/16, --cuda-gpu-arch=ivcore10
  - Stream: c10::cuda::getCurrentCUDAStream()

corex_moe.py: loads CUDA kernel, NO Python fallback
  - Searches pre-compiled .so → JIT compile from source → error
  - MoE pipeline: CUDA topk → cublas expert GEMM → ixformer silu_and_mul

precompile_moe_topk.py: Docker build-time compilation + verification

Key finding from real machine probing:
  ixformer::infer::topk_softmax is DECLARED in ixformer.h but
  NOT IMPLEMENTED in any .so in the base image (nm -D scan: zero hits).
  Must compile our own kernel.

2026-08-10 04:21:43 +00:00

project6-dev

1be9449883

feat(EX): corex_gdn + corex_moe — dlopen dispatch chain from comp 168 log analysis

From 2d5232c5 docker log analysis:
  07-23 (168's docker): corex_gdn.py + corex_moe.py → full fused kernels
  08-07 (our docker): missing both → NaN GDN + PyTorch MoE fallback

corex_gdn.py: GDN fused kernel dispatch
  - FlashQLA .so loading (gdn_forward.cu pre-compiled)
  - PyTorch chunked delta rule with fp32 accum + clamp (no NaN)
  - Decode single-step recurrent with state clamping

corex_moe.py: MoE fused pipeline
  - topk_softmax: replaces MISSING ixf_F.vllm_moe_topk_softmax
  - Per-expert GEMM via torch.matmul (cublas under the hood)
  - ixformer.silu_and_mul for activation when available

DLOPEN_DISPATCH_CHAIN.md: complete .so loading chain map
deploy_corex_modules.sh: wire into VLLM/model_executor/models/

2026-08-10 03:37:15 +00:00

2 Commits