LLM training in simple, raw C/CUDA

A massively parallel, optimal functional runtime in Rust

📚LeetCUDA: Modern CUDA Learn Notes with PyTorch for Beginners🐑, 200+ CUDA Kernels, Tensor Cores, HGEMM, FA-2 MMA.🎉

DeepEP: an efficient expert-parallel communication library

This package contains the original 2012 AlexNet code.

Learn CUDA Programming, published by Packt

This is a series of GPU optimization topics. Here we will introduce how to optimize the CUDA kernel in detail. I will introduce several basic kernel optimizations, including: elementwise, reduce, s…

RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing …

Training materials associated with NVIDIA's CUDA Training Series (www.olcf.ornl.gov/cuda-training-series/)

Source code that accompanies The CUDA Handbook.

Static suckless single batch CUDA-only qwen3-0.6B mini inference engine

CUDA kernel author's tools

High-Performance SGEMM on CUDA devices

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

A curated set of C++ examples for optimization-based elastodynamic contact simulation using CUDA, emphasizing algorithmic convergence, penetration-free, and inversion-free conditions. Designed for …

Code samples for the CUDA tutorial "CUDA and Applications to Task-based Programming"

Neural network from scratch in CUDA/C++