Removing manual unroll in linear shader to improve overall performance.

[trivedivivek]

Summary:

Summary

This diff improves the overall performance of the linear shader by removing manual unrolling in the linear_qcsnw_tiled.glsl file.

The changes include:

• Removing the [[unroll]] directive in the for loop to allow the compiler to automatically unroll the loop, which can lead to better performance.
• Changing the type of mat1 from VEC4_T[TILE_ROWS] to T[TILE_ROWS][4] to better match the access pattern in the loop.

Differential Revision: D84571616

[pytorch-bot]

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/15110

• 📄 Preview Python docs built from this PR

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

❌ 3 New Failures

As of commit 9c3d279 with merge base 45336ce ():

NEW FAILURES - The following jobs have failed:

• pull / test-samsung-models-linux / linux-job (gh)
  RuntimeError: Command docker exec -t 22f63eed7af6375c9c804643bb2424bb10dbf29243b5002e52663a0d0f631404 /exec failed with exit code 1
• pull / unittest-arm-backend-with-no-fvp (test_pytest_models) / linux-job (gh)
  RuntimeError: Command docker exec -t 87c78c5ad5a06c0d3cc244a5ddcb5c3a4b7a965ef999415fa88db248bdc384f8 /exec failed with exit code 1
• Test CUDA Builds / export-voxtral-cuda-artifact / linux-job (gh)
  RuntimeError: Command docker exec -t a21ecc969b00de5dbe7bdae2db49e8285847f345130afad14092c2c8b5f9c58c /exec failed with exit code 2

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

[meta-codesync]

@trivedivivek has exported this pull request. If you are a Meta employee, you can view the originating Diff in D84571616.

[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.