[LoadStoreOpToLLVM] Transpose 2d load.

[chengjunlu]

To use the transpose 2d block io to load column major matrix from global memory. (The column major matrix here could be generalized to the cases that register layout fast change dim is not same as the fast change dim on global memory.)

The transposing operation is a recursive operation:

To use the transpose 2D block IO to load column major matrix on Xe+:

1. To load the matrix as d32 type matrix from memory with transposed in register.
2. To transpose the 1xNxd32 to (32/m)xNxdm with the bitcast operation.

The code is only implemented for functionality for the layouts with limitations.
It is not best efficient for now.

[Copilot]

Pull Request Overview

This draft PR implements transpose 2D block load functionality to efficiently load column major matrices from global memory on Intel Xe+ GPUs. The implementation introduces a transpose operation when the register layout's fast-changing dimension differs from the memory layout, using d32 type matrices with bitcast operations for the transformation.

• Added support for transpose 2D block IO operations with transpose parameter
• Enhanced block IO tile size calculation to handle transpose scenarios
• Implemented new test coverage for transpose and column major load operations

Reviewed Changes

Copilot reviewed 3 out of 3 changed files in this pull request and generated 8 comments.

File	Description
LoadStoreOpToLLVM.cpp	Major refactoring of 2D block load implementation to support transpose operations and simplified layout handling
tensor-pointer-load-block-2d.mlir	Updated test expectations for new block load configurations and tile sizes
test_block_store.py	Added transpose parameter and column major test cases for block operations