Designing High-Performance GPU Cores with TileLang: Tensor GEMMs, Fused Softmax, FlashAttention, and Auto-Tuning
TileLang is a high-level domain-specific language in Python for simplifying GPU kernel creation. The guide demonstrates step-by-step implementation of complex tasks: tensor GEMMs, fused softmax, and FlashAttention, where the compiler handles low-level CUDA details.
TileLang, a high-level domain-specific language built on Python, has been introduced to simplify the design of high-performance GPU kernels. A tutorial demonstrates step-by-step implementation of complex workloads, including blockwise GEMM tensor computations on tensor cores, fused softmax, and FlashAttention. The compiler automatically handles intricate thread mapping, memory layout, and generation of low-level CUDA instructions, allowing developers to focus on algorithmic logic rather than manual optimization.
Source: MarkTechPost —
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