model: fused GPU MoE kernel — eliminate CPU roundtrip

Replace the per-token CPU-routed MoE forward with an all-GPU path:

  1. moe_topk_softmax: GPU top-k + softmax (was CPU sort + softmax)
  2. moe_replicate: broadcast input to all local experts
  3. cublasGemmStridedBatchedEx: batched expert matmul (was per-expert cuBLAS)
  4. moe_weighted_sum: FP32-accumulated weighted sum on GPU (was GPU→CPU→F32→BF16→GPU)

Expert weights stored as contiguous 3D tensors for strided batched GEMM.
Zero CPU↔GPU transfers per MoE layer (was ~40 per token per layer).

Also: configurable geglu_alpha, LayerNorm bias auto-detect, unused-weight
diagnostic at load time.

GSM8K 30-problem: 11/30 → 23/30 (76.7%) vs llama.cpp 30/30 (100%).

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

crates/xserv-kernels/build.rs

@@ -29,6 +29,7 @@ fn main() {
         .file("../../csrc/attention/flash_attention.cu")
         .file("../../csrc/attention/paged_attention.cu")
         .file("../../csrc/attention/reshape_and_cache.cu")
+        .file("../../csrc/moe/moe_kernels.cu")
         .compile("xserv_kernels");
 
     println!("cargo:rerun-if-changed=../../csrc/");