Skip to content

[Bugfix][ROCm] Stage pageable H2D copies in async_copy_to_gpu through pinned memory #1403

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
hadihonarvar wants to merge 1 commit into
base: release/0.23.0
Choose a base branch
from
Open

[Bugfix][ROCm] Stage pageable H2D copies in async_copy_to_gpu through pinned memory #1403

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
10 changes: 6 additions & 4 deletions vllm/v1/worker/gpu/buffer_utils.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -7,7 +7,7 @@
import torch

from vllm.triton_utils import tl, triton
from vllm.utils.platform_utils import is_uva_available
from vllm.utils.platform_utils import is_pin_memory_available, is_uva_available
from vllm.utils.torch_utils import (
async_tensor_h2d,
get_accelerator_view_from_cpu_tensor,
Expand Down Expand Up @@ -36,9 +36,11 @@ def async_copy_to_gpu(
assert device is not None
out = torch.empty_like(x, device=device)

# Copy directly to GPU — explicit pin_memory() causes sporadic stalls
# under high concurrency due to CUDA driver contention. The driver
# handles the transfer efficiently without manual pinning.
if not x.is_pinned() and is_pin_memory_available():
# A non_blocking copy from pageable memory is not reliable on ROCm:
# stage it through the caching host allocator, as async_tensor_h2d
# does on main.
x = torch.empty(x.shape, dtype=x.dtype, device="cpu", pin_memory=True).copy_(x)
return out.copy_(x, non_blocking=True)


Expand Down
Loading