[ExecuTorch][WebGPU] 2D-fold mul + permute dispatch (lift 65535 1D cap)

[ghost]

Stack from ghstack (oldest at bottom):

• [ExecuTorch][WebGPU] Convert remaining native tests to GTest #20706
• [ExecuTorch][WebGPU] Use requiredFeatures instance API on native + emscripten Dawn #20652
• ->[ExecuTorch][WebGPU] 2D-fold mul + permute dispatch (lift 65535 1D cap) #20651
• [ExecuTorch][WebGPU] 2D compute dispatch tests — prefill golden + fold unit test #20584
• [ExecuTorch][WebGPU] 2D compute dispatch — lift the 65535 per-dim cap (prefill path) #20583
• [ExecuTorch][WebGPU] Dynamic-shape integration test (allocate-at-max + per-op resize) #20582
• [ExecuTorch][WebGPU] Dynamic resize hook for slice_copy (dynamic start/end) #20581
• [ExecuTorch][WebGPU] Dynamic resize hook for SDPA (live seq-len S) #20580
• [ExecuTorch][WebGPU] Dynamic resize hook for view_copy #20579
• [ExecuTorch][WebGPU] Dynamic resize hooks for sigmoid and select_copy #20578
• [ExecuTorch][WebGPU] Dynamic resize hooks for add and mul #20577
• [ExecuTorch][WebGPU] Dynamic resize hook for linear_q4gsw #20576
• [ExecuTorch][WebGPU] Dynamic resize hooks for rms_norm, embedding, rope #20575
• [ExecuTorch][WebGPU] Dynamic tensor-shape resize engine core #20574
• [ExecuTorch][WebGPU] SymInt arithmetic ops (add/sub/mul/floordiv) for dynamic shapes #20573

Lift the 65535 workgroup-per-dim cap for mul and permute so they run at any numel.

mul.Tensor and permute still used compute_1d_workgroup_count, which throws once numel / wg_size > 65535 — hit by a realistic Llama-3.2-1B LoRA layer (mul over [2048, 8192] = 262k workgroups; permute of [2048, 2048] = 65536). add/sub/div/fill/sdpa already use the 2D fold; this brings mul + permute in line.

Key changes:

• mul/BinaryOp.cpp, permute/Permute.cpp — compute_1d_workgroup_count → compute_2d_workgroup_count (returns utils::WgCount); dispatch + resize hook now set both workgroup_count_x and workgroup_count_y.
• binary_mul.wgsl, permute.wgsl — main takes @builtin(num_workgroups); flat index gid.x + gid.y * (num_workgroups.x * wg_size) (regenerated *_wgsl.h).

Mirrors the landed add op fold (runtime/ops/add/{BinaryOp.cpp,binary_add.wgsl}).

Co-authored-with: Claude Code.
@exported-using-ghexport

Differential Revision: D110149677

Differential Revision: D110149677

[pytorch-bot]

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/20651

• 📄 Preview Python docs built from this PR

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

❌ 1 New Failure

As of commit 91b2d97 with merge base 124b677 ():

NEW FAILURE - The following job has failed:

• pull / test-binary-size-linux-gcc / linux-job (gh)
  RuntimeError: Command docker exec -t 96ee68bc5f25708b763420ba1de31656e58aac15ef00d525a6e68b856280ef0a /exec failed with exit code 1

This comment was automatically generated by Dr. CI and updates every 15 minutes.

[github-actions]

This PR needs a release notes: label

If your change should be included in the release notes (i.e. would users of this library care about this change?), please use a label starting with release notes:. This helps us keep track and include your important work in the next release notes.

To add a label, you can comment to pytorchbot, for example
@pytorchbot label "release notes: none"

For more information, see
https://github.com/pytorch/pytorch/wiki/PyTorch-AutoLabel-Bot#why-categorize-for-release-notes-and-how-does-it-work.

[ghost]

@claude Review thoroughly. Check for stale code / bugs.

[claude]

Claude finished @JulianCloudNTH's task in 2m 47s —— View job

---

Review: WebGPU 2D-fold for mul + permute

• Read PR diff and understand the change
• Compare against the reference add op fold
• Check compute_2d_workgroup_count / WgCount / add_dispatch signatures
• Verify WGSL flat-index math is correct
• Check for stale code / bugs
• Post review

---

Reviewed against the landed add fold (ops/add/{BinaryOp.cpp,binary_add.wgsl}), WebGPUUtils.h (compute_2d_workgroup_count/fold_workgroup_count_2d/WgCount), and the dispatch path in WebGPUGraph.{h,cpp}. The change is correct and a faithful mirror of the reference — no bugs found. One stale comment worth fixing.

✅ Correctness verified

• add_dispatch brace-init matches the struct.WebGPUDispatch field order is {pipeline, bind_group, workgroup_count_x, kernel_name, workgroup_count_y} (WebGPUGraph.h:46-51). Both call sites pass {pipeline, bind_group, workgroup_count.x, "mul"/"permute", workgroup_count.y} — positions line up exactly. add uses "" as the label; mul/permute supplying real bench labels is a minor improvement, not a bug.
• Dispatch consumes .y.WebGPUGraph.cpp:818 and :898 both call wgpuComputePassEncoderDispatchWorkgroups(pass, workgroup_count_x, workgroup_count_y, 1), so the folded y is actually launched.
• Flat-index math is exact.idx = gid.x + gid.y * (num_workgroups.x * wg_size). With grid (x, y, 1) and @workgroup_size(wg_size,1,1): gid.x ∈ [0, x·wg_size), gid.y ∈ [0, y), num_workgroups.x == x, so idx covers [0, x·y·wg_size), and x·y ≥ ceil(numel/wg_size). The idx >= out_meta.numel guard drops the tail. Byte-identical to binary_add.wgsl:17.
• mul resize hook rewrites both workgroup_count_x and workgroup_count_y (BinaryOp.cpp:204-205), matching add:190-191. permute has no resize hook (it registers none), so nothing to update there — consistent with the op being static-shape only.
• num_workgroups builtin is correctly added to both main signatures and both regenerated *_wgsl.h SHAs were updated.

🟡 Minor: stale comment

backends/webgpu/runtime/ops/mul/BinaryOp.cpp:37

// Rank guard (NCHW backend is <= 4 dims; 1D dispatch only).

The 1D dispatch only clause is now inaccurate — dispatch is 2D-folded. Suggest trimming to // Rank guard (NCHW backend is <= 4 dims).permute has no equivalent stale comment. Fix this →

💭 Observations (non-blocking, shared with the landed add)

• gid.y * (num_workgroups.x * wg_size) is u32 arithmetic. In practice bounded by numel (a uint32_t), so no overflow for any realistic tensor; only a theoretical concern as numel → 2³². This is inherited verbatim from the reference add/sdpa fold, so it's not something this PR should change in isolation.
• No test exercises the >65535 path.test_mul.py / test_permute.py exist but I didn't find a case at the numel that previously threw (mul over [2048, 8192], permute of [2048, 2048]). Adding one would lock in the fix and guard against regression — though if the add fold landed without such a case, matching that precedent is reasonable.

Verdict: LGTM. The one stale comment is optional cleanup; the logic is sound and consistent with the established pattern.
· branch gh/JulianCloudNTH/83/head

[ghost]

Stack from ghstack (oldest at bottom):

• [ExecuTorch][WebGPU] Convert remaining native tests to GTest #20706
• [ExecuTorch][WebGPU] Use requiredFeatures instance API on native + emscripten Dawn #20652
• ->[ExecuTorch][WebGPU] 2D-fold mul + permute dispatch (lift 65535 1D cap) #20651
• [ExecuTorch][WebGPU] 2D compute dispatch tests — prefill golden + fold unit test #20584
• [ExecuTorch][WebGPU] 2D compute dispatch — lift the 65535 per-dim cap (prefill path) #20583
• [ExecuTorch][WebGPU] Dynamic-shape integration test (allocate-at-max + per-op resize) #20582
• [ExecuTorch][WebGPU] Dynamic resize hook for slice_copy (dynamic start/end) #20581
• [ExecuTorch][WebGPU] Dynamic resize hook for SDPA (live seq-len S) #20580
• [ExecuTorch][WebGPU] Dynamic resize hook for view_copy #20579
• [ExecuTorch][WebGPU] Dynamic resize hooks for sigmoid and select_copy #20578
• [ExecuTorch][WebGPU] Dynamic resize hooks for add and mul #20577
• [ExecuTorch][WebGPU] Dynamic resize hook for linear_q4gsw #20576
• [ExecuTorch][WebGPU] Dynamic resize hooks for rms_norm, embedding, rope #20575
• [ExecuTorch][WebGPU] Dynamic tensor-shape resize engine core #20574
• [ExecuTorch][WebGPU] SymInt arithmetic ops (add/sub/mul/floordiv) for dynamic shapes #20573

Lift the 65535 workgroup-per-dim cap for mul and permute so they run at any numel.

mul.Tensor and permute still used compute_1d_workgroup_count, which throws once numel / wg_size > 65535 — hit by a realistic Llama-3.2-1B LoRA layer (mul over [2048, 8192] = 262k workgroups; permute of [2048, 2048] = 65536). add/sub/div/fill/sdpa already use the 2D fold; this brings mul + permute in line.

Key changes:

• mul/BinaryOp.cpp, permute/Permute.cpp — compute_1d_workgroup_count → compute_2d_workgroup_count (returns utils::WgCount); dispatch + resize hook now set both workgroup_count_x and workgroup_count_y.
• binary_mul.wgsl, permute.wgsl — main takes @builtin(num_workgroups); flat index gid.x + gid.y * (num_workgroups.x * wg_size) (regenerated *_wgsl.h).

Mirrors the landed add op fold (runtime/ops/add/{BinaryOp.cpp,binary_add.wgsl}).

Co-authored-with: Claude Code.
@exported-using-ghexport

Differential Revision: D110149677

Differential Revision: D110149677

[pytorch-bot]

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/20651

• 📄 Preview Python docs built from this PR

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

❌ 1 New Failure

As of commit 91b2d97 with merge base 124b677 ():

NEW FAILURE - The following job has failed:

• pull / test-binary-size-linux-gcc / linux-job (gh)
  RuntimeError: Command docker exec -t 96ee68bc5f25708b763420ba1de31656e58aac15ef00d525a6e68b856280ef0a /exec failed with exit code 1

This comment was automatically generated by Dr. CI and updates every 15 minutes.

[github-actions]

This PR needs a release notes: label

If your change should be included in the release notes (i.e. would users of this library care about this change?), please use a label starting with release notes:. This helps us keep track and include your important work in the next release notes.

To add a label, you can comment to pytorchbot, for example
@pytorchbot label "release notes: none"

For more information, see
https://github.com/pytorch/pytorch/wiki/PyTorch-AutoLabel-Bot#why-categorize-for-release-notes-and-how-does-it-work.

[ghost]

@claude Review thoroughly. Check for stale code / bugs.

[claude]

Claude finished @JulianCloudNTH's task in 2m 47s —— View job

---

Review: WebGPU 2D-fold for mul + permute

• Read PR diff and understand the change
• Compare against the reference add op fold
• Check compute_2d_workgroup_count / WgCount / add_dispatch signatures
• Verify WGSL flat-index math is correct
• Check for stale code / bugs
• Post review

---

Reviewed against the landed add fold (ops/add/{BinaryOp.cpp,binary_add.wgsl}), WebGPUUtils.h (compute_2d_workgroup_count/fold_workgroup_count_2d/WgCount), and the dispatch path in WebGPUGraph.{h,cpp}. The change is correct and a faithful mirror of the reference — no bugs found. One stale comment worth fixing.

✅ Correctness verified

• add_dispatch brace-init matches the struct.WebGPUDispatch field order is {pipeline, bind_group, workgroup_count_x, kernel_name, workgroup_count_y} (WebGPUGraph.h:46-51). Both call sites pass {pipeline, bind_group, workgroup_count.x, "mul"/"permute", workgroup_count.y} — positions line up exactly. add uses "" as the label; mul/permute supplying real bench labels is a minor improvement, not a bug.
• Dispatch consumes .y.WebGPUGraph.cpp:818 and :898 both call wgpuComputePassEncoderDispatchWorkgroups(pass, workgroup_count_x, workgroup_count_y, 1), so the folded y is actually launched.
• Flat-index math is exact.idx = gid.x + gid.y * (num_workgroups.x * wg_size). With grid (x, y, 1) and @workgroup_size(wg_size,1,1): gid.x ∈ [0, x·wg_size), gid.y ∈ [0, y), num_workgroups.x == x, so idx covers [0, x·y·wg_size), and x·y ≥ ceil(numel/wg_size). The idx >= out_meta.numel guard drops the tail. Byte-identical to binary_add.wgsl:17.
• mul resize hook rewrites both workgroup_count_x and workgroup_count_y (BinaryOp.cpp:204-205), matching add:190-191. permute has no resize hook (it registers none), so nothing to update there — consistent with the op being static-shape only.
• num_workgroups builtin is correctly added to both main signatures and both regenerated *_wgsl.h SHAs were updated.

🟡 Minor: stale comment

backends/webgpu/runtime/ops/mul/BinaryOp.cpp:37

// Rank guard (NCHW backend is <= 4 dims; 1D dispatch only).

The 1D dispatch only clause is now inaccurate — dispatch is 2D-folded. Suggest trimming to // Rank guard (NCHW backend is <= 4 dims).permute has no equivalent stale comment. Fix this →

💭 Observations (non-blocking, shared with the landed add)

• gid.y * (num_workgroups.x * wg_size) is u32 arithmetic. In practice bounded by numel (a uint32_t), so no overflow for any realistic tensor; only a theoretical concern as numel → 2³². This is inherited verbatim from the reference add/sdpa fold, so it's not something this PR should change in isolation.
• No test exercises the >65535 path.test_mul.py / test_permute.py exist but I didn't find a case at the numel that previously threw (mul over [2048, 8192], permute of [2048, 2048]). Adding one would lock in the fix and guard against regression — though if the add fold landed without such a case, matching that precedent is reasonable.

Verdict: LGTM. The one stale comment is optional cleanup; the logic is sound and consistent with the established pattern.
· branch gh/JulianCloudNTH/83/head

[ghost]

Stack from ghstack (oldest at bottom):

• [ExecuTorch][WebGPU] Convert remaining native tests to GTest #20706
• [ExecuTorch][WebGPU] Use requiredFeatures instance API on native + emscripten Dawn #20652
• ->[ExecuTorch][WebGPU] 2D-fold mul + permute dispatch (lift 65535 1D cap) #20651
• [ExecuTorch][WebGPU] 2D compute dispatch tests — prefill golden + fold unit test #20584
• [ExecuTorch][WebGPU] 2D compute dispatch — lift the 65535 per-dim cap (prefill path) #20583
• [ExecuTorch][WebGPU] Dynamic-shape integration test (allocate-at-max + per-op resize) #20582
• [ExecuTorch][WebGPU] Dynamic resize hook for slice_copy (dynamic start/end) #20581
• [ExecuTorch][WebGPU] Dynamic resize hook for SDPA (live seq-len S) #20580
• [ExecuTorch][WebGPU] Dynamic resize hook for view_copy #20579
• [ExecuTorch][WebGPU] Dynamic resize hooks for sigmoid and select_copy #20578
• [ExecuTorch][WebGPU] Dynamic resize hooks for add and mul #20577
• [ExecuTorch][WebGPU] Dynamic resize hook for linear_q4gsw #20576
• [ExecuTorch][WebGPU] Dynamic resize hooks for rms_norm, embedding, rope #20575
• [ExecuTorch][WebGPU] Dynamic tensor-shape resize engine core #20574
• [ExecuTorch][WebGPU] SymInt arithmetic ops (add/sub/mul/floordiv) for dynamic shapes #20573

Lift the 65535 workgroup-per-dim cap for mul and permute so they run at any numel.

mul.Tensor and permute still used compute_1d_workgroup_count, which throws once numel / wg_size > 65535 — hit by a realistic Llama-3.2-1B LoRA layer (mul over [2048, 8192] = 262k workgroups; permute of [2048, 2048] = 65536). add/sub/div/fill/sdpa already use the 2D fold; this brings mul + permute in line.

Key changes:

• mul/BinaryOp.cpp, permute/Permute.cpp — compute_1d_workgroup_count → compute_2d_workgroup_count (returns utils::WgCount); dispatch + resize hook now set both workgroup_count_x and workgroup_count_y.
• binary_mul.wgsl, permute.wgsl — main takes @builtin(num_workgroups); flat index gid.x + gid.y * (num_workgroups.x * wg_size) (regenerated *_wgsl.h).

Mirrors the landed add op fold (runtime/ops/add/{BinaryOp.cpp,binary_add.wgsl}).

Co-authored-with: Claude Code.
@exported-using-ghexport

Differential Revision: D110149677

Differential Revision: D110149677

[pytorch-bot]

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/20651

• 📄 Preview Python docs built from this PR

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

❌ 1 New Failure

As of commit 91b2d97 with merge base 124b677 ():

NEW FAILURE - The following job has failed:

• pull / test-binary-size-linux-gcc / linux-job (gh)
  RuntimeError: Command docker exec -t 96ee68bc5f25708b763420ba1de31656e58aac15ef00d525a6e68b856280ef0a /exec failed with exit code 1

This comment was automatically generated by Dr. CI and updates every 15 minutes.

[github-actions]

This PR needs a release notes: label

If your change should be included in the release notes (i.e. would users of this library care about this change?), please use a label starting with release notes:. This helps us keep track and include your important work in the next release notes.

To add a label, you can comment to pytorchbot, for example
@pytorchbot label "release notes: none"

For more information, see
https://github.com/pytorch/pytorch/wiki/PyTorch-AutoLabel-Bot#why-categorize-for-release-notes-and-how-does-it-work.

[ghost]

@claude Review thoroughly. Check for stale code / bugs.

[claude]

Claude finished @JulianCloudNTH's task in 2m 47s —— View job

---

Review: WebGPU 2D-fold for mul + permute

• Read PR diff and understand the change
• Compare against the reference add op fold
• Check compute_2d_workgroup_count / WgCount / add_dispatch signatures
• Verify WGSL flat-index math is correct
• Check for stale code / bugs
• Post review

---

Reviewed against the landed add fold (ops/add/{BinaryOp.cpp,binary_add.wgsl}), WebGPUUtils.h (compute_2d_workgroup_count/fold_workgroup_count_2d/WgCount), and the dispatch path in WebGPUGraph.{h,cpp}. The change is correct and a faithful mirror of the reference — no bugs found. One stale comment worth fixing.

✅ Correctness verified

• add_dispatch brace-init matches the struct.WebGPUDispatch field order is {pipeline, bind_group, workgroup_count_x, kernel_name, workgroup_count_y} (WebGPUGraph.h:46-51). Both call sites pass {pipeline, bind_group, workgroup_count.x, "mul"/"permute", workgroup_count.y} — positions line up exactly. add uses "" as the label; mul/permute supplying real bench labels is a minor improvement, not a bug.
• Dispatch consumes .y.WebGPUGraph.cpp:818 and :898 both call wgpuComputePassEncoderDispatchWorkgroups(pass, workgroup_count_x, workgroup_count_y, 1), so the folded y is actually launched.
• Flat-index math is exact.idx = gid.x + gid.y * (num_workgroups.x * wg_size). With grid (x, y, 1) and @workgroup_size(wg_size,1,1): gid.x ∈ [0, x·wg_size), gid.y ∈ [0, y), num_workgroups.x == x, so idx covers [0, x·y·wg_size), and x·y ≥ ceil(numel/wg_size). The idx >= out_meta.numel guard drops the tail. Byte-identical to binary_add.wgsl:17.
• mul resize hook rewrites both workgroup_count_x and workgroup_count_y (BinaryOp.cpp:204-205), matching add:190-191. permute has no resize hook (it registers none), so nothing to update there — consistent with the op being static-shape only.
• num_workgroups builtin is correctly added to both main signatures and both regenerated *_wgsl.h SHAs were updated.

🟡 Minor: stale comment

backends/webgpu/runtime/ops/mul/BinaryOp.cpp:37

// Rank guard (NCHW backend is <= 4 dims; 1D dispatch only).

The 1D dispatch only clause is now inaccurate — dispatch is 2D-folded. Suggest trimming to // Rank guard (NCHW backend is <= 4 dims).permute has no equivalent stale comment. Fix this →

💭 Observations (non-blocking, shared with the landed add)

• gid.y * (num_workgroups.x * wg_size) is u32 arithmetic. In practice bounded by numel (a uint32_t), so no overflow for any realistic tensor; only a theoretical concern as numel → 2³². This is inherited verbatim from the reference add/sdpa fold, so it's not something this PR should change in isolation.
• No test exercises the >65535 path.test_mul.py / test_permute.py exist but I didn't find a case at the numel that previously threw (mul over [2048, 8192], permute of [2048, 2048]). Adding one would lock in the fix and guard against regression — though if the add fold landed without such a case, matching that precedent is reasonable.

Verdict: LGTM. The one stale comment is optional cleanup; the logic is sound and consistent with the established pattern.
· branch gh/JulianCloudNTH/83/head

[ghost]

Stack from ghstack (oldest at bottom):

• [ExecuTorch][WebGPU] Convert remaining native tests to GTest #20706
• [ExecuTorch][WebGPU] Use requiredFeatures instance API on native + emscripten Dawn #20652
• ->[ExecuTorch][WebGPU] 2D-fold mul + permute dispatch (lift 65535 1D cap) #20651
• [ExecuTorch][WebGPU] 2D compute dispatch tests — prefill golden + fold unit test #20584
• [ExecuTorch][WebGPU] 2D compute dispatch — lift the 65535 per-dim cap (prefill path) #20583
• [ExecuTorch][WebGPU] Dynamic-shape integration test (allocate-at-max + per-op resize) #20582
• [ExecuTorch][WebGPU] Dynamic resize hook for slice_copy (dynamic start/end) #20581
• [ExecuTorch][WebGPU] Dynamic resize hook for SDPA (live seq-len S) #20580
• [ExecuTorch][WebGPU] Dynamic resize hook for view_copy #20579
• [ExecuTorch][WebGPU] Dynamic resize hooks for sigmoid and select_copy #20578
• [ExecuTorch][WebGPU] Dynamic resize hooks for add and mul #20577
• [ExecuTorch][WebGPU] Dynamic resize hook for linear_q4gsw #20576
• [ExecuTorch][WebGPU] Dynamic resize hooks for rms_norm, embedding, rope #20575
• [ExecuTorch][WebGPU] Dynamic tensor-shape resize engine core #20574
• [ExecuTorch][WebGPU] SymInt arithmetic ops (add/sub/mul/floordiv) for dynamic shapes #20573

Lift the 65535 workgroup-per-dim cap for mul and permute so they run at any numel.

mul.Tensor and permute still used compute_1d_workgroup_count, which throws once numel / wg_size > 65535 — hit by a realistic Llama-3.2-1B LoRA layer (mul over [2048, 8192] = 262k workgroups; permute of [2048, 2048] = 65536). add/sub/div/fill/sdpa already use the 2D fold; this brings mul + permute in line.

Key changes:

• mul/BinaryOp.cpp, permute/Permute.cpp — compute_1d_workgroup_count → compute_2d_workgroup_count (returns utils::WgCount); dispatch + resize hook now set both workgroup_count_x and workgroup_count_y.
• binary_mul.wgsl, permute.wgsl — main takes @builtin(num_workgroups); flat index gid.x + gid.y * (num_workgroups.x * wg_size) (regenerated *_wgsl.h).

Mirrors the landed add op fold (runtime/ops/add/{BinaryOp.cpp,binary_add.wgsl}).

Co-authored-with: Claude Code.
@exported-using-ghexport

Differential Revision: D110149677

Differential Revision: D110149677

[pytorch-bot]

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/20651

• 📄 Preview Python docs built from this PR

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

❌ 1 New Failure

As of commit 91b2d97 with merge base 124b677 ():

NEW FAILURE - The following job has failed:

• pull / test-binary-size-linux-gcc / linux-job (gh)
  RuntimeError: Command docker exec -t 96ee68bc5f25708b763420ba1de31656e58aac15ef00d525a6e68b856280ef0a /exec failed with exit code 1

This comment was automatically generated by Dr. CI and updates every 15 minutes.

[github-actions]

This PR needs a release notes: label

If your change should be included in the release notes (i.e. would users of this library care about this change?), please use a label starting with release notes:. This helps us keep track and include your important work in the next release notes.

To add a label, you can comment to pytorchbot, for example
@pytorchbot label "release notes: none"

For more information, see
https://github.com/pytorch/pytorch/wiki/PyTorch-AutoLabel-Bot#why-categorize-for-release-notes-and-how-does-it-work.

[ghost]

@claude Review thoroughly. Check for stale code / bugs.

[claude]

Claude finished @JulianCloudNTH's task in 2m 47s —— View job

---

Review: WebGPU 2D-fold for mul + permute

• Read PR diff and understand the change
• Compare against the reference add op fold
• Check compute_2d_workgroup_count / WgCount / add_dispatch signatures
• Verify WGSL flat-index math is correct
• Check for stale code / bugs
• Post review

---

Reviewed against the landed add fold (ops/add/{BinaryOp.cpp,binary_add.wgsl}), WebGPUUtils.h (compute_2d_workgroup_count/fold_workgroup_count_2d/WgCount), and the dispatch path in WebGPUGraph.{h,cpp}. The change is correct and a faithful mirror of the reference — no bugs found. One stale comment worth fixing.

✅ Correctness verified

• add_dispatch brace-init matches the struct.WebGPUDispatch field order is {pipeline, bind_group, workgroup_count_x, kernel_name, workgroup_count_y} (WebGPUGraph.h:46-51). Both call sites pass {pipeline, bind_group, workgroup_count.x, "mul"/"permute", workgroup_count.y} — positions line up exactly. add uses "" as the label; mul/permute supplying real bench labels is a minor improvement, not a bug.
• Dispatch consumes .y.WebGPUGraph.cpp:818 and :898 both call wgpuComputePassEncoderDispatchWorkgroups(pass, workgroup_count_x, workgroup_count_y, 1), so the folded y is actually launched.
• Flat-index math is exact.idx = gid.x + gid.y * (num_workgroups.x * wg_size). With grid (x, y, 1) and @workgroup_size(wg_size,1,1): gid.x ∈ [0, x·wg_size), gid.y ∈ [0, y), num_workgroups.x == x, so idx covers [0, x·y·wg_size), and x·y ≥ ceil(numel/wg_size). The idx >= out_meta.numel guard drops the tail. Byte-identical to binary_add.wgsl:17.
• mul resize hook rewrites both workgroup_count_x and workgroup_count_y (BinaryOp.cpp:204-205), matching add:190-191. permute has no resize hook (it registers none), so nothing to update there — consistent with the op being static-shape only.
• num_workgroups builtin is correctly added to both main signatures and both regenerated *_wgsl.h SHAs were updated.

🟡 Minor: stale comment

backends/webgpu/runtime/ops/mul/BinaryOp.cpp:37

// Rank guard (NCHW backend is <= 4 dims; 1D dispatch only).

The 1D dispatch only clause is now inaccurate — dispatch is 2D-folded. Suggest trimming to // Rank guard (NCHW backend is <= 4 dims).permute has no equivalent stale comment. Fix this →

💭 Observations (non-blocking, shared with the landed add)

• gid.y * (num_workgroups.x * wg_size) is u32 arithmetic. In practice bounded by numel (a uint32_t), so no overflow for any realistic tensor; only a theoretical concern as numel → 2³². This is inherited verbatim from the reference add/sdpa fold, so it's not something this PR should change in isolation.
• No test exercises the >65535 path.test_mul.py / test_permute.py exist but I didn't find a case at the numel that previously threw (mul over [2048, 8192], permute of [2048, 2048]). Adding one would lock in the fix and guard against regression — though if the add fold landed without such a case, matching that precedent is reasonable.

Verdict: LGTM. The one stale comment is optional cleanup; the logic is sound and consistent with the established pattern.
· branch gh/JulianCloudNTH/83/head

[ghost]

Stack from ghstack (oldest at bottom):

• [ExecuTorch][WebGPU] Convert remaining native tests to GTest #20706
• [ExecuTorch][WebGPU] Use requiredFeatures instance API on native + emscripten Dawn #20652
• ->[ExecuTorch][WebGPU] 2D-fold mul + permute dispatch (lift 65535 1D cap) #20651
• [ExecuTorch][WebGPU] 2D compute dispatch tests — prefill golden + fold unit test #20584
• [ExecuTorch][WebGPU] 2D compute dispatch — lift the 65535 per-dim cap (prefill path) #20583
• [ExecuTorch][WebGPU] Dynamic-shape integration test (allocate-at-max + per-op resize) #20582
• [ExecuTorch][WebGPU] Dynamic resize hook for slice_copy (dynamic start/end) #20581
• [ExecuTorch][WebGPU] Dynamic resize hook for SDPA (live seq-len S) #20580
• [ExecuTorch][WebGPU] Dynamic resize hook for view_copy #20579
• [ExecuTorch][WebGPU] Dynamic resize hooks for sigmoid and select_copy #20578
• [ExecuTorch][WebGPU] Dynamic resize hooks for add and mul #20577
• [ExecuTorch][WebGPU] Dynamic resize hook for linear_q4gsw #20576
• [ExecuTorch][WebGPU] Dynamic resize hooks for rms_norm, embedding, rope #20575
• [ExecuTorch][WebGPU] Dynamic tensor-shape resize engine core #20574
• [ExecuTorch][WebGPU] SymInt arithmetic ops (add/sub/mul/floordiv) for dynamic shapes #20573

Lift the 65535 workgroup-per-dim cap for mul and permute so they run at any numel.

mul.Tensor and permute still used compute_1d_workgroup_count, which throws once numel / wg_size > 65535 — hit by a realistic Llama-3.2-1B LoRA layer (mul over [2048, 8192] = 262k workgroups; permute of [2048, 2048] = 65536). add/sub/div/fill/sdpa already use the 2D fold; this brings mul + permute in line.

Key changes:

• mul/BinaryOp.cpp, permute/Permute.cpp — compute_1d_workgroup_count → compute_2d_workgroup_count (returns utils::WgCount); dispatch + resize hook now set both workgroup_count_x and workgroup_count_y.
• binary_mul.wgsl, permute.wgsl — main takes @builtin(num_workgroups); flat index gid.x + gid.y * (num_workgroups.x * wg_size) (regenerated *_wgsl.h).

Mirrors the landed add op fold (runtime/ops/add/{BinaryOp.cpp,binary_add.wgsl}).

Co-authored-with: Claude Code.
@exported-using-ghexport

Differential Revision: D110149677

Differential Revision: D110149677

[pytorch-bot]

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/20651

• 📄 Preview Python docs built from this PR

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

❌ 1 New Failure

As of commit 91b2d97 with merge base 124b677 ():

NEW FAILURE - The following job has failed:

• pull / test-binary-size-linux-gcc / linux-job (gh)
  RuntimeError: Command docker exec -t 96ee68bc5f25708b763420ba1de31656e58aac15ef00d525a6e68b856280ef0a /exec failed with exit code 1

This comment was automatically generated by Dr. CI and updates every 15 minutes.

[github-actions]

This PR needs a release notes: label

If your change should be included in the release notes (i.e. would users of this library care about this change?), please use a label starting with release notes:. This helps us keep track and include your important work in the next release notes.

To add a label, you can comment to pytorchbot, for example
@pytorchbot label "release notes: none"

For more information, see
https://github.com/pytorch/pytorch/wiki/PyTorch-AutoLabel-Bot#why-categorize-for-release-notes-and-how-does-it-work.

[ghost]

@claude Review thoroughly. Check for stale code / bugs.

[claude]

Claude finished @JulianCloudNTH's task in 2m 47s —— View job

---

Review: WebGPU 2D-fold for mul + permute

• Read PR diff and understand the change
• Compare against the reference add op fold
• Check compute_2d_workgroup_count / WgCount / add_dispatch signatures
• Verify WGSL flat-index math is correct
• Check for stale code / bugs
• Post review

---

Reviewed against the landed add fold (ops/add/{BinaryOp.cpp,binary_add.wgsl}), WebGPUUtils.h (compute_2d_workgroup_count/fold_workgroup_count_2d/WgCount), and the dispatch path in WebGPUGraph.{h,cpp}. The change is correct and a faithful mirror of the reference — no bugs found. One stale comment worth fixing.

✅ Correctness verified

• add_dispatch brace-init matches the struct.WebGPUDispatch field order is {pipeline, bind_group, workgroup_count_x, kernel_name, workgroup_count_y} (WebGPUGraph.h:46-51). Both call sites pass {pipeline, bind_group, workgroup_count.x, "mul"/"permute", workgroup_count.y} — positions line up exactly. add uses "" as the label; mul/permute supplying real bench labels is a minor improvement, not a bug.
• Dispatch consumes .y.WebGPUGraph.cpp:818 and :898 both call wgpuComputePassEncoderDispatchWorkgroups(pass, workgroup_count_x, workgroup_count_y, 1), so the folded y is actually launched.
• Flat-index math is exact.idx = gid.x + gid.y * (num_workgroups.x * wg_size). With grid (x, y, 1) and @workgroup_size(wg_size,1,1): gid.x ∈ [0, x·wg_size), gid.y ∈ [0, y), num_workgroups.x == x, so idx covers [0, x·y·wg_size), and x·y ≥ ceil(numel/wg_size). The idx >= out_meta.numel guard drops the tail. Byte-identical to binary_add.wgsl:17.
• mul resize hook rewrites both workgroup_count_x and workgroup_count_y (BinaryOp.cpp:204-205), matching add:190-191. permute has no resize hook (it registers none), so nothing to update there — consistent with the op being static-shape only.
• num_workgroups builtin is correctly added to both main signatures and both regenerated *_wgsl.h SHAs were updated.

🟡 Minor: stale comment

backends/webgpu/runtime/ops/mul/BinaryOp.cpp:37

// Rank guard (NCHW backend is <= 4 dims; 1D dispatch only).

The 1D dispatch only clause is now inaccurate — dispatch is 2D-folded. Suggest trimming to // Rank guard (NCHW backend is <= 4 dims).permute has no equivalent stale comment. Fix this →

💭 Observations (non-blocking, shared with the landed add)

• gid.y * (num_workgroups.x * wg_size) is u32 arithmetic. In practice bounded by numel (a uint32_t), so no overflow for any realistic tensor; only a theoretical concern as numel → 2³². This is inherited verbatim from the reference add/sdpa fold, so it's not something this PR should change in isolation.
• No test exercises the >65535 path.test_mul.py / test_permute.py exist but I didn't find a case at the numel that previously threw (mul over [2048, 8192], permute of [2048, 2048]). Adding one would lock in the fix and guard against regression — though if the add fold landed without such a case, matching that precedent is reasonable.

Verdict: LGTM. The one stale comment is optional cleanup; the logic is sound and consistent with the established pattern.
· branch gh/JulianCloudNTH/83/head

[ghost]

Stack from ghstack (oldest at bottom):

• [ExecuTorch][WebGPU] Convert remaining native tests to GTest #20706
• [ExecuTorch][WebGPU] Use requiredFeatures instance API on native + emscripten Dawn #20652
• ->[ExecuTorch][WebGPU] 2D-fold mul + permute dispatch (lift 65535 1D cap) #20651
• [ExecuTorch][WebGPU] 2D compute dispatch tests — prefill golden + fold unit test #20584
• [ExecuTorch][WebGPU] 2D compute dispatch — lift the 65535 per-dim cap (prefill path) #20583
• [ExecuTorch][WebGPU] Dynamic-shape integration test (allocate-at-max + per-op resize) #20582
• [ExecuTorch][WebGPU] Dynamic resize hook for slice_copy (dynamic start/end) #20581
• [ExecuTorch][WebGPU] Dynamic resize hook for SDPA (live seq-len S) #20580
• [ExecuTorch][WebGPU] Dynamic resize hook for view_copy #20579
• [ExecuTorch][WebGPU] Dynamic resize hooks for sigmoid and select_copy #20578
• [ExecuTorch][WebGPU] Dynamic resize hooks for add and mul #20577
• [ExecuTorch][WebGPU] Dynamic resize hook for linear_q4gsw #20576
• [ExecuTorch][WebGPU] Dynamic resize hooks for rms_norm, embedding, rope #20575
• [ExecuTorch][WebGPU] Dynamic tensor-shape resize engine core #20574
• [ExecuTorch][WebGPU] SymInt arithmetic ops (add/sub/mul/floordiv) for dynamic shapes #20573

Lift the 65535 workgroup-per-dim cap for mul and permute so they run at any numel.

mul.Tensor and permute still used compute_1d_workgroup_count, which throws once numel / wg_size > 65535 — hit by a realistic Llama-3.2-1B LoRA layer (mul over [2048, 8192] = 262k workgroups; permute of [2048, 2048] = 65536). add/sub/div/fill/sdpa already use the 2D fold; this brings mul + permute in line.

Key changes:

• mul/BinaryOp.cpp, permute/Permute.cpp — compute_1d_workgroup_count → compute_2d_workgroup_count (returns utils::WgCount); dispatch + resize hook now set both workgroup_count_x and workgroup_count_y.
• binary_mul.wgsl, permute.wgsl — main takes @builtin(num_workgroups); flat index gid.x + gid.y * (num_workgroups.x * wg_size) (regenerated *_wgsl.h).

Mirrors the landed add op fold (runtime/ops/add/{BinaryOp.cpp,binary_add.wgsl}).

Co-authored-with: Claude Code.
@exported-using-ghexport

Differential Revision: D110149677

Differential Revision: D110149677

[pytorch-bot]

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/20651

• 📄 Preview Python docs built from this PR

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

❌ 1 New Failure

As of commit 91b2d97 with merge base 124b677 ():

NEW FAILURE - The following job has failed:

• pull / test-binary-size-linux-gcc / linux-job (gh)
  RuntimeError: Command docker exec -t 96ee68bc5f25708b763420ba1de31656e58aac15ef00d525a6e68b856280ef0a /exec failed with exit code 1

This comment was automatically generated by Dr. CI and updates every 15 minutes.

[github-actions]

This PR needs a release notes: label

If your change should be included in the release notes (i.e. would users of this library care about this change?), please use a label starting with release notes:. This helps us keep track and include your important work in the next release notes.

To add a label, you can comment to pytorchbot, for example
@pytorchbot label "release notes: none"

For more information, see
https://github.com/pytorch/pytorch/wiki/PyTorch-AutoLabel-Bot#why-categorize-for-release-notes-and-how-does-it-work.

[ghost]

@claude Review thoroughly. Check for stale code / bugs.

[claude]

Claude finished @JulianCloudNTH's task in 2m 47s —— View job

---

Review: WebGPU 2D-fold for mul + permute

• Read PR diff and understand the change
• Compare against the reference add op fold
• Check compute_2d_workgroup_count / WgCount / add_dispatch signatures
• Verify WGSL flat-index math is correct
• Check for stale code / bugs
• Post review

---

Reviewed against the landed add fold (ops/add/{BinaryOp.cpp,binary_add.wgsl}), WebGPUUtils.h (compute_2d_workgroup_count/fold_workgroup_count_2d/WgCount), and the dispatch path in WebGPUGraph.{h,cpp}. The change is correct and a faithful mirror of the reference — no bugs found. One stale comment worth fixing.

✅ Correctness verified

• add_dispatch brace-init matches the struct.WebGPUDispatch field order is {pipeline, bind_group, workgroup_count_x, kernel_name, workgroup_count_y} (WebGPUGraph.h:46-51). Both call sites pass {pipeline, bind_group, workgroup_count.x, "mul"/"permute", workgroup_count.y} — positions line up exactly. add uses "" as the label; mul/permute supplying real bench labels is a minor improvement, not a bug.
• Dispatch consumes .y.WebGPUGraph.cpp:818 and :898 both call wgpuComputePassEncoderDispatchWorkgroups(pass, workgroup_count_x, workgroup_count_y, 1), so the folded y is actually launched.
• Flat-index math is exact.idx = gid.x + gid.y * (num_workgroups.x * wg_size). With grid (x, y, 1) and @workgroup_size(wg_size,1,1): gid.x ∈ [0, x·wg_size), gid.y ∈ [0, y), num_workgroups.x == x, so idx covers [0, x·y·wg_size), and x·y ≥ ceil(numel/wg_size). The idx >= out_meta.numel guard drops the tail. Byte-identical to binary_add.wgsl:17.
• mul resize hook rewrites both workgroup_count_x and workgroup_count_y (BinaryOp.cpp:204-205), matching add:190-191. permute has no resize hook (it registers none), so nothing to update there — consistent with the op being static-shape only.
• num_workgroups builtin is correctly added to both main signatures and both regenerated *_wgsl.h SHAs were updated.

🟡 Minor: stale comment

backends/webgpu/runtime/ops/mul/BinaryOp.cpp:37

// Rank guard (NCHW backend is <= 4 dims; 1D dispatch only).

The 1D dispatch only clause is now inaccurate — dispatch is 2D-folded. Suggest trimming to // Rank guard (NCHW backend is <= 4 dims).permute has no equivalent stale comment. Fix this →

💭 Observations (non-blocking, shared with the landed add)

• gid.y * (num_workgroups.x * wg_size) is u32 arithmetic. In practice bounded by numel (a uint32_t), so no overflow for any realistic tensor; only a theoretical concern as numel → 2³². This is inherited verbatim from the reference add/sdpa fold, so it's not something this PR should change in isolation.
• No test exercises the >65535 path.test_mul.py / test_permute.py exist but I didn't find a case at the numel that previously threw (mul over [2048, 8192], permute of [2048, 2048]). Adding one would lock in the fix and guard against regression — though if the add fold landed without such a case, matching that precedent is reasonable.

Verdict: LGTM. The one stale comment is optional cleanup; the logic is sound and consistent with the established pattern.
· branch gh/JulianCloudNTH/83/head

[ghost]

Stack from ghstack (oldest at bottom):

• [ExecuTorch][WebGPU] Convert remaining native tests to GTest #20706
• [ExecuTorch][WebGPU] Use requiredFeatures instance API on native + emscripten Dawn #20652
• ->[ExecuTorch][WebGPU] 2D-fold mul + permute dispatch (lift 65535 1D cap) #20651
• [ExecuTorch][WebGPU] 2D compute dispatch tests — prefill golden + fold unit test #20584
• [ExecuTorch][WebGPU] 2D compute dispatch — lift the 65535 per-dim cap (prefill path) #20583
• [ExecuTorch][WebGPU] Dynamic-shape integration test (allocate-at-max + per-op resize) #20582
• [ExecuTorch][WebGPU] Dynamic resize hook for slice_copy (dynamic start/end) #20581
• [ExecuTorch][WebGPU] Dynamic resize hook for SDPA (live seq-len S) #20580
• [ExecuTorch][WebGPU] Dynamic resize hook for view_copy #20579
• [ExecuTorch][WebGPU] Dynamic resize hooks for sigmoid and select_copy #20578
• [ExecuTorch][WebGPU] Dynamic resize hooks for add and mul #20577
• [ExecuTorch][WebGPU] Dynamic resize hook for linear_q4gsw #20576
• [ExecuTorch][WebGPU] Dynamic resize hooks for rms_norm, embedding, rope #20575
• [ExecuTorch][WebGPU] Dynamic tensor-shape resize engine core #20574
• [ExecuTorch][WebGPU] SymInt arithmetic ops (add/sub/mul/floordiv) for dynamic shapes #20573

Lift the 65535 workgroup-per-dim cap for mul and permute so they run at any numel.

mul.Tensor and permute still used compute_1d_workgroup_count, which throws once numel / wg_size > 65535 — hit by a realistic Llama-3.2-1B LoRA layer (mul over [2048, 8192] = 262k workgroups; permute of [2048, 2048] = 65536). add/sub/div/fill/sdpa already use the 2D fold; this brings mul + permute in line.

Key changes:

• mul/BinaryOp.cpp, permute/Permute.cpp — compute_1d_workgroup_count → compute_2d_workgroup_count (returns utils::WgCount); dispatch + resize hook now set both workgroup_count_x and workgroup_count_y.
• binary_mul.wgsl, permute.wgsl — main takes @builtin(num_workgroups); flat index gid.x + gid.y * (num_workgroups.x * wg_size) (regenerated *_wgsl.h).

Mirrors the landed add op fold (runtime/ops/add/{BinaryOp.cpp,binary_add.wgsl}).

Co-authored-with: Claude Code.
@exported-using-ghexport

Differential Revision: D110149677

Differential Revision: D110149677

[pytorch-bot]

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/20651

• 📄 Preview Python docs built from this PR

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

❌ 1 New Failure

As of commit 91b2d97 with merge base 124b677 ():

NEW FAILURE - The following job has failed:

• pull / test-binary-size-linux-gcc / linux-job (gh)
  RuntimeError: Command docker exec -t 96ee68bc5f25708b763420ba1de31656e58aac15ef00d525a6e68b856280ef0a /exec failed with exit code 1

This comment was automatically generated by Dr. CI and updates every 15 minutes.

[github-actions]

This PR needs a release notes: label

If your change should be included in the release notes (i.e. would users of this library care about this change?), please use a label starting with release notes:. This helps us keep track and include your important work in the next release notes.

To add a label, you can comment to pytorchbot, for example
@pytorchbot label "release notes: none"

For more information, see
https://github.com/pytorch/pytorch/wiki/PyTorch-AutoLabel-Bot#why-categorize-for-release-notes-and-how-does-it-work.

[ghost]

@claude Review thoroughly. Check for stale code / bugs.

[claude]

Claude finished @JulianCloudNTH's task in 2m 47s —— View job

---

Review: WebGPU 2D-fold for mul + permute

• Read PR diff and understand the change
• Compare against the reference add op fold
• Check compute_2d_workgroup_count / WgCount / add_dispatch signatures
• Verify WGSL flat-index math is correct
• Check for stale code / bugs
• Post review

---

Reviewed against the landed add fold (ops/add/{BinaryOp.cpp,binary_add.wgsl}), WebGPUUtils.h (compute_2d_workgroup_count/fold_workgroup_count_2d/WgCount), and the dispatch path in WebGPUGraph.{h,cpp}. The change is correct and a faithful mirror of the reference — no bugs found. One stale comment worth fixing.

✅ Correctness verified

• add_dispatch brace-init matches the struct.WebGPUDispatch field order is {pipeline, bind_group, workgroup_count_x, kernel_name, workgroup_count_y} (WebGPUGraph.h:46-51). Both call sites pass {pipeline, bind_group, workgroup_count.x, "mul"/"permute", workgroup_count.y} — positions line up exactly. add uses "" as the label; mul/permute supplying real bench labels is a minor improvement, not a bug.
• Dispatch consumes .y.WebGPUGraph.cpp:818 and :898 both call wgpuComputePassEncoderDispatchWorkgroups(pass, workgroup_count_x, workgroup_count_y, 1), so the folded y is actually launched.
• Flat-index math is exact.idx = gid.x + gid.y * (num_workgroups.x * wg_size). With grid (x, y, 1) and @workgroup_size(wg_size,1,1): gid.x ∈ [0, x·wg_size), gid.y ∈ [0, y), num_workgroups.x == x, so idx covers [0, x·y·wg_size), and x·y ≥ ceil(numel/wg_size). The idx >= out_meta.numel guard drops the tail. Byte-identical to binary_add.wgsl:17.
• mul resize hook rewrites both workgroup_count_x and workgroup_count_y (BinaryOp.cpp:204-205), matching add:190-191. permute has no resize hook (it registers none), so nothing to update there — consistent with the op being static-shape only.
• num_workgroups builtin is correctly added to both main signatures and both regenerated *_wgsl.h SHAs were updated.

🟡 Minor: stale comment

backends/webgpu/runtime/ops/mul/BinaryOp.cpp:37

// Rank guard (NCHW backend is <= 4 dims; 1D dispatch only).

The 1D dispatch only clause is now inaccurate — dispatch is 2D-folded. Suggest trimming to // Rank guard (NCHW backend is <= 4 dims).permute has no equivalent stale comment. Fix this →

💭 Observations (non-blocking, shared with the landed add)

• gid.y * (num_workgroups.x * wg_size) is u32 arithmetic. In practice bounded by numel (a uint32_t), so no overflow for any realistic tensor; only a theoretical concern as numel → 2³². This is inherited verbatim from the reference add/sdpa fold, so it's not something this PR should change in isolation.
• No test exercises the >65535 path.test_mul.py / test_permute.py exist but I didn't find a case at the numel that previously threw (mul over [2048, 8192], permute of [2048, 2048]). Adding one would lock in the fix and guard against regression — though if the add fold landed without such a case, matching that precedent is reasonable.

Verdict: LGTM. The one stale comment is optional cleanup; the logic is sound and consistent with the established pattern.
· branch gh/JulianCloudNTH/83/head

[ghost]

Stack from ghstack (oldest at bottom):

• [ExecuTorch][WebGPU] Convert remaining native tests to GTest #20706
• [ExecuTorch][WebGPU] Use requiredFeatures instance API on native + emscripten Dawn #20652
• ->[ExecuTorch][WebGPU] 2D-fold mul + permute dispatch (lift 65535 1D cap) #20651
• [ExecuTorch][WebGPU] 2D compute dispatch tests — prefill golden + fold unit test #20584
• [ExecuTorch][WebGPU] 2D compute dispatch — lift the 65535 per-dim cap (prefill path) #20583
• [ExecuTorch][WebGPU] Dynamic-shape integration test (allocate-at-max + per-op resize) #20582
• [ExecuTorch][WebGPU] Dynamic resize hook for slice_copy (dynamic start/end) #20581
• [ExecuTorch][WebGPU] Dynamic resize hook for SDPA (live seq-len S) #20580
• [ExecuTorch][WebGPU] Dynamic resize hook for view_copy #20579
• [ExecuTorch][WebGPU] Dynamic resize hooks for sigmoid and select_copy #20578
• [ExecuTorch][WebGPU] Dynamic resize hooks for add and mul #20577
• [ExecuTorch][WebGPU] Dynamic resize hook for linear_q4gsw #20576
• [ExecuTorch][WebGPU] Dynamic resize hooks for rms_norm, embedding, rope #20575
• [ExecuTorch][WebGPU] Dynamic tensor-shape resize engine core #20574
• [ExecuTorch][WebGPU] SymInt arithmetic ops (add/sub/mul/floordiv) for dynamic shapes #20573

Lift the 65535 workgroup-per-dim cap for mul and permute so they run at any numel.

mul.Tensor and permute still used compute_1d_workgroup_count, which throws once numel / wg_size > 65535 — hit by a realistic Llama-3.2-1B LoRA layer (mul over [2048, 8192] = 262k workgroups; permute of [2048, 2048] = 65536). add/sub/div/fill/sdpa already use the 2D fold; this brings mul + permute in line.

Key changes:

• mul/BinaryOp.cpp, permute/Permute.cpp — compute_1d_workgroup_count → compute_2d_workgroup_count (returns utils::WgCount); dispatch + resize hook now set both workgroup_count_x and workgroup_count_y.
• binary_mul.wgsl, permute.wgsl — main takes @builtin(num_workgroups); flat index gid.x + gid.y * (num_workgroups.x * wg_size) (regenerated *_wgsl.h).

Mirrors the landed add op fold (runtime/ops/add/{BinaryOp.cpp,binary_add.wgsl}).

Co-authored-with: Claude Code.
@exported-using-ghexport

Differential Revision: D110149677

Differential Revision: D110149677

[pytorch-bot]

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/20651

• 📄 Preview Python docs built from this PR

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

❌ 1 New Failure

As of commit 91b2d97 with merge base 124b677 ():

NEW FAILURE - The following job has failed:

• pull / test-binary-size-linux-gcc / linux-job (gh)
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[ghost]

@claude Review thoroughly. Check for stale code / bugs.

[claude]

Claude finished @JulianCloudNTH's task in 2m 47s —— View job

---

Review: WebGPU 2D-fold for mul + permute

• Read PR diff and understand the change
• Compare against the reference add op fold
• Check compute_2d_workgroup_count / WgCount / add_dispatch signatures
• Verify WGSL flat-index math is correct
• Check for stale code / bugs
• Post review

---

Reviewed against the landed add fold (ops/add/{BinaryOp.cpp,binary_add.wgsl}), WebGPUUtils.h (compute_2d_workgroup_count/fold_workgroup_count_2d/WgCount), and the dispatch path in WebGPUGraph.{h,cpp}. The change is correct and a faithful mirror of the reference — no bugs found. One stale comment worth fixing.

✅ Correctness verified

• add_dispatch brace-init matches the struct.WebGPUDispatch field order is {pipeline, bind_group, workgroup_count_x, kernel_name, workgroup_count_y} (WebGPUGraph.h:46-51). Both call sites pass {pipeline, bind_group, workgroup_count.x, "mul"/"permute", workgroup_count.y} — positions line up exactly. add uses "" as the label; mul/permute supplying real bench labels is a minor improvement, not a bug.
• Dispatch consumes .y.WebGPUGraph.cpp:818 and :898 both call wgpuComputePassEncoderDispatchWorkgroups(pass, workgroup_count_x, workgroup_count_y, 1), so the folded y is actually launched.
• Flat-index math is exact.idx = gid.x + gid.y * (num_workgroups.x * wg_size). With grid (x, y, 1) and @workgroup_size(wg_size,1,1): gid.x ∈ [0, x·wg_size), gid.y ∈ [0, y), num_workgroups.x == x, so idx covers [0, x·y·wg_size), and x·y ≥ ceil(numel/wg_size). The idx >= out_meta.numel guard drops the tail. Byte-identical to binary_add.wgsl:17.
• mul resize hook rewrites both workgroup_count_x and workgroup_count_y (BinaryOp.cpp:204-205), matching add:190-191. permute has no resize hook (it registers none), so nothing to update there — consistent with the op being static-shape only.
• num_workgroups builtin is correctly added to both main signatures and both regenerated *_wgsl.h SHAs were updated.

🟡 Minor: stale comment

backends/webgpu/runtime/ops/mul/BinaryOp.cpp:37

// Rank guard (NCHW backend is <= 4 dims; 1D dispatch only).

The 1D dispatch only clause is now inaccurate — dispatch is 2D-folded. Suggest trimming to // Rank guard (NCHW backend is <= 4 dims).permute has no equivalent stale comment. Fix this →

💭 Observations (non-blocking, shared with the landed add)

• gid.y * (num_workgroups.x * wg_size) is u32 arithmetic. In practice bounded by numel (a uint32_t), so no overflow for any realistic tensor; only a theoretical concern as numel → 2³². This is inherited verbatim from the reference add/sdpa fold, so it's not something this PR should change in isolation.
• No test exercises the >65535 path.test_mul.py / test_permute.py exist but I didn't find a case at the numel that previously threw (mul over [2048, 8192], permute of [2048, 2048]). Adding one would lock in the fix and guard against regression — though if the add fold landed without such a case, matching that precedent is reasonable.

Verdict: LGTM. The one stale comment is optional cleanup; the logic is sound and consistent with the established pattern.
· branch gh/JulianCloudNTH/83/head