cuda: infrastructure for whole-step CUDA graph capture

- Thread-local launch stream (xserv_cuda::stream): every kernel
  wrapper, cublasSetStream, and NCCL collective now launches on
  current_stream_raw() — the legacy null stream by default (behavior
  unchanged), or the capture stream installed via push_stream during
  graph capture. Capture is impossible on the legacy stream.
- Allocator retain mode: blocks freed inside a retain window are
  quarantined (RetainedBlocks) instead of pooled, so an instantiated
  graph keeps exclusive ownership of every intermediate buffer it
  references across replays.
- Capture mode GLOBAL -> THREAD_LOCAL: concurrent TP rank threads
  must not poison each other's captures with their own cudaMallocs.
- embedding_device_ids / rope_inplace_device_pos: variants reading
  token ids / positions from persistent device buffers, replacing the
  per-call host upload that a captured region cannot contain.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

crates/xserv-kernels/src/gemm.rs

@@ -151,7 +151,7 @@ pub fn matmul(a: &Tensor, b: &Tensor, backend: GemmBackend) -> Tensor {
     let a_ptr = a.data_ptr() as *const c_void;
     let b_ptr = b.data_ptr() as *const c_void;
     let c_ptr = c.data_ptr() as *mut c_void;
-    let null_stream = std::ptr::null_mut();
+    let null_stream = xserv_cuda::current_stream_raw();
 
     match backend {
         GemmBackend::Naive => {
@@ -260,7 +260,7 @@ pub fn batched_matmul(a: &Tensor, b: &Tensor) -> Tensor {
     let stride_c = (m * n) as i64;
 
     with_cublas(|handle| unsafe {
-        cublasSetStream_v2(handle, std::ptr::null_mut());
+        cublasSetStream_v2(handle, xserv_cuda::current_stream_raw());
         // Row-major trick: C = A @ B ⟺ C^T = B^T @ A^T (col-major)
         error::check(cublasGemmStridedBatchedEx(
             handle,