cuda: deterministic BF16 gemv + paged attention reductions

BF16 greedy decode was sensitive to inter-block scheduling when logits
were close, which broke speculative-decoding verify-vs-decode parity.

- gemv.cu: write per-K-block partials, then reduce in fixed block order
  in a second kernel instead of atomicAdd across K-blocks. Scratch
  buffer size is now n * ceil(k / GEMV_TILE_K); gemv_scratch_elems()
  exposes this to callers, and decode_graph.rs sizes fp32_hidden/q/kv/
  intermediate/vocab from it.
- paged_attention.cu: replace atomicAdd merge of warp outputs with
  per-warp shared partials reduced in warp-id order for both the base
  and sinks kernels.

crates/xserv-kernels/src/gemm.rs

@@ -5,6 +5,7 @@ use xserv_cuda::error::{self, Result};
 use xserv_tensor::{DType, Device, Tensor};
 
 const CUBLAS_WORKSPACE_BYTES: usize = 32 * 1024 * 1024;
+const GEMV_TILE_K: usize = 256;
 
 // GEMV: single-kernel, no FP32 temp buffer needed
 unsafe extern "C" {
@@ -26,6 +27,10 @@ pub enum GemmBackend {
     CuBlas,
 }
 
+pub fn gemv_scratch_elems(k: usize, n: usize) -> usize {
+    n * k.div_ceil(GEMV_TILE_K)
+}
+
 // --- FFI: custom CUDA kernels ---
 unsafe extern "C" {
     fn launch_gemm_naive_f32(
@@ -274,7 +279,8 @@ pub fn matmul(a: &Tensor, b: &Tensor, backend: GemmBackend) -> Tensor {
         },
         GemmBackend::CuBlas => {
             if m == 1 && dtype == DType::BF16 && n >= 256 {
-                let mut fp32_buf = xserv_cuda::allocator::cached_alloc(n * 4).unwrap();
+                let mut fp32_buf =
+                    xserv_cuda::allocator::cached_alloc(gemv_scratch_elems(k, n) * 4).unwrap();
                 unsafe {
                     launch_gemv_bf16(
                         a_ptr,

crates/xserv-model/src/decode_graph.rs

@@ -9,7 +9,7 @@
 use std::ffi::c_void;
 use xserv_cuda::{CudaGraph, CudaStream, GpuBuffer};
 use xserv_kernels::dispatch;
-use xserv_kernels::gemm::cublas_handle;
+use xserv_kernels::gemm::{cublas_handle, gemv_scratch_elems};
 
 use crate::config::ModelConfig;
 use crate::kv_cache::GpuKVCache;
@@ -54,7 +54,7 @@ struct DecodeBuffers {
     up: GpuBuffer,       // [1, intermediate]
     silu_out: GpuBuffer, // [1, intermediate]
 
-    // GEMV fp32 accumulators (separate per output dimension)
+    // GEMV fp32 scratch for deterministic K-block partials.
     fp32_hidden: GpuBuffer,       // for hidden-sized GEMV outputs
     fp32_q: GpuBuffer,            // for Q projection
     fp32_kv: GpuBuffer,           // for K/V projection
@@ -140,11 +140,14 @@ impl DecodeGraphState {
             up: alloc(intermediate * es),
             silu_out: alloc(intermediate * es),
 
-            fp32_hidden: alloc(hidden * 4),
-            fp32_q: alloc(num_heads * head_dim * 4),
-            fp32_kv: alloc(num_kv_heads * head_dim * 4),
-            fp32_intermediate: alloc(intermediate * 4),
-            fp32_vocab: alloc(vocab_size * 4),
+            fp32_hidden: alloc(
+                gemv_scratch_elems(hidden, hidden).max(gemv_scratch_elems(intermediate, hidden))
+                    * 4,
+            ),
+            fp32_q: alloc(gemv_scratch_elems(hidden, num_heads * head_dim) * 4),
+            fp32_kv: alloc(gemv_scratch_elems(hidden, num_kv_heads * head_dim) * 4),
+            fp32_intermediate: alloc(gemv_scratch_elems(hidden, intermediate) * 4),
+            fp32_vocab: alloc(gemv_scratch_elems(hidden, vocab_size) * 4),
 
             token_id_gpu: alloc(4),
             position_gpu: alloc(4),