Best Open Source cuda Libraries
A curated list of the most popular GitHub repositories tagged with cuda. Select any project to visualize its architecture and dive into the codebase using RepoMind's AI engine.
#1vllm-project/vllm
A high-throughput and memory-efficient inference and serving engine for LLMs
#2sgl-project/sglang
SGLang is a high-performance serving framework for large language models and multimodal models.
#3hashcat/hashcat
World's fastest and most advanced password recovery utility
#4NVlabs/instant-ngp
Instant neural graphics primitives: lightning fast NeRF and more
#5kaldi-asr/kaldi
kaldi-asr/kaldi is the official location of the Kaldi project.
#6LMCache/LMCache
LMCache: Supercharge Your LLM with the Fastest KV Cache Layer
#7xlite-dev/LeetCUDA
📚LeetCUDA: Modern CUDA Learn Notes with PyTorch for Beginners🐑, 200+ CUDA Kernels, Tensor Cores, HGEMM, FA-2 MMA.🎉
#8rapidsai/cudf
cuDF - GPU DataFrame Library
#9NVIDIA/cutlass
CUDA Templates and Python DSLs for High-Performance Linear Algebra
#10Oneflow-Inc/oneflow
OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient.
#11replicate/cog
Containers for machine learning
#12NVIDIA/cuda-samples
Samples for CUDA Developers which demonstrates features in CUDA Toolkit
#13catboost/catboost
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
#14flashinfer-ai/flashinfer
FlashInfer: Kernel Library for LLM Serving
#15shader-slang/slang
Making it easier to work with shaders
#16arrayfire/arrayfire
ArrayFire: a general purpose GPU library.
#17harry7557558/spirula-studio
Cross-vendor 3D Gaussian Splatting trainer - video to splat to mesh, Vulkan or CUDA.
#18sgl-project/sglang-omni
SGLang-Omni is a high-performance serving framework for audio models (TTS, ASR) and unified multimodal models.
#19JuliaGPU/CUDA.jl
CUDA programming in Julia.
#20Motphys/UniLab
UniLab: A Heterogeneous Architecture for Robot RL Beyond GPU-Dominant Paradigms
#21professorpalmer/bonsai-ada-surgery
Bonsai 2 27B: 262k context (trained max) on 12 GB, 54 to 97 tok/s decode, 2x prefill, q8_0 KV recipe, grammar tool calls 9/9. Same ternary weights. Windows bundle + receipts.