Skip to content

fix race condition bug in cute _flash_attn_fwd in multiple gpu env #1793

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
wants to merge 2 commits into
base: main
Choose a base branch
from
Open

fix race condition bug in cute _flash_attn_fwd in multiple gpu env #1793

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
fafc477
fix race condition bug in _flash_attn_fwd in multiple gpu env
Aug 1, 2025
ff88962
Merge branch 'main' into main
beiw-nv Aug 6, 2025
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
93 changes: 48 additions & 45 deletions flash_attn/cute/interface.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -149,55 +149,58 @@ def _flash_attn_fwd(
if not causal and not local:
n_block_size = 192

compile_key = (
dtype, head_dim, head_dim_v, qhead_per_kvhead, causal, softcap is not None,
lse is None, cu_seqlens_q is None, cu_seqlens_k is None, seqused_q is None, seqused_k is None,
window_size_left is not None, window_size_right is not None,
learnable_sink is not None,
m_block_size, n_block_size, num_threads,
compute_capability,
)
if compile_key not in _flash_attn_fwd.compile_cache:
if compute_capability == 9:
assert learnable_sink is None, "Sm90 doesn't support additive sink"
# fa_fwd = FlashAttentionForwardSm80(
fa_fwd = FlashAttentionForwardSm90(
dtype,
head_dim,
head_dim_v,
qhead_per_kvhead,
is_causal=causal,
is_local=local,
pack_gqa=False,
m_block_size=m_block_size,
n_block_size=n_block_size,
# num_stages=1,
num_stages=2,
num_threads=num_threads,
Q_in_regs=False,
)
elif compute_capability == 10:
fa_fwd = FlashAttentionForwardSm100(
head_dim,
head_dim_v,
is_causal=causal,
is_local=local,
qhead_per_kvhead=qhead_per_kvhead,
is_persistent=not causal and not local and cu_seqlens_q is None and seqused_q is None,
with torch.cuda.device(q.device.index):
compile_key = (
dtype, head_dim, head_dim_v, qhead_per_kvhead, causal, softcap is not None,
lse is None, cu_seqlens_q is None, cu_seqlens_k is None, seqused_q is None, seqused_k is None,
window_size_left is not None, window_size_right is not None,
m_block_size, n_block_size, num_threads,
compute_capability,
)

if compile_key not in _flash_attn_fwd.compile_cache:
if compute_capability == 9:
# fa_fwd = FlashAttentionForwardSm80(
fa_fwd = FlashAttentionForwardSm90(
dtype,
head_dim,
head_dim_v,
qhead_per_kvhead,
is_causal=causal,
is_local=local,
pack_gqa=False,
m_block_size=m_block_size,
n_block_size=n_block_size,
# num_stages=1,
num_stages=2,
num_threads=num_threads,
Q_in_regs=False,
)
elif compute_capability == 10:
fa_fwd = FlashAttentionForwardSm100(
head_dim,
head_dim_v,
is_causal=causal,
is_local=local,
qhead_per_kvhead=qhead_per_kvhead,
is_persistent=not causal and not local and cu_seqlens_q is None and seqused_q is None,
)
else:
raise ValueError(f"Unsupported compute capability: {compute_capability}. Supported: 9.x, 10.x")
# TODO: check @can_implement
_flash_attn_fwd.compile_cache[compile_key] = cute.compile(
fa_fwd, q_tensor, k_tensor, v_tensor, o_tensor, lse_tensor, softmax_scale, current_stream,
cu_seqlens_q_tensor, cu_seqlens_k_tensor, seqused_q_tensor, seqused_k_tensor,
softcap, window_size_left, window_size_right,

)
else:
raise ValueError(f"Unsupported compute capability: {compute_capability}. Supported: 9.x, 10.x")
# TODO: check @can_implement
_flash_attn_fwd.compile_cache[compile_key] = cute.compile(
fa_fwd, q_tensor, k_tensor, v_tensor, o_tensor, lse_tensor, softmax_scale, current_stream,

_flash_attn_fwd.compile_cache[compile_key](
q_tensor, k_tensor, v_tensor, o_tensor, lse_tensor, softmax_scale, current_stream,
cu_seqlens_q_tensor, cu_seqlens_k_tensor, seqused_q_tensor, seqused_k_tensor,
softcap, window_size_left, window_size_right, additive_sink_tensor,
)
_flash_attn_fwd.compile_cache[compile_key](
q_tensor, k_tensor, v_tensor, o_tensor, lse_tensor, softmax_scale, current_stream,
cu_seqlens_q_tensor, cu_seqlens_k_tensor, seqused_q_tensor, seqused_k_tensor,
softcap, window_size_left, window_size_right, additive_sink_tensor,
)

return out, lse


Expand Down