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[Inductor] Naive foreach autotune support (#162053)

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Initial autotuning support for foreach kernels, 4x improvement for some kernels in internal workload. More improvements can surely be made here in the future. Removing num_warps for definition to enable autotune support in generated wrapper code.

Before:
triton_for_fused_18.kd 🔍 | 4.986 ms | 4.986 ms | 2.493 ms | 2 |
triton_for_fused_6.kd 🔍 | 0.098 ms | 0.098 ms | 0.049 ms | 2 |
triton_for_fused_7.kd 🔍 | 0.036 ms | 0.036 ms | 0.018 ms | 2 |

After:
triton_for_fused_18.kd 🔍 | 1.273 ms | 1.273 ms | 0.636 ms | 2 |
triton_for_fused_6.kd 🔍 | 0.044 ms | 0.044 ms | 0.022 ms | 2 |
triton_for_fused_7.kd 🔍 | 0.024 ms | 0.024 ms | 0.012 ms | 2 |

Pull Request resolved: https://github.com/pytorch/pytorch/pull/162053
Approved by: https://github.com/mlazos, https://github.com/naromero77amd

Co-authored-by: Nichols A. Romero <nick.romero@amd.com>
This commit is contained in:
Jack Taylor 2025-10-26 02:36:15 +00:00 committed by PyTorch MergeBot
parent 25909d2629
commit cdb60e44eb
2 changed files with 14 additions and 3 deletions
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2
torch/_inductor/codegen/triton_combo_kernel.py
View File

@ -628,7 +628,7 @@ class ComboKernel(Kernel):
if heuristics == "foreach": if heuristics == "foreach":
heuristics_line = f""" heuristics_line = f"""
@triton_heuristics.foreach( @triton_heuristics.foreach(
num_warps={self.num_warps}, filename=__file__,
triton_meta={triton_meta!r}, triton_meta={triton_meta!r},
inductor_meta={inductor_meta!r}, inductor_meta={inductor_meta!r},
) )

15
torch/_inductor/runtime/triton_heuristics.py
View File

@ -3530,13 +3530,24 @@ def user_autotune(
) )
def foreach(triton_meta, num_warps, filename=None, inductor_meta=None): def foreach(triton_meta, filename=None, inductor_meta=None):
""" """
Compile a triton foreach kernel Compile a triton foreach kernel
""" """
configs = []
# Naive autotuning path for num_warps
if not inductor_meta.get("autotune_pointwise", True) and not (
inductor_meta.get("max_autotune") or inductor_meta.get("max_autotune_pointwise")
):
configs.append(triton.Config({}, num_stages=1, num_warps=8))
else:
for warps in [1, 2, 4, 8]:
configs.append(triton.Config({}, num_stages=1, num_warps=warps))
return cached_autotune( return cached_autotune(
None, None,
[triton.Config({}, num_stages=1, num_warps=num_warps)], configs,
triton_meta=triton_meta, triton_meta=triton_meta,
inductor_meta=inductor_meta, inductor_meta=inductor_meta,
heuristic_type=HeuristicType.TEMPLATE, heuristic_type=HeuristicType.TEMPLATE,