Radar / AI infrastructure / TileLang
TileLang
Pythonic domain-specific language on top of TVM for writing high-performance GPU/CPU kernels — GEMM, dequant GEMM, FlashAttention, LinearAttention — without hand-writing CUDA.
Why it matters
Three levels of abstraction from pure compute logic down to thread-level primitives, so kernel work goes from weeks of CUDA to Pythonic code with state-of-the-art performance.
What you could build with it
A GPU startup could write custom attention kernels (e.g. FlashAttention variants for a new model architecture) in Pythonic TileLang instead of hand-tuned CUDA, cutting kernel development time from weeks to days.
Does it hold up?
Real adoption evidence: ~7.9k stars, ~2k commits, PyPI distribution, full programming guides and examples; users still need GPU/TVM familiarity to use it well.
Built with TileLang
- TileLang Puzzlesgithub · Interactive puzzle-style tutorials for learning to write TileLang kernels, maintained by the TileLang org.
- tile-ai/tilelang-lspgithub · Language server for TileLang bringing editor support (completions, diagnostics) to the kernel DSL.
Learn more
First spotted on github: source.
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