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Triton autotune configs for devices with warp size != 32 #1534

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Merged
tridao merged 1 commit into from
Mar 15, 2025
Merged

Triton autotune configs for devices with warp size != 32 #1534

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31 changes: 15 additions & 16 deletions flash_attn/ops/triton/layer_norm.py
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Original file line number Diff line number Diff line change
Expand Up @@ -15,6 +15,19 @@
import triton
import triton.language as tl

def triton_autotune_configs():
# Return configs with a valid warp count for the current device
configs=[]
# Maximum threads per block is architecture-dependent in theory, but in reality all are 1024
max_threads_per_block=1024
# Default to warp size 32 if not defined by device
warp_size=getattr(torch.cuda.get_device_properties(torch.cuda.current_device()), "warp_size", 32)
# Autotune for warp counts which are powers of 2 and do not exceed thread per block limit
warp_count=1
while warp_count*warp_size <= max_threads_per_block:
configs.append(triton.Config({}, num_warps=warp_count))
warp_count*=2
return configs

def layer_norm_ref(
x,
Expand Down Expand Up @@ -126,14 +139,7 @@ def rms_norm_ref(


@triton.autotune(
configs=[
triton.Config({}, num_warps=1),
triton.Config({}, num_warps=2),
triton.Config({}, num_warps=4),
triton.Config({}, num_warps=8),
triton.Config({}, num_warps=16),
triton.Config({}, num_warps=32),
],
configs=triton_autotune_configs(),
key=["N", "HAS_RESIDUAL", "STORE_RESIDUAL_OUT", "IS_RMS_NORM", "HAS_BIAS"],
)
# @triton.heuristics({"HAS_BIAS": lambda args: args["B"] is not None})
Expand Down Expand Up @@ -393,14 +399,7 @@ def _layer_norm_fwd(


@triton.autotune(
configs=[
triton.Config({}, num_warps=1),
triton.Config({}, num_warps=2),
triton.Config({}, num_warps=4),
triton.Config({}, num_warps=8),
triton.Config({}, num_warps=16),
triton.Config({}, num_warps=32),
],
configs=triton_autotune_configs(),
key=["N", "HAS_DRESIDUAL", "STORE_DRESIDUAL", "IS_RMS_NORM", "HAS_BIAS", "HAS_DROPOUT"],
)
# @triton.heuristics({"HAS_BIAS": lambda args: args["B"] is not None})
Expand Down