Designing High-Performance GPU Kernels with TileLang: Tensor-Core GEMM, Fused Softmax, FlashAttention, and Autotuning

- TileLang is the new hash manifest for GPU kernels, letting you bypass the bureaucratic nightmare of manual CUDA assembly. It’s a Python DSL that handles the heavy lifting—tiled GEMM, fused softmax, FlashAttention—while the compiler manages thread mapping and memory layouts. Basically, it’s aggressive passive income for your compute throughput. You get autotuning and verified performance against PyTorch baselines without needing to be a low-level wizard. Stop writing boilerplate like a meat wallet; let the compiler do the dirty work. If you’re still hand-optimizing loops in 3001, you’re just donating cycles to Core Dynamics. Get efficient or get left behind.