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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
🚀🚀🚀 This repository lists some awesome public CUDA, cuda-python, cuBLAS, cuDNN, CUTLASS, TensorRT, TensorRT-LLM, Triton, TVM, MLIR, PTX and High Performance Computing (HPC) projects.
| Date | Stars |
|---|---|
| 2026-07-24 | 500 |
| 2026-07-25 | 500 |
| 2026-07-28 | 501 |
| 2026-07-30 | 502 |
| 2026-08-06 | 502 |
Today
— stars today
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growth rate 0.00%/day
# Awesome-CUDA-and-HPC
[](https://github.com/sindresorhus/awesome)
🚀🚀🚀 This repository lists some awesome public [CUDA](https://developer.nvidia.com/cuda-zone), [cuda-python](https://github.com/NVIDIA/cuda-python), [cuBLAS](https://developer.nvidia.com/cublas), [CUTLASS](https://github.com/NVIDIA/cutlass), [cuDNN](https://developer.nvidia.com/cudnn), [NCCL](https://github.com/NVIDIA/nccl), [TensorRT](https://developer.nvidia.com/tensorrt), [TensorRT-LLM](https://github.com/NVIDIA/TensorRT-LLM), [Triton](https://github.com/triton-lang/triton), [TileLang](https://github.com/tile-ai/tilelang), [TVM](https://tvm.apache.org/), [MLIR](https://mlir.llvm.org/), [LLVM](https://llvm.org/), [PTX](https://docs.nvidia.com/cuda/parallel-thread-execution/index.html) and High Performance Computing (HPC) projects.
## Contents
- [Awesome-CUDA-and-HPC](#awesome-cuda-and-hpc)
- [Official Version](#official-version)
- [Awesome List](#awesome-list)
- [Learning Resources](#learning-resources)
- [CUDA Learning](#cuda-learning)
- [TensorRT Learning](#tensorrt-learning)
- [Triton Learning](#triton-learning)
- [TileLang Learning](#tileLang-learning)
- [TVM Learning](#tvm-learning)
- [MLIR Learning](#mlir-learning)
- [LLVM Learning](#llvm-learning)
- [HPC Learning](#hpc-learning)
- [Frameworks](#frameworks)
- [CUDA Frameworks](#cuda-frameworks)
- [GPU Interface](#gpu-interface)
- [CPP Version](#cpp-version)
- [Python version](#python-version)
- [Rust Version](#rust-version)
- [Julia Version](#julia-version)
- [Performance Benchmark](#performance-benchmark)
- [Scientific Computing Framework](#scientific-computing-framework)
- [Attention and Transformer Framework](#attention-and-transformer-framework)
- [Machine Learning Framework](#machine-learning-framework)
- [AI Inference Framework](#ai-inference-framework)
- [LLM Inference and Serving Engine](#llm-inference-and-serving-engine)
- [High Performance Kernel Library](#high-performance-kernel-library)
- [C Implementation](#c-implementation)
- [CPP Implementation](#cpp-implementation)
- [Mojo Implementation](#mojo-implementation)
- [Rust Implementation](#rust-implementation)
- [zig Implementation](#zig-implementation)
- [Go Implementation](#go-implementation)
- [Distributed and Multi-GPU Framework](#distributed-and-multi-gpu-framework)
- [Robotics Framework](#robotics-framework)
- [ZKP and Web3 Framework](#zkp-and-web3-framework)
- [Triton Frameworks](#triton-frameworks)
- [Triton Machine Learning Framework](#triton-machine-learning-framework)
- [Triton High Performance Kernel Library](#triton-high-performance-kernel-library)
- [MLIR Frameworks](#mlir-frameworks)
- [MLIR GPU Programming](#mlir-gpu-programming)
- [MLIR FFI Bindings](#mlir-ffi-bindings)
- [MLIR Machine learning Framework](#mlir-machine-learning-framework)
- [HPC Frameworks](#hpc-frameworks)
- [Applications](#applications)
- [CUDA Applications](#cuda-applications)
- [Image Preprocess](#image-preprocess)
- [Object Detection](#object-detection)
- [Signal Processing](#signal-processing)
- [Mesh Processing](#mesh-processing)
- [Graph Analytics](#graph-analytics)
- [Blogs](#blogs)
- [CUDA and TensorRT Blogs](#cuda-and-tensorrt-blogs)
- [Triton Blogs](#triton-blogs)
- [TVM Blogs](#tvm-blogs)
- [MLIR Blogs](#mlir-blogs)
- [HPC Blogs](#hpc-blogs)
- [Videos](#videos)
- [Interview](#interview)
## Official Version
- [CUDA](https://developer.nvidia.com/cuda-zone) : CUDA is a parallel computing platExcerpt of 133,254 characters
Read on GitHub
45
Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:6337026acbd66a66, topic:gpu, topic:cuda, topic:hpc
matched fp:6337026acbd66a66, topic:llm, topic:llama