NVIDIA tutorial demonstrates tile-based GPU programming with cuTile and Triton

A new tutorial explores NVIDIA's TileGym framework by building a practical Colab workflow that adapts to different hardware conditions. The guide probes the CUDA environment to determine if NVIDIA cuTile can run directly, falling back to Triton when standard Colab GPUs lack the required stack.

• The core tile-programming model operates on entire data tiles rather than individual threads, loading them into the kernel for efficient computation.
• The tutorial implements vector addition, fused GELU, row-wise softmax, tiled matrix multiplication, and flash attention using both cuTile and Triton primitives.
• Each implementation is compared against PyTorch for correctness and benchmarked for performance.

The resource serves as a practical guide for understanding tile-based programming concepts across different GPU capabilities.