cuda-kernels

Samples for CUDA Developers which demonstrates features in CUDA Toolkit

LMDeploy is a toolkit for compressing, deploying, and serving LLMs.

Ecosystem of libraries and tools for writing and executing fast GPU code fully in Rust.

📚Modern CUDA Learn Notes: 200+ Tensor/CUDA Cores Kernels🎉, HGEMM, FA2 via MMA and CuTe, 98~100% TFLOPS of cuBLAS/FA2.

Deep learning in Rust, with shape checked tensors and neural networks

CUDA Core Compute Libraries

Safe rust wrapper around CUDA toolkit

CUDA Kernel Benchmarking Library

Simple utilities to enable code reuse and portability between CUDA C/C++ and standard C/C++.

Kernel Tuner

This is an archive of materials produced for an introductory class on CUDA programming at Stanford University in 2010

Zero to Hero GPU and CUDA for Maths & ML tutorials with examples.

Amplifier allows .NET developers to easily run complex applications with intensive mathematical computation on Intel CPU/GPU, NVIDIA, AMD without writing any additional C kernel code. Write your function in .NET and Amplifier will take care of running it on your favorite hardware.

Some CUDA design patterns and a bit of template magic for CUDA

Spiking Neural Networks in C++ with strong GPU acceleration through CUDA

CUDA kernel author's tools

Open source cross-platform compiler for compute-intensive loops used in AI algorithms, from Microsoft Research

Triton implementation of FlashAttention2 that adds Custom Masks.

High-speed GEMV kernels, at most 2.7x speedup compared to pytorch baseline.

TileFusion is an experimental C++ macro kernel template library that elevates the abstraction level in CUDA C for tile processing.