Suggestion: Add roofline/arithmetic-intensity analysis to matrixMul samples

[ragulk143]

The matrixMul and matrixMulCUBLAS samples report GFLOPS and execution time, and matrixMulCUBLAS already compares a custom kernel against cuBLAS — both genuinely useful for learners.

Suggestion: extend these (or add a companion sample) that additionally:

1. Implements the same GEMM at multiple optimization stages — naive, shared-memory tiled, and Tensor Core (WMMA) — so learners see the actual performance delta between each technique, not just a single implementation.
2. Reports arithmetic intensity (FLOPs/byte) alongside achieved GFLOPS, plotted against the GPU's roofline (peak compute vs peak memory bandwidth), so learners can see whether their kernel is memory-bound or compute-bound.

I built a small reference implementation exploring this for my own learning, benchmarked on an RTX 3050: https://github.com/ragulk143/cuda-gemm

Happy to contribute a PR along these lines if this is something the maintainers would find valuable for the samples repo.