[ExecuTorch][WebGPU] Fuse the SwiGLU elementwise chain - #21129

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[ExecuTorch][WebGPU] Fuse the SwiGLU elementwise chain#21129
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Stack from ghstack (oldest at bottom):

The SwiGLU feed-forward activation lowered to separate gate and up projections
followed by a sigmoid and two elementwise multiplies, launching several
dispatches over the same tensors. This fuses the sigmoid and the two multiplies
into a single dynamically-resized 2D dispatch that computes
(gate * sigmoid(gate)) * up in one pass. Fusion applies only when the pattern
is exact and its scratch is planner-owned; graph outputs, extra consumers, and
separate inputs fall back to the unfused chain, and the landed broad-QKV
behavior is left untouched until its dedicated corrective diff. No Vulkan
analogue: the Vulkan backend has no fused SiLU/SwiGLU shader and composes it
from a sigmoid unary op plus an elementwise multiply at graph level.

Key changes:

  • runtime/ops/mul/silu_mul_fused.wgsl (+ generated header): one-thread-per-
    element SiLU-gated multiply of gate and up into a single output.
  • WebGPUGraph.cpp: detect the exact gate/up/sigmoid/mul pattern, own the gate
    scratch, size the 2D dispatch, and fall back conservatively.
    @exported-using-ghexport

Differential Revision: D113171742

Differential Revision: D113171742

@JCNTH
Update
5928269
[ghstack-poisoned]
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🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/21129

Note: Links to docs will display an error until the docs builds have been completed.

❌ 37 New Failures, 22 Pending

As of commit 38d5fa0 with merge base 28a7fac (image):

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[ExecuTorch][WebGPU] Fuse the SwiGLU elementwise chain
b398254
Pull Request resolved: #21129
The SwiGLU feed-forward activation lowered to separate gate and up projections
followed by a sigmoid and two elementwise multiplies, launching several
dispatches over the same tensors. This fuses the sigmoid and the two multiplies
into a single dynamically-resized 2D dispatch that computes
(gate * sigmoid(gate)) * up in one pass. Fusion applies only when the pattern
is exact and its scratch is planner-owned; graph outputs, extra consumers, and
separate inputs fall back to the unfused chain, and the landed broad-QKV
behavior is left untouched until its dedicated corrective diff. No Vulkan
analogue: the Vulkan backend has no fused SiLU/SwiGLU shader and composes it
from a sigmoid unary op plus an elementwise multiply at graph level.
Key changes:
- runtime/ops/mul/silu_mul_fused.wgsl (+ generated header): one-thread-per-
element SiLU-gated multiply of gate and up into a single output.
- WebGPUGraph.cpp: detect the exact gate/up/sigmoid/mul pattern, own the gate
scratch, size the 2D dispatch, and fall back conservatively.
ghstack-source-id: 411961441
@exported-using-ghexport
Differential Revision: [D113171742](https://our.internmc.facebook.com/intern/diff/D113171742/)
JCNTH added a commit that referenced this pull request Aug 7, 2026
@JCNTH
[ExecuTorch][WebGPU] Fuse the SwiGLU elementwise chain
965c3c5
Pull Request resolved: #21129
The SwiGLU feed-forward activation lowered to separate gate and up projections
followed by a sigmoid and two elementwise multiplies, launching several
dispatches over the same tensors. This fuses the sigmoid and the two multiplies
into a single dynamically-resized 2D dispatch that computes
(gate * sigmoid(gate)) * up in one pass. Fusion applies only when the pattern
is exact and its scratch is planner-owned; graph outputs, extra consumers, and
separate inputs fall back to the unfused chain, and the landed broad-QKV
behavior is left untouched until its dedicated corrective diff. No Vulkan
analogue: the Vulkan backend has no fused SiLU/SwiGLU shader and composes it
from a sigmoid unary op plus an elementwise multiply at graph level.
Key changes:
- runtime/ops/mul/silu_mul_fused.wgsl (+ generated header): one-thread-per-
element SiLU-gated multiply of gate and up into a single output.
- WebGPUGraph.cpp: detect the exact gate/up/sigmoid/mul pattern, own the gate
scratch, size the 2D dispatch, and fall back conservatively.
ghstack-source-id: 411961441
@exported-using-ghexport
Differential Revision: [D113171742](https://our.internmc.facebook.com/intern/diff/D113171742/)
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[ExecuTorch][WebGPU] Fuse the SwiGLU elementwise chain - #21129

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Stack from ghstack (oldest at bottom):

The SwiGLU feed-forward activation lowered to separate gate and up projections
followed by a sigmoid and two elementwise multiplies, launching several
dispatches over the same tensors. This fuses the sigmoid and the two multiplies
into a single dynamically-resized 2D dispatch that computes
(gate * sigmoid(gate)) * up in one pass. Fusion applies only when the pattern
is exact and its scratch is planner-owned; graph outputs, extra consumers, and
separate inputs fall back to the unfused chain, and the landed broad-QKV
behavior is left untouched until its dedicated corrective diff. No Vulkan
analogue: the Vulkan backend has no fused SiLU/SwiGLU shader and composes it
from a sigmoid unary op plus an elementwise multiply at graph level.

Key changes:

  • runtime/ops/mul/silu_mul_fused.wgsl (+ generated header): one-thread-per-
    element SiLU-gated multiply of gate and up into a single output.
  • WebGPUGraph.cpp: detect the exact gate/up/sigmoid/mul pattern, own the gate
    scratch, size the 2D dispatch, and fall back conservatively.
    @exported-using-ghexport

Differential Revision: D113171742

Differential Revision: D113171742

@JCNTH
Update
5928269
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🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/21129

Note: Links to docs will display an error until the docs builds have been completed.

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[ExecuTorch][WebGPU] Fuse the SwiGLU elementwise chain
b398254
Pull Request resolved: #21129
The SwiGLU feed-forward activation lowered to separate gate and up projections
followed by a sigmoid and two elementwise multiplies, launching several
dispatches over the same tensors. This fuses the sigmoid and the two multiplies
into a single dynamically-resized 2D dispatch that computes
(gate * sigmoid(gate)) * up in one pass. Fusion applies only when the pattern
is exact and its scratch is planner-owned; graph outputs, extra consumers, and
separate inputs fall back to the unfused chain, and the landed broad-QKV
behavior is left untouched until its dedicated corrective diff. No Vulkan
analogue: the Vulkan backend has no fused SiLU/SwiGLU shader and composes it
from a sigmoid unary op plus an elementwise multiply at graph level.
Key changes:
- runtime/ops/mul/silu_mul_fused.wgsl (+ generated header): one-thread-per-
element SiLU-gated multiply of gate and up into a single output.
- WebGPUGraph.cpp: detect the exact gate/up/sigmoid/mul pattern, own the gate
scratch, size the 2D dispatch, and fall back conservatively.
ghstack-source-id: 411961441
@exported-using-ghexport
Differential Revision: [D113171742](https://our.internmc.facebook.com/intern/diff/D113171742/)
JCNTH added a commit that referenced this pull request Aug 7, 2026
@JCNTH
[ExecuTorch][WebGPU] Fuse the SwiGLU elementwise chain
965c3c5
Pull Request resolved: #21129
The SwiGLU feed-forward activation lowered to separate gate and up projections
followed by a sigmoid and two elementwise multiplies, launching several
dispatches over the same tensors. This fuses the sigmoid and the two multiplies
into a single dynamically-resized 2D dispatch that computes
(gate * sigmoid(gate)) * up in one pass. Fusion applies only when the pattern
is exact and its scratch is planner-owned; graph outputs, extra consumers, and
separate inputs fall back to the unfused chain, and the landed broad-QKV
behavior is left untouched until its dedicated corrective diff. No Vulkan
analogue: the Vulkan backend has no fused SiLU/SwiGLU shader and composes it
from a sigmoid unary op plus an elementwise multiply at graph level.
Key changes:
- runtime/ops/mul/silu_mul_fused.wgsl (+ generated header): one-thread-per-
element SiLU-gated multiply of gate and up into a single output.
- WebGPUGraph.cpp: detect the exact gate/up/sigmoid/mul pattern, own the gate
scratch, size the 2D dispatch, and fall back conservatively.
ghstack-source-id: 411961441
@exported-using-ghexport
Differential Revision: [D113171742](https://our.internmc.facebook.com/intern/diff/D113171742/)
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[ExecuTorch][WebGPU] Fuse the SwiGLU elementwise chain - #21129

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Stack from ghstack (oldest at bottom):

The SwiGLU feed-forward activation lowered to separate gate and up projections
followed by a sigmoid and two elementwise multiplies, launching several
dispatches over the same tensors. This fuses the sigmoid and the two multiplies
into a single dynamically-resized 2D dispatch that computes
(gate * sigmoid(gate)) * up in one pass. Fusion applies only when the pattern
is exact and its scratch is planner-owned; graph outputs, extra consumers, and
separate inputs fall back to the unfused chain, and the landed broad-QKV
behavior is left untouched until its dedicated corrective diff. No Vulkan
analogue: the Vulkan backend has no fused SiLU/SwiGLU shader and composes it
from a sigmoid unary op plus an elementwise multiply at graph level.

Key changes:

  • runtime/ops/mul/silu_mul_fused.wgsl (+ generated header): one-thread-per-
    element SiLU-gated multiply of gate and up into a single output.
  • WebGPUGraph.cpp: detect the exact gate/up/sigmoid/mul pattern, own the gate
    scratch, size the 2D dispatch, and fall back conservatively.
    @exported-using-ghexport

Differential Revision: D113171742

Differential Revision: D113171742

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🔗 Helpful Links

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[ExecuTorch][WebGPU] Fuse the SwiGLU elementwise chain
b398254
Pull Request resolved: #21129
The SwiGLU feed-forward activation lowered to separate gate and up projections
followed by a sigmoid and two elementwise multiplies, launching several
dispatches over the same tensors. This fuses the sigmoid and the two multiplies
into a single dynamically-resized 2D dispatch that computes
(gate * sigmoid(gate)) * up in one pass. Fusion applies only when the pattern
is exact and its scratch is planner-owned; graph outputs, extra consumers, and
separate inputs fall back to the unfused chain, and the landed broad-QKV
behavior is left untouched until its dedicated corrective diff. No Vulkan
analogue: the Vulkan backend has no fused SiLU/SwiGLU shader and composes it
from a sigmoid unary op plus an elementwise multiply at graph level.
Key changes:
- runtime/ops/mul/silu_mul_fused.wgsl (+ generated header): one-thread-per-
element SiLU-gated multiply of gate and up into a single output.
- WebGPUGraph.cpp: detect the exact gate/up/sigmoid/mul pattern, own the gate
scratch, size the 2D dispatch, and fall back conservatively.
ghstack-source-id: 411961441
@exported-using-ghexport
Differential Revision: [D113171742](https://our.internmc.facebook.com/intern/diff/D113171742/)
JCNTH added a commit that referenced this pull request Aug 7, 2026
@JCNTH
[ExecuTorch][WebGPU] Fuse the SwiGLU elementwise chain
965c3c5
Pull Request resolved: #21129
The SwiGLU feed-forward activation lowered to separate gate and up projections
followed by a sigmoid and two elementwise multiplies, launching several
dispatches over the same tensors. This fuses the sigmoid and the two multiplies
into a single dynamically-resized 2D dispatch that computes
(gate * sigmoid(gate)) * up in one pass. Fusion applies only when the pattern
is exact and its scratch is planner-owned; graph outputs, extra consumers, and
separate inputs fall back to the unfused chain, and the landed broad-QKV
behavior is left untouched until its dedicated corrective diff. No Vulkan
analogue: the Vulkan backend has no fused SiLU/SwiGLU shader and composes it
from a sigmoid unary op plus an elementwise multiply at graph level.
Key changes:
- runtime/ops/mul/silu_mul_fused.wgsl (+ generated header): one-thread-per-
element SiLU-gated multiply of gate and up into a single output.
- WebGPUGraph.cpp: detect the exact gate/up/sigmoid/mul pattern, own the gate
scratch, size the 2D dispatch, and fall back conservatively.
ghstack-source-id: 411961441
@exported-using-ghexport
Differential Revision: [D113171742](https://our.internmc.facebook.com/intern/diff/D113171742/)
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[ExecuTorch][WebGPU] Fuse the SwiGLU elementwise chain - #21129

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Stack from ghstack (oldest at bottom):

The SwiGLU feed-forward activation lowered to separate gate and up projections
followed by a sigmoid and two elementwise multiplies, launching several
dispatches over the same tensors. This fuses the sigmoid and the two multiplies
into a single dynamically-resized 2D dispatch that computes
(gate * sigmoid(gate)) * up in one pass. Fusion applies only when the pattern
is exact and its scratch is planner-owned; graph outputs, extra consumers, and
separate inputs fall back to the unfused chain, and the landed broad-QKV
behavior is left untouched until its dedicated corrective diff. No Vulkan
analogue: the Vulkan backend has no fused SiLU/SwiGLU shader and composes it
from a sigmoid unary op plus an elementwise multiply at graph level.

Key changes:

  • runtime/ops/mul/silu_mul_fused.wgsl (+ generated header): one-thread-per-
    element SiLU-gated multiply of gate and up into a single output.
  • WebGPUGraph.cpp: detect the exact gate/up/sigmoid/mul pattern, own the gate
    scratch, size the 2D dispatch, and fall back conservatively.
    @exported-using-ghexport

Differential Revision: D113171742

Differential Revision: D113171742

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🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/21129

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[ExecuTorch][WebGPU] Fuse the SwiGLU elementwise chain
b398254
Pull Request resolved: #21129
The SwiGLU feed-forward activation lowered to separate gate and up projections
followed by a sigmoid and two elementwise multiplies, launching several
dispatches over the same tensors. This fuses the sigmoid and the two multiplies
into a single dynamically-resized 2D dispatch that computes
(gate * sigmoid(gate)) * up in one pass. Fusion applies only when the pattern
is exact and its scratch is planner-owned; graph outputs, extra consumers, and
separate inputs fall back to the unfused chain, and the landed broad-QKV
behavior is left untouched until its dedicated corrective diff. No Vulkan
analogue: the Vulkan backend has no fused SiLU/SwiGLU shader and composes it
from a sigmoid unary op plus an elementwise multiply at graph level.
Key changes:
- runtime/ops/mul/silu_mul_fused.wgsl (+ generated header): one-thread-per-
element SiLU-gated multiply of gate and up into a single output.
- WebGPUGraph.cpp: detect the exact gate/up/sigmoid/mul pattern, own the gate
scratch, size the 2D dispatch, and fall back conservatively.
ghstack-source-id: 411961441
@exported-using-ghexport
Differential Revision: [D113171742](https://our.internmc.facebook.com/intern/diff/D113171742/)
JCNTH added a commit that referenced this pull request Aug 7, 2026
@JCNTH
[ExecuTorch][WebGPU] Fuse the SwiGLU elementwise chain
965c3c5
Pull Request resolved: #21129
The SwiGLU feed-forward activation lowered to separate gate and up projections
followed by a sigmoid and two elementwise multiplies, launching several
dispatches over the same tensors. This fuses the sigmoid and the two multiplies
into a single dynamically-resized 2D dispatch that computes
(gate * sigmoid(gate)) * up in one pass. Fusion applies only when the pattern
is exact and its scratch is planner-owned; graph outputs, extra consumers, and
separate inputs fall back to the unfused chain, and the landed broad-QKV
behavior is left untouched until its dedicated corrective diff. No Vulkan
analogue: the Vulkan backend has no fused SiLU/SwiGLU shader and composes it
from a sigmoid unary op plus an elementwise multiply at graph level.
Key changes:
- runtime/ops/mul/silu_mul_fused.wgsl (+ generated header): one-thread-per-
element SiLU-gated multiply of gate and up into a single output.
- WebGPUGraph.cpp: detect the exact gate/up/sigmoid/mul pattern, own the gate
scratch, size the 2D dispatch, and fall back conservatively.
ghstack-source-id: 411961441
@exported-using-ghexport
Differential Revision: [D113171742](https://our.internmc.facebook.com/intern/diff/D113171742/)
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[ExecuTorch][WebGPU] Fuse the SwiGLU elementwise chain - #21129

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[ExecuTorch][WebGPU] Fuse the SwiGLU elementwise chain#21129
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Stack from ghstack (oldest at bottom):

The SwiGLU feed-forward activation lowered to separate gate and up projections
followed by a sigmoid and two elementwise multiplies, launching several
dispatches over the same tensors. This fuses the sigmoid and the two multiplies
into a single dynamically-resized 2D dispatch that computes
(gate * sigmoid(gate)) * up in one pass. Fusion applies only when the pattern
is exact and its scratch is planner-owned; graph outputs, extra consumers, and
separate inputs fall back to the unfused chain, and the landed broad-QKV
behavior is left untouched until its dedicated corrective diff. No Vulkan
analogue: the Vulkan backend has no fused SiLU/SwiGLU shader and composes it
from a sigmoid unary op plus an elementwise multiply at graph level.

Key changes:

  • runtime/ops/mul/silu_mul_fused.wgsl (+ generated header): one-thread-per-
    element SiLU-gated multiply of gate and up into a single output.
  • WebGPUGraph.cpp: detect the exact gate/up/sigmoid/mul pattern, own the gate
    scratch, size the 2D dispatch, and fall back conservatively.
    @exported-using-ghexport

Differential Revision: D113171742

Differential Revision: D113171742

@JCNTH
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🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/21129

Note: Links to docs will display an error until the docs builds have been completed.

❌ 37 New Failures, 22 Pending

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[ExecuTorch][WebGPU] Fuse the SwiGLU elementwise chain
b398254
Pull Request resolved: #21129
The SwiGLU feed-forward activation lowered to separate gate and up projections
followed by a sigmoid and two elementwise multiplies, launching several
dispatches over the same tensors. This fuses the sigmoid and the two multiplies
into a single dynamically-resized 2D dispatch that computes
(gate * sigmoid(gate)) * up in one pass. Fusion applies only when the pattern
is exact and its scratch is planner-owned; graph outputs, extra consumers, and
separate inputs fall back to the unfused chain, and the landed broad-QKV
behavior is left untouched until its dedicated corrective diff. No Vulkan
analogue: the Vulkan backend has no fused SiLU/SwiGLU shader and composes it
from a sigmoid unary op plus an elementwise multiply at graph level.
Key changes:
- runtime/ops/mul/silu_mul_fused.wgsl (+ generated header): one-thread-per-
element SiLU-gated multiply of gate and up into a single output.
- WebGPUGraph.cpp: detect the exact gate/up/sigmoid/mul pattern, own the gate
scratch, size the 2D dispatch, and fall back conservatively.
ghstack-source-id: 411961441
@exported-using-ghexport
Differential Revision: [D113171742](https://our.internmc.facebook.com/intern/diff/D113171742/)
JCNTH added a commit that referenced this pull request Aug 7, 2026
@JCNTH
[ExecuTorch][WebGPU] Fuse the SwiGLU elementwise chain
965c3c5
Pull Request resolved: #21129
The SwiGLU feed-forward activation lowered to separate gate and up projections
followed by a sigmoid and two elementwise multiplies, launching several
dispatches over the same tensors. This fuses the sigmoid and the two multiplies
into a single dynamically-resized 2D dispatch that computes
(gate * sigmoid(gate)) * up in one pass. Fusion applies only when the pattern
is exact and its scratch is planner-owned; graph outputs, extra consumers, and
separate inputs fall back to the unfused chain, and the landed broad-QKV
behavior is left untouched until its dedicated corrective diff. No Vulkan
analogue: the Vulkan backend has no fused SiLU/SwiGLU shader and composes it
from a sigmoid unary op plus an elementwise multiply at graph level.
Key changes:
- runtime/ops/mul/silu_mul_fused.wgsl (+ generated header): one-thread-per-
element SiLU-gated multiply of gate and up into a single output.
- WebGPUGraph.cpp: detect the exact gate/up/sigmoid/mul pattern, own the gate
scratch, size the 2D dispatch, and fall back conservatively.
ghstack-source-id: 411961441
@exported-using-ghexport
Differential Revision: [D113171742](https://our.internmc.facebook.com/intern/diff/D113171742/)
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[ExecuTorch][WebGPU] Fuse the SwiGLU elementwise chain - #21129

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Stack from ghstack (oldest at bottom):

The SwiGLU feed-forward activation lowered to separate gate and up projections
followed by a sigmoid and two elementwise multiplies, launching several
dispatches over the same tensors. This fuses the sigmoid and the two multiplies
into a single dynamically-resized 2D dispatch that computes
(gate * sigmoid(gate)) * up in one pass. Fusion applies only when the pattern
is exact and its scratch is planner-owned; graph outputs, extra consumers, and
separate inputs fall back to the unfused chain, and the landed broad-QKV
behavior is left untouched until its dedicated corrective diff. No Vulkan
analogue: the Vulkan backend has no fused SiLU/SwiGLU shader and composes it
from a sigmoid unary op plus an elementwise multiply at graph level.

Key changes:

  • runtime/ops/mul/silu_mul_fused.wgsl (+ generated header): one-thread-per-
    element SiLU-gated multiply of gate and up into a single output.
  • WebGPUGraph.cpp: detect the exact gate/up/sigmoid/mul pattern, own the gate
    scratch, size the 2D dispatch, and fall back conservatively.
    @exported-using-ghexport

Differential Revision: D113171742

Differential Revision: D113171742

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🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/21129

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[ExecuTorch][WebGPU] Fuse the SwiGLU elementwise chain
b398254
Pull Request resolved: #21129
The SwiGLU feed-forward activation lowered to separate gate and up projections
followed by a sigmoid and two elementwise multiplies, launching several
dispatches over the same tensors. This fuses the sigmoid and the two multiplies
into a single dynamically-resized 2D dispatch that computes
(gate * sigmoid(gate)) * up in one pass. Fusion applies only when the pattern
is exact and its scratch is planner-owned; graph outputs, extra consumers, and
separate inputs fall back to the unfused chain, and the landed broad-QKV
behavior is left untouched until its dedicated corrective diff. No Vulkan
analogue: the Vulkan backend has no fused SiLU/SwiGLU shader and composes it
from a sigmoid unary op plus an elementwise multiply at graph level.
Key changes:
- runtime/ops/mul/silu_mul_fused.wgsl (+ generated header): one-thread-per-
element SiLU-gated multiply of gate and up into a single output.
- WebGPUGraph.cpp: detect the exact gate/up/sigmoid/mul pattern, own the gate
scratch, size the 2D dispatch, and fall back conservatively.
ghstack-source-id: 411961441
@exported-using-ghexport
Differential Revision: [D113171742](https://our.internmc.facebook.com/intern/diff/D113171742/)
JCNTH added a commit that referenced this pull request Aug 7, 2026
@JCNTH
[ExecuTorch][WebGPU] Fuse the SwiGLU elementwise chain
965c3c5
Pull Request resolved: #21129
The SwiGLU feed-forward activation lowered to separate gate and up projections
followed by a sigmoid and two elementwise multiplies, launching several
dispatches over the same tensors. This fuses the sigmoid and the two multiplies
into a single dynamically-resized 2D dispatch that computes
(gate * sigmoid(gate)) * up in one pass. Fusion applies only when the pattern
is exact and its scratch is planner-owned; graph outputs, extra consumers, and
separate inputs fall back to the unfused chain, and the landed broad-QKV
behavior is left untouched until its dedicated corrective diff. No Vulkan
analogue: the Vulkan backend has no fused SiLU/SwiGLU shader and composes it
from a sigmoid unary op plus an elementwise multiply at graph level.
Key changes:
- runtime/ops/mul/silu_mul_fused.wgsl (+ generated header): one-thread-per-
element SiLU-gated multiply of gate and up into a single output.
- WebGPUGraph.cpp: detect the exact gate/up/sigmoid/mul pattern, own the gate
scratch, size the 2D dispatch, and fall back conservatively.
ghstack-source-id: 411961441
@exported-using-ghexport
Differential Revision: [D113171742](https://our.internmc.facebook.com/intern/diff/D113171742/)
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[ExecuTorch][WebGPU] Fuse the SwiGLU elementwise chain - #21129

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Stack from ghstack (oldest at bottom):

The SwiGLU feed-forward activation lowered to separate gate and up projections
followed by a sigmoid and two elementwise multiplies, launching several
dispatches over the same tensors. This fuses the sigmoid and the two multiplies
into a single dynamically-resized 2D dispatch that computes
(gate * sigmoid(gate)) * up in one pass. Fusion applies only when the pattern
is exact and its scratch is planner-owned; graph outputs, extra consumers, and
separate inputs fall back to the unfused chain, and the landed broad-QKV
behavior is left untouched until its dedicated corrective diff. No Vulkan
analogue: the Vulkan backend has no fused SiLU/SwiGLU shader and composes it
from a sigmoid unary op plus an elementwise multiply at graph level.

Key changes:

  • runtime/ops/mul/silu_mul_fused.wgsl (+ generated header): one-thread-per-
    element SiLU-gated multiply of gate and up into a single output.
  • WebGPUGraph.cpp: detect the exact gate/up/sigmoid/mul pattern, own the gate
    scratch, size the 2D dispatch, and fall back conservatively.
    @exported-using-ghexport

Differential Revision: D113171742

Differential Revision: D113171742

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🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/21129

Note: Links to docs will display an error until the docs builds have been completed.

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[ExecuTorch][WebGPU] Fuse the SwiGLU elementwise chain
b398254
Pull Request resolved: #21129
The SwiGLU feed-forward activation lowered to separate gate and up projections
followed by a sigmoid and two elementwise multiplies, launching several
dispatches over the same tensors. This fuses the sigmoid and the two multiplies
into a single dynamically-resized 2D dispatch that computes
(gate * sigmoid(gate)) * up in one pass. Fusion applies only when the pattern
is exact and its scratch is planner-owned; graph outputs, extra consumers, and
separate inputs fall back to the unfused chain, and the landed broad-QKV
behavior is left untouched until its dedicated corrective diff. No Vulkan
analogue: the Vulkan backend has no fused SiLU/SwiGLU shader and composes it
from a sigmoid unary op plus an elementwise multiply at graph level.
Key changes:
- runtime/ops/mul/silu_mul_fused.wgsl (+ generated header): one-thread-per-
element SiLU-gated multiply of gate and up into a single output.
- WebGPUGraph.cpp: detect the exact gate/up/sigmoid/mul pattern, own the gate
scratch, size the 2D dispatch, and fall back conservatively.
ghstack-source-id: 411961441
@exported-using-ghexport
Differential Revision: [D113171742](https://our.internmc.facebook.com/intern/diff/D113171742/)
JCNTH added a commit that referenced this pull request Aug 7, 2026
@JCNTH
[ExecuTorch][WebGPU] Fuse the SwiGLU elementwise chain
965c3c5
Pull Request resolved: #21129
The SwiGLU feed-forward activation lowered to separate gate and up projections
followed by a sigmoid and two elementwise multiplies, launching several
dispatches over the same tensors. This fuses the sigmoid and the two multiplies
into a single dynamically-resized 2D dispatch that computes
(gate * sigmoid(gate)) * up in one pass. Fusion applies only when the pattern
is exact and its scratch is planner-owned; graph outputs, extra consumers, and
separate inputs fall back to the unfused chain, and the landed broad-QKV
behavior is left untouched until its dedicated corrective diff. No Vulkan
analogue: the Vulkan backend has no fused SiLU/SwiGLU shader and composes it
from a sigmoid unary op plus an elementwise multiply at graph level.
Key changes:
- runtime/ops/mul/silu_mul_fused.wgsl (+ generated header): one-thread-per-
element SiLU-gated multiply of gate and up into a single output.
- WebGPUGraph.cpp: detect the exact gate/up/sigmoid/mul pattern, own the gate
scratch, size the 2D dispatch, and fall back conservatively.
ghstack-source-id: 411961441
@exported-using-ghexport
Differential Revision: [D113171742](https://our.internmc.facebook.com/intern/diff/D113171742/)
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[ExecuTorch][WebGPU] Fuse the SwiGLU elementwise chain - #21129

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Stack from ghstack (oldest at bottom):

The SwiGLU feed-forward activation lowered to separate gate and up projections
followed by a sigmoid and two elementwise multiplies, launching several
dispatches over the same tensors. This fuses the sigmoid and the two multiplies
into a single dynamically-resized 2D dispatch that computes
(gate * sigmoid(gate)) * up in one pass. Fusion applies only when the pattern
is exact and its scratch is planner-owned; graph outputs, extra consumers, and
separate inputs fall back to the unfused chain, and the landed broad-QKV
behavior is left untouched until its dedicated corrective diff. No Vulkan
analogue: the Vulkan backend has no fused SiLU/SwiGLU shader and composes it
from a sigmoid unary op plus an elementwise multiply at graph level.

Key changes:

  • runtime/ops/mul/silu_mul_fused.wgsl (+ generated header): one-thread-per-
    element SiLU-gated multiply of gate and up into a single output.
  • WebGPUGraph.cpp: detect the exact gate/up/sigmoid/mul pattern, own the gate
    scratch, size the 2D dispatch, and fall back conservatively.
    @exported-using-ghexport

Differential Revision: D113171742

Differential Revision: D113171742

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🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/21129

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[ExecuTorch][WebGPU] Fuse the SwiGLU elementwise chain
b398254
Pull Request resolved: #21129
The SwiGLU feed-forward activation lowered to separate gate and up projections
followed by a sigmoid and two elementwise multiplies, launching several
dispatches over the same tensors. This fuses the sigmoid and the two multiplies
into a single dynamically-resized 2D dispatch that computes
(gate * sigmoid(gate)) * up in one pass. Fusion applies only when the pattern
is exact and its scratch is planner-owned; graph outputs, extra consumers, and
separate inputs fall back to the unfused chain, and the landed broad-QKV
behavior is left untouched until its dedicated corrective diff. No Vulkan
analogue: the Vulkan backend has no fused SiLU/SwiGLU shader and composes it
from a sigmoid unary op plus an elementwise multiply at graph level.
Key changes:
- runtime/ops/mul/silu_mul_fused.wgsl (+ generated header): one-thread-per-
element SiLU-gated multiply of gate and up into a single output.
- WebGPUGraph.cpp: detect the exact gate/up/sigmoid/mul pattern, own the gate
scratch, size the 2D dispatch, and fall back conservatively.
ghstack-source-id: 411961441
@exported-using-ghexport
Differential Revision: [D113171742](https://our.internmc.facebook.com/intern/diff/D113171742/)
JCNTH added a commit that referenced this pull request Aug 7, 2026
@JCNTH
[ExecuTorch][WebGPU] Fuse the SwiGLU elementwise chain
965c3c5
Pull Request resolved: #21129
The SwiGLU feed-forward activation lowered to separate gate and up projections
followed by a sigmoid and two elementwise multiplies, launching several
dispatches over the same tensors. This fuses the sigmoid and the two multiplies
into a single dynamically-resized 2D dispatch that computes
(gate * sigmoid(gate)) * up in one pass. Fusion applies only when the pattern
is exact and its scratch is planner-owned; graph outputs, extra consumers, and
separate inputs fall back to the unfused chain, and the landed broad-QKV
behavior is left untouched until its dedicated corrective diff. No Vulkan
analogue: the Vulkan backend has no fused SiLU/SwiGLU shader and composes it
from a sigmoid unary op plus an elementwise multiply at graph level.
Key changes:
- runtime/ops/mul/silu_mul_fused.wgsl (+ generated header): one-thread-per-
element SiLU-gated multiply of gate and up into a single output.
- WebGPUGraph.cpp: detect the exact gate/up/sigmoid/mul pattern, own the gate
scratch, size the 2D dispatch, and fall back conservatively.
ghstack-source-id: 411961441
@exported-using-ghexport
Differential Revision: [D113171742](https://our.internmc.facebook.com/intern/diff/D113171742/)
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