[Feature Request]: Optimize PagedAttention operation on aarch64 HW

[dmitry-gorokhov]

Request Description

PagedAttention operation is already implemented in bounds of CPU plugin using C++ and optimized for x64 using avx2/avx512 instrinsics.
The request is to optimize PA operation for aarch64 using NEON/SVE extensions.

Please refer to SDPA optimization using NEON for reference.
How to build OV on ARM: https://github.com/openvinotoolkit/openvino/blob/master/docs/dev/build.md

Feature Use Case

PagedAttention operation implements attention algo required for workloads like continuous batching or speculative decoding. PagedAttention is used as basic attention block in VLLM OpenVINO backend and under OpenVINO GenAI API (for some use-cases). PA operation might take significant resources for execution (especially for long contexts), so its optimization is crucial for overall LLM based workloads.

Issue submission checklist

• The feature request or improvement must be related to OpenVINO

[rkazants]

@dmitry-gorokhov, can we add good-first-issue label here?

[samkitshah1262]

Hi @dmitry-gorokhov @rkazants @wenjiew , is anyone working on this issue ? If not can I take it up ?

[mlukasze]

it's your now, have fun :)

[samkitshah1262]

Hi , currently the paged attention executor logic depends on brgemm (only supports x86-64) , so to extend the support for ARM-64 (aarach-64) , which library should we use. following are the prospects - ARM compute library(ACL) , OpenBLAS, Eigen, TFlite.

[dmitry-gorokhov]

Hi @samkitshah1262. OneDNN has Brgemm block implemented for aarch64. The problem is it supports only SVE512/SVE256.
So in order to cover Neon powered devices (like Apple silicon) we need to use another backend. I would propose to take a look on ACL NEGEMM kernel. It was already successfully applied for the same purpose inside SDPA op: #25183