feat(moe): FlyDSL MegaMoE fused EP-MoE integration (mega_moe_v1 @8acf…

[JiaoliangYu]

ATOM_USE_FLYDSL_FUSED=1 replaces the EP experts step (dispatch+gemm1+quant+ gemm2+combine) with FlyDSL MegaMoE. Adapted from PR yanbo/mega to the current mega_moe_v1 tip (post kernels refactor #807):

• fp4_utils module removed -> import gemm_common_utils (e8m0_shuffle/ shuffle_scale_w4 live there now)
• w1/w1_scale use shuffle_weight_w4/shuffle_scale_w4(gate_up=True, moe_gemm= True) to match the a8w4 INTERLEAVE(g1u1) gate_mode default; the generic shuffle_weight is the SEPARATED layout and mispairs gate/up in swiglu (gsm8k ~0.017)
• stash layer._mega_local_E at build; do NOT infer expert count from the shuffled _mega_w1 shape (shuffle_weight_w4 + view(-1) breaks the old shape[0]//(2*inter) inference -> experts blows up -> ~76GB mori buffer -> shmem_malloc failed)
• per-layer weight swap targets mega._s1_w1/_s1_w1_scale (fused stage-1 runtime pointers); forward_bf16 is aliased to forward
• build MegaMoE and run forward under inference_mode(False)+no_grad so its persistent mori buffers are normal tensors (cudagraph capture does in-place .zero_() outside inference mode)
• empty_cache after weight build; warmup/dummy token scatter

Validated on DeepSeek-V4-Pro a8w4, 8x MI355X (gfx950), fused ON / EPLB OFF: gsm8k 3-shot flexible=strict=0.9424 (on par with mori/EPLB baseline ~0.95).

Runtime env: ATOM_USE_FLYDSL=1 ATOM_USE_FLYDSL_FUSED=1 ATOM_FLYDSL_KERNELS_PATH=; launch with --max-num-batched-tokens 8192 (keeps mtpr<=8192; larger overflows a stage2 int32 kernel arg).

Motivation

Technical Details

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