gau-nernst / learn-cudaLinks
Learn CUDA with PyTorch
☆138Updated last week
Alternatives and similar repositories for learn-cuda
Users that are interested in learn-cuda are comparing it to the libraries listed below
Sorting:
- A curated collection of resources, tutorials, and best practices for learning and mastering NVIDIA CUTLASS☆244Updated 7 months ago
- Cataloging released Triton kernels.☆278Updated 3 months ago
- ☆268Updated this week
- ring-attention experiments☆160Updated last year
- Official Problem Sets / Reference Kernels for the GPU MODE Leaderboard!☆177Updated last week
- Fast low-bit matmul kernels in Triton☆413Updated last week
- Small scale distributed training of sequential deep learning models, built on Numpy and MPI.☆153Updated 2 years ago
- A curated list of resources for learning and exploring Triton, OpenAI's programming language for writing efficient GPU code.☆444Updated 9 months ago
- A repository to unravel the language of GPUs, making their kernel conversations easy to understand☆195Updated 6 months ago
- ☆228Updated 11 months ago
- ☆178Updated last year
- Fastest kernels written from scratch☆501Updated 3 months ago
- a minimal cache manager for PagedAttention, on top of llama3.☆127Updated last year
- Applied AI experiments and examples for PyTorch☆311Updated 4 months ago
- Collection of kernels written in Triton language☆173Updated 8 months ago
- Helpful kernel tutorials and examples for tile-based GPU programming☆501Updated this week
- Simple MPI implementation for prototyping or learning☆293Updated 4 months ago
- A bunch of kernels that might make stuff slower 😉☆69Updated this week
- coding CUDA everyday!☆71Updated 2 weeks ago
- PTX-Tutorial Written Purely By AIs (Deep Research of Openai and Claude 3.7)☆66Updated 9 months ago
- Write a fast kernel and run it on Discord. See how you compare against the best!☆64Updated last week
- Learning about CUDA by writing PTX code.☆150Updated last year
- Tritonbench is a collection of PyTorch custom operators with example inputs to measure their performance.☆306Updated this week
- extensible collectives library in triton☆91Updated 8 months ago
- A Quirky Assortment of CuTe Kernels☆724Updated this week
- High-Performance SGEMM on CUDA devices☆114Updated 11 months ago
- Load compute kernels from the Hub☆352Updated last week
- making the official triton tutorials actually comprehensible☆80Updated 4 months ago
- Explore training for quantized models☆25Updated 5 months ago
- Accelerating MoE with IO and Tile-aware Optimizations☆469Updated this week