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triton sdpa kernel perf test #17584

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48 changes: 20 additions & 28 deletions backends/cuda/triton/kernels/sdpa.py
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Original file line number Diff line number Diff line change
Expand Up @@ -158,8 +158,6 @@ def _sdpa_fwd_kernel_non_pow2(
if HAS_MASK:
mask_b_base = mask_ptr + b * stride_mb

NEG_INF: tl.constexpr = float("-inf")

for start_n in tl.range(0, LK, BLOCK_N, num_stages=2):
kn = start_n + offs_n
kv_col_mask = kn < LK
Expand All @@ -168,39 +166,37 @@ def _sdpa_fwd_kernel_non_pow2(
k = tl.load(k_ptrs, mask=kv_col_mask[:, None] & d_mask[None, :], other=0.0)

qk = tl.dot(q, tl.trans(k))
qk = (qk * qk_scale_log2).to(tl.float32)
qk = qk * qk_scale_log2

if IS_CAUSAL:
row_abs = offs_m[:, None]
col_abs = kn[None, :]
causal_mask = col_abs > row_abs
qk = tl.where(causal_mask, tl.full(qk.shape, NEG_INF, dtype=tl.float32), qk)
qk = tl.where(causal_mask, -float("inf"), qk)

if HAS_MASK:
mask_ptrs = (
mask_b_base + offs_m[:, None] * stride_mlq + kn[None, :] * stride_mlk
)
tile_valid = q_row_mask[:, None] & kv_col_mask[None, :]
keep = tl.load(mask_ptrs, mask=tile_valid, other=True)
qk = tl.where(keep, qk, tl.full(qk.shape, NEG_INF, dtype=tl.float32))
qk = tl.where(keep, qk, -float("inf"))

qk = tl.where(
kv_col_mask[None, :], qk, tl.full(qk.shape, NEG_INF, dtype=tl.float32)
)
qk = tl.where(kv_col_mask[None, :], qk, -float("inf"))

m_ij = tl.maximum(m_i, tl.max(qk, 1).to(tl.float32))
p = tl.math.exp2(qk - m_ij[:, None]).to(tl.float32)
l_ij = tl.sum(p, 1).to(tl.float32)
alpha = tl.math.exp2(m_i - m_ij).to(tl.float32)
m_ij = tl.maximum(m_i, tl.max(qk, 1))
p = tl.math.exp2(qk - m_ij[:, None])
l_ij = tl.sum(p, 1)
alpha = tl.math.exp2(m_i - m_ij)

acc = (acc * alpha[:, None]).to(tl.float32)
acc = acc * alpha[:, None]

v_ptrs = v_base + (kn[:, None] * stride_vl + offs_d[None, :] * stride_vd)
v = tl.load(v_ptrs, mask=kv_col_mask[:, None] & d_mask[None, :], other=0.0)

acc = tl.dot(p.to(v.dtype), v, acc).to(tl.float32)
acc = tl.dot(p.to(v.dtype), v, acc)

l_i = (l_i * alpha + l_ij).to(tl.float32)
l_i = l_i * alpha + l_ij
m_i = m_ij

out = acc / l_i[:, None]
Expand Down Expand Up @@ -285,7 +281,7 @@ def _sdpa_fwd_kernel_body(
k_mask = (offs_n[:, None] < Lk) & (offs_d[None, :] < HEAD_DIM)
k = tl.load(k_ptrs, mask=k_mask, other=0.0).to(tl.bfloat16)

qk = (tl.dot(q, tl.trans(k)).to(tl.float32) * sm_scale).to(tl.float32)
qk = tl.dot(q, tl.trans(k)).to(tl.float32) * sm_scale

if HAS_MASK:
mask_ptrs = Mask_ptr + (
Expand All @@ -295,22 +291,18 @@ def _sdpa_fwd_kernel_body(
)
mn_mask = (offs_m[:, None] < Lq) & (offs_n[None, :] < Lk)
mask_block = tl.load(mask_ptrs, mask=mn_mask, other=False)
qk = tl.where(
mask_block, qk, tl.full(qk.shape, -float("inf"), dtype=tl.float32)
)
qk = tl.where(mask_block, qk, -float("inf"))

if IS_CAUSAL:
abs_m = offs_m[:, None]
abs_n = offs_n[None, :]
causal = abs_n > abs_m
qk = tl.where(
causal, tl.full(qk.shape, -float("inf"), dtype=tl.float32), qk
)
qk = tl.where(causal, -float("inf"), qk)

m_ij = tl.maximum(m_i, tl.max(qk, axis=1).to(tl.float32))
p_f32 = tl.exp(qk - m_ij[:, None]).to(tl.float32)
l_ij = tl.sum(p_f32, axis=1).to(tl.float32)
alpha = tl.exp(m_i - m_ij).to(tl.float32)
m_ij = tl.maximum(m_i, tl.max(qk, axis=1))
p_f32 = tl.exp(qk - m_ij[:, None])
l_ij = tl.sum(p_f32, axis=1)
alpha = tl.exp(m_i - m_ij)

v_ptrs = V_ptr + (
b * stride_vb
Expand All @@ -322,8 +314,8 @@ def _sdpa_fwd_kernel_body(
v = tl.load(v_ptrs, mask=v_mask, other=0.0).to(tl.bfloat16)

p_bf16 = p_f32.to(tl.bfloat16)
acc = (acc * alpha[:, None] + tl.dot(p_bf16, v)).to(tl.float32)
l_i = (l_i * alpha + l_ij).to(tl.float32)
acc = acc * alpha[:, None] + tl.dot(p_bf16, v)
l_i = l_i * alpha + l_ij
m_i = m_ij

inv_l_i = tl.where(l_i > 0, 1.0 / l_i, 0.0)
Expand Down
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