Designing High-Performance GPU Kernels with TileLang: Tensor-Core GEMM, Fused Softmax, FlashAttention, and Autotuning
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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.
1Key Takeaways
- 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.
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3Why it matters
Tool launches and updates shape which workflows teams adopt and which vendors gain traction. MarkTechPost reports that explore TileLang, a high-level Python domain-specific language that simplifies the design of high-performance GPU kernels.
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