Add XMMatrixInverseTranspose for optimal normal vector transformation

[RohithPariki]

Fixes #9

Description

This PR introduces XMMatrixInverseTranspose, computing (M^-1)^T in a single pass. This is a common operation used for transforming surface normals, where developers previously had to chain XMMatrixTranspose(XMMatrixInverse(nullptr, M)).

Optimization Insight:
The standard XMMatrixInverse internally transposes the matrix first (MT = M^T) and then computes the cofactors of MT to produce adj(M^T) = adj(M)^T. Since the caller ultimately requests the transpose of the inverse, that final transpose cancels out the internal one.

XMMatrixInverseTranspose simply runs the cofactor algorithm directly on M (skipping the initial transpose block entirely) to produce adj(M) / det(M).

Savings:

• Eliminates ~12 redundant _mm_shuffle_ps instructions on the _XM_SSE_INTRINSICS_ path.
• Removes the initial matrix transpose on the scalar and NEON paths.

Verification

All paths (Scalar, NEON, and SSE) were successfully implemented and verified against chained calls (Transpose(Inverse(M))) for:

• Identity Matrices
• Pure Rotation Matrices (invT(R) == R)
• Scaling Matrices
• Arbitrary non-degenerate matrices (ensuring matrix values and determinant outputs match perfectly)
  i can share the test code , if needed.

[azure-pipelines]

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