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TileLang: DSL for High-performance Operators

TileLang is a domain-specific language for high-performance AI kernels that simplifies writing GPU/CPU/accelerator operators.

Overview

TileLang (tile-lang) is a DSL designed for implementing high-performance operators (e.g., GEMM, FlashAttention) on GPUs and CPUs. Built on top of TVM, it provides concise Pythonic syntax and tooling for performance engineering.

Key features

  • Concise DSL and Python API for operator expression and layout annotations.
  • Multi-backend support (CUDA, HIP, CPU) with device-specific optimizations and examples.
  • Comprehensive examples and benchmark suites, including MLA decoding, FlashMLA and dequantize GEMM.

Use cases

  • Implementing and optimizing kernels for deep learning workloads.
  • Performance tuning on cloud GPUs and accelerators (H100, A100, MI300X, etc.).
  • Research and engineering workflows connecting high-level models to low-level, optimized kernels.

Technical details

  • Core implementation uses C++ and Python; relies on TVM for compilation and JIT workflows.
  • Offers source build instructions, pip packages and nightly builds for quick experimentation.
  • Includes benchmark scripts and device-specific examples to reproduce reported performance results.

Comments

TileLang: DSL for High-performance Operators
Resource Info
Author Tile AI
Added Date 2025-10-02
Open Source Since 2024-10-03
Tags
Open Source Framework Benchmark