[ET-VK][runtime][1/3] Prepare linear shaders for 2D dispatch - #22288
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Pull Request resolved: #22223 Add `dispatch.glslh` with `linear_idx_from_gid()`, which flattens two-dimensional global invocation IDs. Migrate shaders whose global X coordinate represents a linear logical index. Existing one-dimensional dispatch geometry remains unchanged, making this a behavior-neutral preparation for centralized dispatch wrapping. Authored with Codex. ghstack-source-id: 421281480 @exported-using-ghexport Differential Revision: [D117706349](https://our.internmc.facebook.com/intern/diff/D117706349/)
Pull Request resolved: #22224 Introduce `LocalWorkGroup`, `LwgShape`, `GlobalWorkGrid`, and `DispatchGridIntent` in `runtime/vk_api/DispatchGrid`. Remove legacy `WorkgroupSize`. Model local shapes as power-of-two exponents, support fitting against global extents, and validate local dimensions against device limits. Track dispatch intent independently from optional required local workgroup geometry. Authored with Codex. ghstack-source-id: 421281484 @exported-using-ghexport Differential Revision: [D117706351](https://our.internmc.facebook.com/intern/diff/D117706351/)
Pull Request resolved: #22225 Migrate dispatch, prepack, profiling, and workgroup picker interfaces to `GlobalWorkGrid` and `LocalWorkGroup`. Wrap oversized linear grids using device limits and validate final geometry before `vkCmdDispatch`. Carry exact local geometry as `GlobalWorkGrid` metadata. Cooperative and reduction grid pickers set it explicitly, while `pick_required_lwg` validates and returns it. Preserve elongated Conv1d depthwise workgroups where the default shape would regress GPU latency. Add end-to-end oversized linear dispatch coverage. Authored with Codex. ghstack-source-id: 421281492 @exported-using-ghexport Differential Revision: [D117706355](https://our.internmc.facebook.com/intern/diff/D117706355/)
Add batch-aware direct, pointwise, depthwise, and im2col q8ta convolution dispatch. Batched im2col uses an NCHW scratch tensor and batch-strided shader indexing, with conservative groups=1 high-K/small-spatial routing bounded by a 32 MiB scratch cap. Grouped and large-spatial convolutions stay on the direct path. Authored with Codex. Differential Revision: [D117869783](https://our.internmc.facebook.com/intern/diff/D117869783/) ghstack-source-id: 421281491 Pull-Request: #22254
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This PR was created by the merge bot to help merge the original PR into the main branch.
ghstack PR number: #22223 by @SS-JIA
^ Please use this as the source of truth for the PR details, comments, and reviews
ghstack PR base: https://github.com/pytorch/executorch/tree/gh/SS-JIA/603/base
ghstack PR head: https://github.com/pytorch/executorch/tree/gh/SS-JIA/603/head
Merge bot PR base: https://github.com/pytorch/executorch/tree/gh/SS-JIA/602/orig
Merge bot PR head: https://github.com/pytorch/executorch/tree/gh/SS-JIA/603/orig
Differential Revision: D117706349
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