kernels: reshape_and_cache, GPU argmax, single-launch GEMV

Three new CUDA kernels and one rewrite:

- reshape_and_cache: scatter K/V into paged pool in a single kernel per
  layer, replacing the Rust-side per-token per-head cudaMemcpy loop.
  Includes both single-sequence (prefill) and batched (decode) variants.

- argmax: GPU-side BF16 argmax with warp-shuffle reduction. Greedy
  decode now only D2H-transfers B×4 bytes (token ids) instead of the
  full [B, vocab] logits tensor.

- GEMV rewrite: fused zero-init inside the K-split kernel eliminates
  the cudaMemsetAsync call, reducing launches from 3 to 2 per GEMV.

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

crates/xserv-kernels/src/lib.rs

@@ -1,4 +1,5 @@
 pub mod activation;
+pub mod argmax;
 pub mod attention;
 pub mod dispatch;
 pub mod embedding;
@@ -10,8 +11,9 @@ pub mod softmax;
 pub mod transpose;
 
 pub use activation::{add, gelu, mul, scale, silu, silu_mul};
+pub use argmax::{argmax_bf16_single, argmax_bf16_to_host};
 pub use transpose::{merge_heads_gpu, repeat_kv_gpu, reshape_heads_gpu, strided_to_contiguous_gpu, transpose_for_rope_gpu, transpose_from_rope_gpu};
-pub use attention::{attention, decode_attention, flash_attention, paged_decode_attention};
+pub use attention::{attention, decode_attention, flash_attention, paged_decode_attention, reshape_and_cache_bf16, reshape_and_cache_batched_bf16};
 pub use embedding::embedding;
 pub use gemm::{batched_matmul, matmul, GemmBackend};
 pub use layernorm::layernorm;