Squeeze-and-Excitation Networks

GPU Accelerated t-SNE for CUDA with Python bindings

cuGraph - RAPIDS Graph Analytics Library

[ARCHIVED] Cooperative primitives for CUDA C++. See https://github.com/NVIDIA/cccl

FlashInfer: Kernel Library for LLM Serving

A CUDA implementation of SIFT for NVidia GPUs (1.2 ms on a GTX 1060)

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 high performance applications.

CUDA Kernel Benchmarking Library

Graphics Processing Units Molecular Dynamics

PopSift is an implementation of the SIFT algorithm in CUDA.

A simple GPU hash table implemented in CUDA using lock free techniques

Several optimization methods of half-precision general matrix multiplication (HGEMM) using tensor core with WMMA API and MMA PTX instruction.

SDK for GPU accelerated genome assembly and analysis

基于《cuda编程-基础与实践》（樊哲勇 著）的cuda学习之路。

GPU-accelerated triangle mesh processing

my own implementation of the WCSPH, DFSPH and PBD fluid solvers using CUDA and C++

cuVS - a library for vector search and clustering on the GPU

Efficient Distributed GPU Programming for Exascale, an SC/ISC Tutorial

an implementation of parallel linear BVH (LBVH) on GPU

CUDA Matrix Factorization Library with Alternating Least Square (ALS)