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[ET-VK][sdpa] Reuse shared V cache across GQA query heads in AV coop-GEMV#21117

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Jul 22, 2026
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[ET-VK][sdpa] Reuse shared V cache across GQA query heads in AV coop-GEMV#21117
SS-JIA merged 2 commits into
gh/SS-JIA/575/origfrom
gh/SS-JIA/576/orig

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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: #21063 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/576/base
ghstack PR head: https://github.com/pytorch/executorch/tree/gh/SS-JIA/576/head
Merge bot PR base: https://github.com/pytorch/executorch/tree/gh/SS-JIA/575/orig
Merge bot PR head: https://github.com/pytorch/executorch/tree/gh/SS-JIA/576/orig
Differential Revision: D112906311
@diff-train-skip-merge

…GEMV

Pull Request resolved: #21063

The LLM decode AV coop-GEMV reloads the shared V cache once per query head. In
grouped-query attention Hq = G * Hkv query heads share each KV head (Llama G=4,
Phi G=3, Qwen G=2), and out[q_h, d] = sum_c attn[c, q_h] * V[c, kv_h, d] reads
the SAME V texel for every query head in a group. The per-query-head coop shader
gives each of the Hq heads its own workgroup, so V -- the dominant traffic
(head_dim-wide per context texel, vs a scalar attn weight) -- is read G times.

This adds a GQA-reuse AV variant that assigns ONE workgroup per (d4, kv_h): it
loads each V texel once and reuses it across all G query heads in the group,
producing G output texels. For this bandwidth-bound kernel that cuts V-cache
traffic ~Gx.

Implementation:
- The variant is a codegen flag (`GQA`) on the existing
  `sdpa_compute_out_coop.glsl` template, not a separate file: one shared header
  plus two `#ifdef GQA` `main()`s (per-head and GQA-reuse), so the shared setup
  lives in one place while each algorithm reads end-to-end. It emits the shader
  `sdpa_compute_out_gqa_coop`.
- Reduction reuses the per-head coop shader's shared-memory tree reduction (no
  subgroup arithmetic), so the variant runs on any Vulkan device -- Adreno and
  Mali alike -- with no capability gate.
- Each thread holds G output accumulators; the array is sized to a compile-time
  `MAX_GROUP_SIZE` = 8 and the group loop is bounded by the `group_size` =
  Hq/Hkv spec constant, so the driver fully unrolls it at pipeline creation.
- Dispatch (`pick_sdpa_av_shader` + global-wg picker + spec-const wiring in
  `add_sdpa_compute_out_node`): the GQA variant is selected on the LLM decode
  coop path when Hq > Hkv, evenly divisible, and G <= 8 (`use_gqa_av_coop`); it
  sets `group_size` and changes the global workgroup z-dim from Hq to Hkv.
  Everything else -- MHA (Hq == Hkv), groups exceeding the cap (G > 8, e.g. MQA
  with Hq > 8), and non-divisible shapes -- falls back to the unchanged per-head
  `sdpa_compute_out_coop`. (Low-ratio MQA -- Hkv == 1 with Hq <= 8 -- is
  eligible and takes the GQA path.)
- A test-only `gqa_override` knob is threaded through `add_sdpa_compute_out_node`
  (declared in the new `SDPA.h`): -1 auto-select, 0 force per-head, 1 force GQA,
  so a benchmark can exercise both AV shaders on the same shape; forcing GQA is
  VK_CHECK'd against shape eligibility.
ghstack-source-id: 405400503
@exported-using-ghexport

Differential Revision: [D112906311](https://our.internmc.facebook.com/intern/diff/D112906311/)
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pytorchbot requested a review from SS-JIA as a code owner July 22, 2026 02:35
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🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/21117

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@meta-cla meta-cla Bot added the CLA Signed This label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed. label Jul 22, 2026
…QA AV coop-GEMV

Pull Request resolved: #21064

Builds on the GQA-reuse AV coop-GEMV (parent commit). The base
`sdpa_compute_out_gqa_coop` shader assigns one head_dim texel (TILE_N4=1) per
workgroup x-slot. This adds a head_dim output-tiled variant,
`sdpa_compute_out_gqa_coop_tile2` (TILE_N4=2): each workgroup owns 2 head_dim
texels and emits G x TILE_N4 outputs, so the per-context-texel attn-weight loads
and the shared-memory tree reduction are amortized over twice as many outputs.
The AV coop GEMV GLSL is already a TILE_N4-parameterized template (the
`partial_n_tile` uniform branch handles the D4 % TILE_N4 != 0 tail), so this
change is purely a new codegen variant plus dispatch wiring — no shader-body
change.

Selection is vendor-adaptive: `pick_sdpa_av_shader` appends the `_tile2` suffix
only on Adreno (`graph->device_is_adreno()`). Tiling is a consistent win on
Adreno (AV ~1.14-1.63x over the base GQA variant) but a regression on Mali at
common decode contexts (~0.67-0.86x, interleaved median-of-N), so Mali and other
vendors keep the base `sdpa_compute_out_gqa_coop`.
`pick_sdpa_av_global_wg_size` keys off the same `_tile2` suffix: the tiled
variant's x-dim collapses from D4 to div_up(D4, 2) since each workgroup now
covers 2 head_dim texels.

Because the variant is Adreno-only in production, the test-only `gqa_override`
knob (see SDPA.h) is extended so tests can pin the variant on any device:
`kGqaOverrideForceTile2` / `kGqaOverrideForceBase` force the tiled / base
variant regardless of vendor (via `resolve_use_tile2`), giving the tiled shader
deterministic coverage on Mali / SwiftShader. `resolve_use_gqa` is unchanged
(any non-`ForceNonGqa` value still forces the GQA family, VK_CHECK'd for
eligibility).
ghstack-source-id: 405400514
@exported-using-ghexport

Differential Revision: [D112906313](https://our.internmc.facebook.com/intern/diff/D112906313/)
@SS-JIA
SS-JIA merged commit 1f3cabb into gh/SS-JIA/575/orig Jul 22, 2026
58 of 59 checks passed
@SS-JIA
SS-JIA deleted the gh/SS-JIA/576/orig branch July 22, 2026 03:49
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