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DeepSeek open-sources TileKernels GPU library
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YT · YOUTUBE// 7h agoOPENSOURCE RELEASE

DeepSeek open-sources TileKernels GPU library

DeepSeek's TileKernels is a library of high-performance GPU operators for LLM training and inference, written in the Python-based TileLang DSL. It features production-ready kernels for MoE routing, multi-precision quantization, and MLA, specifically optimized for NVIDIA Hopper and Blackwell architectures.

// ANALYSIS

DeepSeek is systematically replacing the traditional CUDA C++ and Triton stack with their own automated compiler DSL to achieve hardware-limit performance.

  • TileLang allows DeepSeek to implement complex kernels like MLA in ~80 lines of Python while matching the speed of thousands of lines of CUTLASS C++.
  • The library provides first-class support for FP4 and FP8 quantization, signaling a shift towards aggressive multi-precision training on next-gen hardware.
  • By open-sourcing these internal kernels, DeepSeek is positioning TileLang as a serious competitor to OpenAI's Triton for custom GPU operator development.
  • The focus on Hopper (SM90) and Blackwell (SM100) indicates these kernels are built for the absolute cutting edge of AI infrastructure.
// TAGS
gputilelangdeepseekllmopen-sourceinfrastructurecudahopperblackwell

DISCOVERED

7h ago

2026-04-24

PUBLISHED

7h ago

2026-04-24

RELEVANCE

9/ 10

AUTHOR

Github Awesome