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fix(critical): use cuMemAlloc for cublasLt workspace (cross-stream access)

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cudarc's stream.alloc_zeros uses cuMemAllocAsync (stream-ordered).
These allocations are only accessible from the allocating stream.
When cublasLtMatmul runs on a forked BRANCH stream (multi-stream
branch dispatch), the stream-ordered workspace is inaccessible,
causing CUBLAS_STATUS_NOT_SUPPORTED on H100 at batch=4096.

Fix: allocate workspace via cuMemAlloc_v2 (synchronous, globally
accessible from all streams). This matches the C++ debug test
which uses cudaMalloc and works on H100 for all dimensions.

Also: add d_layout destroy (leaked handle cleanup).

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
jgrusewski
2026-04-10 13:14:00 +02:00
parent 90826adad3
commit 06f9819f05
1 changed files with 20 additions and 7 deletions
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27
crates/ml/src/cuda_pipeline/batched_forward.rs
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@@ -237,13 +237,26 @@ impl CublasForward {
let lt_raw_handle = cublaslt_result::create_handle()
.map_err(|e| MLError::ModelError(format!("cublasLtCreate: {e:?}")))?;
// 32 MB unconditionally — TF32 HMMA algorithms need large workspace
// even on Ampere (SM86). NVIDIA recommends 32 MB for Hopper but
// the TF32 heuristic returns NOT_SUPPORTED with 4 MB at (128,512,64).
// 32 MB workspace for cublasLtMatmul.
// CRITICAL: use cudaMalloc (not cuMemAllocAsync) so the workspace is
// accessible from ALL streams including forked branch streams. Stream-ordered
// allocations are only valid on the allocating stream, causing
// CUBLAS_STATUS_NOT_SUPPORTED when cublasLtMatmul runs on branch streams.
let lt_ws_size: usize = 32 * 1024 * 1024;
let lt_ws_buf = stream.alloc_zeros::<u8>(lt_ws_size)
.map_err(|e| MLError::ModelError(format!("cublasLt workspace alloc: {e}")))?;
let lt_ws_ptr = lt_ws_buf.raw_ptr();
let lt_ws_ptr: u64;
unsafe {
let mut dev_ptr: cudarc::driver::sys::CUdeviceptr = 0;
let result = cudarc::driver::sys::cuMemAlloc_v2(&mut dev_ptr, lt_ws_size);
if result != cudarc::driver::sys::CUresult::CUDA_SUCCESS {
return Err(MLError::ModelError(format!("cuMemAlloc workspace: {result:?}")));
}
// Zero the workspace
cudarc::driver::sys::cuMemsetD8_v2(dev_ptr, 0, lt_ws_size);
lt_ws_ptr = dev_ptr;
}
// Dummy CudaSlice to satisfy struct field (workspace is managed by cuMemAlloc)
let lt_workspace_buf = stream.alloc_zeros::<u8>(1)
.map_err(|e| MLError::ModelError(format!("dummy ws alloc: {e}")))?;
// ── Load f32 bias kernels from precompiled cubin ──
let (add_bias_relu_f32_kernel, add_bias_f32_kernel) =
@@ -274,7 +287,7 @@ impl CublasForward {
workspace_ptr,
workspace_size,
lt_handle: SendSyncCublasLtHandle(lt_raw_handle),
_lt_workspace_buf: lt_ws_buf,
_lt_workspace_buf: lt_workspace_buf,
lt_workspace_ptr: lt_ws_ptr,
lt_workspace_size: lt_ws_size,
add_bias_relu_f32_kernel,