想写GPU内核但被CUDA细节劝退？TileLang用Python帮你搞定Tensor-Core GEMM和FlashAttention，自动处理线程映射和调优，省心。
TileLang是一种高级Python领域特定语言，用于简化高性能GPU内核设计。教程演示如何实现分块Tensor-Core GEMM、融合Softmax和FlashAttention等复杂工作负载。TileLang编译器自动处理线程映射、内存布局和底层CUDA指令生成。同时支持自动调优，帮助用户优化内核性能。
Designing High-Performance GPU Kernels with TileLang: Tensor-Core GEMM, Fused Softmax, FlashAttention, and Autotuning
Explore TileLang, a high-level Python domain-specific language that simplifies the design of high-performance GPU kernels. This tutorial provides a step-by-step approach to implementing complex workloads—including tiled tensor-core GEMM, fused softmax, and FlashAttention—while letting the compiler handle intricate thread mapping, memory layouts, and low-level CUDA instruction generation. The post Designing High-Performance GPU Kernels with TileLang: Tensor-Core GEMM, Fused Softmax, FlashAttention, and Autotuning appeared first on MarkTechPost .