[CUDA] Implement BlockMaskedMM

[Lyxot]

Proposed changes

Implement mx.block_masked_mm for the CUDA backend

Performance

Compared against naive MLX expand + matmul

float32:

Case (MxNxKxBS)	Sparsity	MLX ms	Naive ms	Speedup
256x256x256x32	50%	0.036	0.060	1.65x
512x512x512x32	50%	0.053	0.076	1.43x
1024x1024x1024x32	50%	0.141	0.169	1.20x
2048x2048x2048x64	50%	0.751	1.040	1.38x
4096x4096x4096x32	50%	4.510	5.860	1.30x
8192x8192x8192x64	50%	30.916	36.695	1.19x
4096x4096x11008x32	50%	11.290	14.249	1.26x

float16:

Case (MxNxKxBS)	Sparsity	MLX ms	Naive ms	Speedup
256x256x256x32	50%	0.037	0.056	1.52x
512x512x512x32	50%	0.043	0.066	1.52x
1024x1024x1024x32	50%	0.097	0.106	1.09x
2048x2048x2048x64	50%	0.387	0.443	1.14x
4096x4096x4096x32	50%	2.359	2.992	1.27x
8192x8192x8192x64	50%	16.493	19.072	1.16x

Checklist

Put an x in the boxes that apply.

• I have read the CONTRIBUTING document
• I have run pre-commit run --all-files to format my code / installed pre-commit prior to committing changes
• I have added tests that prove my fix is effective or that my feature works

[Copilot]

Pull request overview

This PR implements the mx.block_masked_mm primitive for the CUDA backend, enabling block/tile-masked matrix multiplication on NVIDIA GPUs and unskipping the corresponding CUDA tests.

Changes:

• Add CUDA BlockMaskedMM::eval_gpu implementation wired into the CUDA matmul path.
• Introduce CUDA kernels/helpers to apply and fuse-copy block masks (apply_block_mask, copy_with_block_mask).
• Enable CUDA CI coverage for test_block_masked_matmul and add a Python benchmark script.

Reviewed changes

Copilot reviewed 7 out of 7 changed files in this pull request and generated 2 comments.

Show a summary per file

File	Description
python/tests/cuda_skip.py	Unskips the block-masked matmul test on CUDA.
mlx/backend/cuda/primitives.cpp	Removes the “no CUDA implementation” stub for BlockMaskedMM.
mlx/backend/cuda/matmul.cpp	Adds BlockMaskedMM::eval_gpu and integrates mask-copy/mask-apply around GEMM.
mlx/backend/cuda/gemms/block_mask.h	Declares CUDA block-mask helper APIs.
mlx/backend/cuda/gemms/block_mask.cu	Implements CUDA kernels for masked copy and in-place output masking.
mlx/backend/cuda/CMakeLists.txt	Adds gemms/block_mask.cu to the CUDA build.
benchmarks/python/block_masked_mm_bench.py	Adds a benchmark + optional correctness check vs naive expand+matmul.

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[zcbenz]

Looks good to me, thanks!