Designing High-Performance GPU Kernels with TileLang: Tensor-Core GEMM, Fused Softmax, FlashAttention, and Autotuning
TileLang is a high-level Python domain-specific language (DSL) that streamlines the design of high-performance GPU kernels by allowing the compiler to manage complex CUDA details. A recent tutorial illustrates how to implement tiled tensor-core GEMM, fused softmax, and FlashAttention using TileLang, highlighting its ability to handle intricate thread mapping, memory layouts, and instruction generation.
Why it matters: TileLang makes advanced GPU kernel optimizations more accessible by abstracting away low-level programming complexities.
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