[webgpu] Optimize AttentionPrepare

[qjia7]

This pull request refactors and streamlines the computation of Q, K, V tensors in the WebGPU BERT Attention operator. The main changes include removing a custom QKV preparation kernel in favor of a more modular approach using a MatMul operation followed by a dedicated split kernel, and generalizing the QKV splitting logic for broader reuse. This improves maintainability, code reuse, and performance since we have done many optimization on MatMul op.

With this change, PrepareQKV becomes 128.88 ms from 751.67 ms in phi4-vision model.

Before

Kernel	Time (ms)	Percentage (%)
Attention|AttentionPrepare	751.67	49.91

After

Kernel	Time (ms)	Percentage (%)
Attention|MatMul	120.87	19.77
Attention|SplitPackedQKV	1.94	0.32

[Copilot]

Pull request overview

This pull request optimizes the AttentionPrepare operation in the WebGPU BERT Attention operator by replacing a custom QKV preparation kernel with a more modular approach using MatMul followed by a dedicated SplitPackedQKV kernel. This refactoring improves performance (from 751.67ms to 128.88ms in phi4-vision model) by leveraging optimized MatMul operations and enhances code maintainability through better separation of concerns and reusability.

Key changes:

• Replaced custom AttentionPrepare kernel with MatMul + SplitPackedQKV approach
• Moved SplitPackedQKV implementation from group_query_attention.cc to attention.cc for broader reuse
• Enhanced SplitPackedQKV with vectorization support and an additional kv_hidden_size parameter

Reviewed changes

Copilot reviewed 5 out of 5 changed files in this pull request and generated 1 comment.

Show a summary per file

File	Description
onnxruntime/contrib_ops/webgpu/bert/group_query_attention.h	Removed SplitPackedQKVProgram class declaration (moved to attention.h)
onnxruntime/contrib_ops/webgpu/bert/group_query_attention.cc	Removed SplitPackedQKV function implementation and updated call site to include new kv_hidden_size parameter
onnxruntime/contrib_ops/webgpu/bert/attention_common.h	Added SplitPackedQKV function declaration for shared use across attention operators
onnxruntime/contrib_ops/webgpu/bert/attention.h	Added SplitPackedQKVProgram class declaration with updated uniform variables including input_size
onnxruntime/contrib_ops/webgpu/bert/attention.cc	Implemented new PrepareQKV using MatMul + SplitPackedQKV, added vectorization support, refactored to create Q/K/V in BSD format first before converting to BNSH for non-flash attention path

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