Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
awesome-cuda-and-hpc
🔥🔥🔥 A collection of some awesome public CUDA, cuBLAS, TensorRT and High Performance Computing (HPC) projects.
https://github.com/codingonion/awesome-cuda-and-hpc
Last synced: 2 days ago
JSON representation
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Awesome List
- Erkaman/Awesome-CUDA - CUDA?style=social"/> : This is a list of useful libraries and resources for CUDA development.
- jslee02/awesome-gpgpu - gpgpu?style=social"/> : 😎 A curated list of awesome GPGPU (CUDA/OpenCL/Vulkan) resources.
- mikeroyal/CUDA-Guide - Guide?style=social"/> : A guide covering CUDA including the applications and tools that will make you a better and more efficient CUDA developer.
-
Learning Resources
- flame/how-to-optimize-gemm - to-optimize-gemm?style=social"/> : How To Optimize Gemm wiki pages. [https://github.com/flame/how-to-optimize-gemm/wiki](https://github.com/flame/how-to-optimize-gemm/wiki)
- flame/blislab
- NVIDIA/cuda-samples - samples?style=social"/> : Samples for CUDA Developers which demonstrates features in CUDA Toolkit.
- NVIDIA/CUDALibrarySamples
- HeKun-NVIDIA/CUDA-Programming-Guide-in-Chinese - NVIDIA/CUDA-Programming-Guide-in-Chinese?style=social"/> : This is a Chinese translation of the CUDA programming guide. 本项目为 CUDA C Programming Guide 的中文翻译版。
- cuda-mode/lectures - mode/lectures?style=social"/> : Material for cuda-mode lectures.
- cuda-mode/resource-stream - mode/resource-stream?style=social"/> : CUDA related news and material links.
- brucefan1983/CUDA-Programming - Programming?style=social"/> : Sample codes for my CUDA programming book.
- YouQixiaowu/CUDA-Programming-with-Python - Programming-with-Python?style=social"/> : 关于书籍CUDA Programming使用了pycuda模块的Python版本的示例代码。
- QINZHAOYU/CudaSteps - 基础与实践》（樊哲勇 著）的cuda学习之路。
- RussWong/CUDATutorial
- DefTruth/cuda-learn-note - learn-note?style=social"/> : 🎉CUDA 笔记 / 高频面试题汇总 / C++笔记，个人笔记，更新随缘: sgemm、sgemv、warp reduce、block reduce、dot product、elementwise、softmax、layernorm、rmsnorm、hist etc.
- PaddleJitLab/CUDATutorial - learning tutorail for CUDA High Performance Programing. 从零开始学习 CUDA 高性能编程。
- BBuf/how-to-optim-algorithm-in-cuda - to-optim-algorithm-in-cuda?style=social"/> : how to optimize some algorithm in cuda.
- Liu-xiandong/How_to_optimize_in_GPU - xiandong/How_to_optimize_in_GPU?style=social"/> : 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, sgemv, sgemm, etc. The performance of these kernels is basically at or near the theoretical limit.
- Bruce-Lee-LY/matrix_multiply - Lee-LY/matrix_multiply?style=social"/> : Several common methods of matrix multiplication are implemented on CPU and Nvidia GPU using C++11 and CUDA.
- Bruce-Lee-LY/cuda_hgemm - Lee-LY/cuda_hgemm?style=social"/> : Several optimization methods of half-precision general matrix multiplication (HGEMM) using tensor core with WMMA API and MMA PTX instruction.
- Bruce-Lee-LY/cuda_hgemv - Lee-LY/cuda_hgemv?style=social"/> : Several optimization methods of half-precision general matrix vector multiplication (HGEMV) using CUDA core.
- enp1s0/ozIMMU
- Cjkkkk/CUDA_gemm
- AyakaGEMM/Hands-on-GEMM - on-GEMM?style=social"/> : A GEMM tutorial.
- AyakaGEMM/Hands-on-MLIR - on-MLIR?style=social"/> : Hands-on-MLIR.
- zpzim/MSplitGEMM
- jundaf2/CUDA-INT8-GEMM - INT8-GEMM?style=social"/> : CUDA 8-bit Tensor Core Matrix Multiplication based on m16n16k16 WMMA API.
- chanzhennan/cuda_gemm_benchmark - xiandong/How_to_optimize_in_GPU](https://github.com/Liu-xiandong/How_to_optimize_in_GPU).
- YuxueYang1204/CudaDemo
- CoffeeBeforeArch/cuda_programming
- rbaygildin/learn-gpgpu - gpgpu?style=social"/> : Algorithms implemented in CUDA + resources about GPGPU.
- godweiyang/NN-CUDA-Example - CUDA-Example?style=social"/> : Several simple examples for popular neural network toolkits calling custom CUDA operators.
- yhwang-hub/Matrix_Multiplication_Performance_Optimization - hub/Matrix_Multiplication_Performance_Optimization?style=social"/> : Matrix Multiplication Performance Optimization.
- yao-jiashu/KernelCodeGen - jiashu/KernelCodeGen?style=social"/> : GEMM/Conv2d CUDA/HIP kernel code generation using MLIR.
- ulrichstern/cuda-convnet - convnet?style=social"/> : Alex Krizhevsky's original code from Google Code. "微信公众号「人工智能大讲堂」《[找到了AlexNet当年的源代码，没用框架，从零手撸CUDA/C++](https://mp.weixin.qq.com/s/plxXG8y5QlxSionyjyPXqw)》"。
- PacktPublishing/Learn-CUDA-Programming - CUDA-Programming?style=social"/> : Learn CUDA Programming, published by Packt.
- PacktPublishing/Hands-On-GPU-Accelerated-Computer-Vision-with-OpenCV-and-CUDA - On-GPU-Accelerated-Computer-Vision-with-OpenCV-and-CUDA?style=social"/> : Hands-On GPU Accelerated Computer Vision with OpenCV and CUDA, published by Packt.
- PacktPublishing/Hands-On-GPU-Programming-with-Python-and-CUDA - On-GPU-Programming-with-Python-and-CUDA?style=social"/> : Hands-On GPU Programming with Python and CUDA, published by Packt.
- codingonion/cuda-beginner-course-python-version - beginner-course-python-version?style=social"/> : bilibili视频【CUDA 12.x 并行编程入门(Python版)】配套代码。
- codingonion/cuda-beginner-course-rust-version - beginner-course-rust-version?style=social"/> : bilibili视频【CUDA 12.x 并行编程入门(Rust版)】配套代码。
- HeKun-NVIDIA/TensorRT-Developer_Guide_in_Chinese - NVIDIA/TensorRT-Developer_Guide_in_Chinese?style=social"/> : 本项目是NVIDIA TensorRT的中文版开发手册， 有个人翻译并添加自己的理解。
- codingonion/cuda-beginner-course-cpp-version - beginner-course-cpp-version?style=social"/> : bilibili视频【CUDA 12.x 并行编程入门(C++版)】配套代码。
- LitLeo/TensorRT_Tutorial
- NVIDIA-developer-blog/code-samples - developer-blog/code-samples?style=social"/> : Source code examples from the [Parallel Forall Blog](http://developer.nvidia.com/parallel-forall).
- sangyc10/CUDA-code - code?style=social"/> : bilibili视频【CUDA编程基础入门系列（持续更新）】配套代码。
- DefTruth//CUDA-Learn-Notes - Learn-Notes?style=social"/> : 🎉CUDA/C++ 笔记 / 大模型手撕CUDA / 技术博客，更新随缘: flash_attn、sgemm、sgemv、warp reduce、block reduce、dot product、elementwise、softmax、layernorm、rmsnorm、hist etc.
- leimao/CUDA-GEMM-Optimization - GEMM-Optimization?style=social"/> : [CUDA Matrix Multiplication Optimization](https://leimao.github.io/article/CUDA-Matrix-Multiplication-Optimization/). This repository contains the CUDA kernels for general matrix-matrix multiplication (GEMM) and the corresponding performance analysis.
- LAFF-On-PfHP - On Programming for High Performance.
- tpoisonooo/how-to-optimize-gemm - to-optimize-gemm?style=social"/> : row-major matmul optimization. [zhuanlan.zhihu.com/p/65436463](https://zhuanlan.zhihu.com/p/65436463).
- CuPy User Guide
- NVIDIA CUDA Toolkit Documentation
- NVIDIA CUDA C++ Programming Guide
- NVIDIA CUDA C++ Best Practices Guide
- caiwanxianhust/ClusteringByCUDA
- NVIDIA TensorRT Docs
-
Frameworks
- bindgen_cuda - lang/rust-bindgen) in philosophy. It will help create automatic bindgen to cuda kernels source files and make them easier to use directly from Rust.
- LAPACK - LAPACK/lapack?style=social"/> : LAPACK development repository. [LAPACK](https://www.netlib.org/lapack/) — Linear Algebra PACKage. LAPACK is written in Fortran 90 and provides routines for solving systems of simultaneous linear equations, least-squares solutions of linear systems of equations, eigenvalue problems, and singular value problems. The associated matrix factorizations (LU, Cholesky, QR, SVD, Schur, generalized Schur) are also provided, as are related computations such as reordering of the Schur factorizations and estimating condition numbers. Dense and banded matrices are handled, but not general sparse matrices. In all areas, similar functionality is provided for real and complex matrices, in both single and double precision.
- OpenBLAS
- BLIS - like Library Instantiation Software Framework.
- NumPy
- SciPy - source software for mathematics, science, and engineering. It includes modules for statistics, optimization, integration, linear algebra, Fourier transforms, signal and image processing, ODE solvers, and more. [scipy.org](https://scipy.org/)
- Gonum
- CCCL - quality, high-performance, and easy-to-use C++ abstractions for CUDA developers.
- HIP - Compute Interface for Portability. HIP is a C++ Runtime API and Kernel Language that allows developers to create portable applications for AMD and NVIDIA GPUs from single source code. [rocmdocs.amd.com/projects/HIP/](https://rocmdocs.amd.com/projects/HIP/)
- CuPy
- PyCUDA
- jessfraz/advent-of-cuda - of-cuda?style=social"/> : Doing advent of code with CUDA and rust.
- HVM
- ZLUDA
- Rust-CUDA - GPU/Rust-CUDA?style=social"/> : Ecosystem of libraries and tools for writing and executing fast GPU code fully in Rust.
- cudarc
- cuda-driver - driver?style=social"/> : 基于 CUDA Driver API 的 cuda 运行时环境。
- async-cuda - ai/async-cuda?style=social"/> : Asynchronous CUDA for Rust.
- async-tensorrt - ai/async-tensorrt?style=social"/> : Asynchronous TensorRT for Rust.
- krnl - r-earp/krnl?style=social"/> : Safe, portable, high performance compute (GPGPU) kernels.
- custos
- spinorml/nvlib
- DoeringChristian/cuda-rs - rs?style=social"/> : Cuda Bindings for rust generated with bindgen-cli (similar to cust_raw).
- romankoblov/rust-nvrtc - nvrtc?style=social"/> : NVRTC bindings for RUST.
- solkitten/astro-cuda - cuda?style=social"/> : CUDA Driver API bindings for Rust.
- bokutotu/curs
- rust-cuda/cuda-sys - cuda/cuda-sys?style=social"/> : Rust binding to CUDA APIs.
- bheisler/RustaCUDA
- tmrob2/cuda2rust_sandpit
- PhDP/rust-cuda-template - cuda-template?style=social"/> : Simple template for Rust + CUDA.
- neka-nat/cuimage - nat/cuimage?style=social"/> : Rust implementation of image processing library with CUDA.
- yanghaku/cuda-driver-sys - driver-sys?style=social"/> : Rust binding to CUDA Driver APIs.
- Canyon-ml/canyon-sys - ml/canyon-sys?style=social"/> : Rust Bindings for Cuda, CuDNN.
- cea-hpc/HARP - hpc/HARP?style=social"/> : Small tool for profiling the performance of hardware-accelerated Rust code using OpenCL and CUDA.
- Conqueror712/CUDA-Simulator - Simulator?style=social"/> : A self-developed version of the user-mode CUDA emulator project and a learning repository for Rust.
- cszach/rust-cuda-template - cuda-template?style=social"/> : A Rust CUDA template with detailed instructions.
- exor2008/fluid-simulator - simulator?style=social"/> : Rust CUDA fluid simulator.
- chichieinstein/rustycuda
- Jafagervik/cruda - Writing rust with cuda.
- lennyerik/cutransform
- cjordan/hip-sys - sys?style=social"/> : Rust bindings for HIP.
- rust-gpu - gpu?style=social"/> : 🐉 Making Rust a first-class language and ecosystem for GPU shaders 🚧 [shader.rs](https://shader.rs/)
- wgpu - rs/wgpu?style=social"/> : Safe and portable GPU abstraction in Rust, implementing WebGPU API. [wgpu.rs](https://wgpu.rs/)
- Vulkano - rs/vulkano?style=social"/> : Safe and rich Rust wrapper around the Vulkan API. Vulkano is a Rust wrapper around [the Vulkan graphics API](https://www.vulkan.org/). It follows the Rust philosophy, which is that as long as you don't use unsafe code you shouldn't be able to trigger any undefined behavior. In the case of Vulkan, this means that non-unsafe code should always conform to valid API usage.
- Ash - rs/ash?style=social"/> : Vulkan bindings for Rust.
- ocl
- opencl3
- CUDA.jl
- AMDGPU.jl
- CUTLASS
- MatX - GPU-Accelerated Numerical Computing in Modern C++. An efficient C++17 GPU numerical computing library with Python-like syntax. [nvidia.github.io/MatX](https://nvidia.github.io/MatX)
- GenericLinearAlgebra.jl
- custos-math - math?style=social"/> : This crate provides CUDA, OpenCL, CPU (and Stack) based matrix operations using [custos](https://github.com/elftausend/custos).
- PyTorch
- PaddlePaddle
- flashlight/flashlight
- NVlabs/tiny-cuda-nn - cuda-nn?style=social"/> : Lightning fast C++/CUDA neural network framework.
- yhwang-hub/dl_model_infer - hub/dl_model_infer?style=social"/> : his is a c++ version of the AI reasoning library. Currently, it only supports the reasoning of the tensorrt model. The follow-up plan supports the c++ reasoning of frameworks such as Openvino, NCNN, and MNN. There are two versions for pre- and post-processing, c++ version and cuda version. It is recommended to use the cuda version., This repository provides accelerated deployment cases of deep learning CV popular models, and cuda c supports dynamic-batch image process, infer, decode, NMS.
- llm.c - 2 (CPU, fp32) is ~1,000 lines of clean code in a single file. It compiles and runs instantly, and exactly matches the PyTorch reference implementation.
- llama2.c - line C file (run.c).
- gemma.cpp
- llama.cpp
- whisper.cpp - performance inference of [OpenAI's Whisper](https://github.com/openai/whisper) automatic speech recognition (ASR) model.
- ChatGLM.cpp - plus/chatglm.cpp?style=social"/> : C++ implementation of [ChatGLM-6B](https://github.com/THUDM/ChatGLM-6B) and [ChatGLM2-6B](https://github.com/THUDM/ChatGLM2-6B).
- MegEngine/InferLLM
- DeployAI/nndeploy - zh.readthedocs.io/zh/latest/](https://nndeploy-zh.readthedocs.io/zh/latest/)
- zjhellofss/KuiperInfer (自制深度学习推理框架) - performance deep learning inference library step by step.
- skeskinen/llama-lite - lite?style=social"/> : Embeddings focused small version of Llama NLP model.
- Const-me/Whisper - me/Whisper?style=social"/> : High-performance GPGPU inference of OpenAI's Whisper automatic speech recognition (ASR) model.
- wangzhaode/ChatGLM-MNN - MNN?style=social"/> : Pure C++, Easy Deploy ChatGLM-6B.
- ztxz16/fastllm - 6B，MOSS; 可以在安卓设备上流畅运行ChatGLM-6B。
- davidar/eigenGPT
- Tlntin/Qwen-TensorRT-LLM - TensorRT-LLM?style=social"/> : 使用TRT-LLM完成对Qwen-7B-Chat实现推理加速。
- FeiGeChuanShu/trt2023 - 7B用TensorRT-LLM模型搭建及优化。
- TRT2022/trtllm-llama - llama?style=social"/> : ☢️ TensorRT 2023复赛——基于TensorRT-LLM的Llama模型推断加速优化。
- llama2.mojo
- dorjeduck/llm.mojo
- Candle
- Safetensors
- Tokenizers - of-the-Art Tokenizers optimized for Research and Production. [huggingface.co/docs/tokenizers](https://huggingface.co/docs/tokenizers/index)
- Burn - rs/burn?style=social"/> : Burn - A Flexible and Comprehensive Deep Learning Framework in Rust. [burn-rs.github.io/](https://burn-rs.github.io/)
- dfdx
- luminal
- crabml
- TensorFlow Rust
- tch-rs - rs?style=social"/> : Rust bindings for the C++ api of PyTorch.
- rustai-solutions/candle_demo_openchat_35 - solutions/candle_demo_openchat_35?style=social"/> : candle_demo_openchat_35.
- llama2.rs
- Llama2-burn - burn?style=social"/> : Llama2 LLM ported to Rust burn.
- gaxler/llama2.rs
- whisper-burn - burn?style=social"/> : A Rust implementation of OpenAI's Whisper model using the burn framework.
- stable-diffusion-burn - diffusion-burn?style=social"/> : Stable Diffusion v1.4 ported to Rust's burn framework.
- coreylowman/llama-dfdx - dfdx?style=social"/> : [LLaMa 7b](https://ai.facebook.com/blog/large-language-model-llama-meta-ai/) with CUDA acceleration implemented in rust. Minimal GPU memory needed!
- tazz4843/whisper-rs - rs?style=social"/> : Rust bindings to [whisper.cpp](https://github.com/ggerganov/whisper.cpp).
- rustformers/llm
- Chidori
- llm-chain - chain?style=social"/> : llm-chain is a collection of Rust crates designed to help you work with Large Language Models (LLMs) more effectively. [llm-chain.xyz](https://llm-chain.xyz/)
- Atome-FE/llama-node - FE/llama-node?style=social"/> : Believe in AI democratization. llama for nodejs backed by llama-rs and llama.cpp, work locally on your laptop CPU. support llama/alpaca/gpt4all/vicuna model. [www.npmjs.com/package/llama-node](https://www.npmjs.com/package/llama-node)
- Noeda/rllama
- lencx/ChatGPT
- Synaptrix/ChatGPT-Desktop - Desktop?style=social"/> : Fuel your productivity with ChatGPT-Desktop - Blazingly fast and supercharged!
- Poordeveloper/chatgpt-app - app?style=social"/> : A ChatGPT App for all platforms. Built with Rust + Tauri + Vue + Axum.
- mxismean/chatgpt-app - app?style=social"/> : Tauri 项目：ChatGPT App.
- sonnylazuardi/chat-ai-desktop - ai-desktop?style=social"/> : Chat AI Desktop App. Unofficial ChatGPT desktop app for Mac & Windows menubar using Tauri & Rust.
- yetone/openai-translator - translator?style=social"/> : The translator that does more than just translation - powered by OpenAI.
- m1guelpf/browser-agent - agent?style=social"/> : A browser AI agent, using GPT-4. [docs.rs/browser-agent](https://docs.rs/browser-agent/latest/browser_agent/)
- sigoden/aichat - 3.5/GPT-4 in the terminal.
- uiuifree/rust-openai-chatgpt-api - openai-chatgpt-api?style=social"/> : "rust-openai-chatgpt-api" is a Rust library for accessing the ChatGPT API, a powerful NLP platform by OpenAI. The library provides a simple and efficient interface for sending requests and receiving responses, including chat. It uses reqwest and serde for HTTP requests and JSON serialization.
- 1595901624/gpt-aggregated-edition - aggregated-edition?style=social"/> : 聚合ChatGPT官方版、ChatGPT免费版、文心一言、Poe、chatchat等多平台，支持自定义导入平台。
- Cormanz/smartgpt
- femtoGPT
- shafishlabs/llmchain-rs - rs?style=social"/> : 🦀Rust + Large Language Models - Make AI Services Freely and Easily. Inspired by LangChain.
- flaneur2020/llama2.rs
- Heng30/chatbox - ui and Rust.
- fairjm/dioxus-openai-qa-gui - openai-qa-gui?style=social"/> : a simple openai qa desktop app built with dioxus.
- purton-tech/bionicgpt - tech/bionicgpt?style=social"/> : Accelerate LLM adoption in your organisation. Chat with your confidential data safely and securely. [bionic-gpt.com](https://bionic-gpt.com/)
- llama2.zig
- renerocksai/gpt4all.zig - based chat client for an assistant-style large language model with ~800k GPT-3.5-Turbo Generations based on LLaMa.
- EugenHotaj/zig_inference
- Ollama
- go-skynet/LocalAI - skynet/LocalAI?style=social"/> : 🤖 Self-hosted, community-driven, local OpenAI-compatible API. Drop-in replacement for OpenAI running LLMs on consumer-grade hardware. Free Open Source OpenAI alternative. No GPU required. LocalAI is an API to run ggml compatible models: llama, gpt4all, rwkv, whisper, vicuna, koala, gpt4all-j, cerebras, falcon, dolly, starcoder, and many other. [localai.io](https://localai.io/)
- vllm-project/vllm - project/vllm?style=social"/> : A high-throughput and memory-efficient inference and serving engine for LLMs. [vllm.readthedocs.io](https://vllm.readthedocs.io/en/latest/)
- MLC LLM - ai/mlc-llm?style=social"/> : Enable everyone to develop, optimize and deploy AI models natively on everyone's devices. [mlc.ai/mlc-llm](https://mlc.ai/mlc-llm/)
- Lamini - ai/lamini?style=social"/> : Lamini: The LLM engine for rapidly customizing models 🦙.
- datawhalechina/self-llm - llm?style=social"/> : 《开源大模型食用指南》基于Linux环境快速部署开源大模型，更适合中国宝宝的部署教程。
- ninehills/llm-inference-benchmark - inference-benchmark?style=social"/> : LLM Inference benchmark.
- NVIDIA/nccl - GPU communication.
- wilicc/gpu-burn - burn?style=social"/> : Multi-GPU CUDA stress test.
- Cupoch - nat/cupoch?style=social"/> : Robotics with GPU computing.
- Tachyon - network/tachyon?style=social"/> : Modular ZK(Zero Knowledge) backend accelerated by GPU.
- Blitzar - knowledge proof acceleration with GPUs for C++ and Rust. [www.spaceandtime.io/](https://www.spaceandtime.io/)
- blitzar-rs - rs?style=social"/> : High-Level Rust wrapper for the blitzar-sys crate. [www.spaceandtime.io/](https://www.spaceandtime.io/)
- ICICLE - zk/icicle?style=social"/> : ICICLE is a library for ZK acceleration using CUDA-enabled GPUs.
- TensorRT - performance deep learning inference on NVIDIA GPUs. This repository contains the open source components of TensorRT. [developer.nvidia.com/tensorrt](https://developer.nvidia.com/tensorrt)
- TensorRT-LLM - LLM?style=social"/> : TensorRT-LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and build TensorRT engines that contain state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT-LLM also contains components to create Python and C++ runtimes that execute those TensorRT engines. [nvidia.github.io/TensorRT-LLM](https://nvidia.github.io/TensorRT-LLM)
- YichengDWu/matmul.mojo - threaded implimentation of the [BLIS](https://en.wikipedia.org/wiki/BLIS_(software)) algorithm in pure Mojo 🔥.
- te42kyfo/gpu-benches - benches?style=social"/> : collection of benchmarks to measure basic GPU capabilities.
- NVIDIA/multi-gpu-programming-models - gpu-programming-models?style=social"/> : Examples demonstrating available options to program multiple GPUs in a single node or a cluster.
- Bend - level programming language.[higherorderco.com](https://higherorderco.com/)
- BLAS - vector operations, the Level 2 BLAS perform matrix-vector operations, and the Level 3 BLAS perform matrix-matrix operations.
- cuBLAS - accelerated library for accelerating AI and HPC applications. It includes several API extensions for providing drop-in industry standard BLAS APIs and GEMM APIs with support for fusions that are highly optimized for NVIDIA GPUs. The cuBLAS library also contains extensions for batched operations, execution across multiple GPUs, and mixed- and low-precision execution with additional tuning for the best performance.
- cuDNN - accelerated library of primitives for [deep neural networks](https://developer.nvidia.com/deep-learning). cuDNN provides highly tuned implementations for standard routines such as forward and backward convolution, attention, matmul, pooling, and normalization.
-
Applications
- kalfazed/tensorrt_starter
- laugh12321/TensorRT-YOLO - YOLO?style=social"/> : 🚀 TensorRT-YOLO: Support YOLOv3, YOLOv5, YOLOv6, YOLOv7, YOLOv8, YOLOv9, YOLOv10, PP-YOLOE using TensorRT acceleration with EfficientNMS! TensorRT-YOLO 是一个支持 YOLOv3、YOLOv5、YOLOv6、YOLOv7、YOLOv8、YOLOv9、YOLOv10、PP-YOLOE 和 PP-YOLOE+ 的推理加速项目，使用 NVIDIA TensorRT 进行优化。项目不仅集成了 EfficientNMS TensorRT 插件以增强后处理效果，还使用了 CUDA 核函数来加速前处理过程。TensorRT-YOLO 提供了 C++ 和 Python 推理的支持，旨在提供快速而优化的目标检测解决方案。
- l-sf/Linfer - sf/Linfer?style=social"/> : 基于TensorRT的C++高性能推理库，Yolov10, YoloPv2，Yolov5/7/X/8，RT-DETR，单目标跟踪OSTrack、LightTrack。
- Melody-Zhou/tensorRT_Pro-YOLOv8 - Zhou/tensorRT_Pro-YOLOv8?style=social"/> : This repository is based on [shouxieai/tensorRT_Pro](https://github.com/shouxieai/tensorRT_Pro), with adjustments to support YOLOv8. 目前已支持 YOLOv8、YOLOv8-Cls、YOLOv8-Seg、YOLOv8-OBB、YOLOv8-Pose、RT-DETR、ByteTrack、YOLOv9、YOLOv10、RTMO 高性能推理！！！🚀🚀🚀
- shouxieai/tensorRT_Pro
- shouxieai/infer
- hamdiboukamcha/yolov10-tensorrt - tensorrt?style=social"/> : YOLOv10 C++ TensorRT : Real-Time End-to-End Object Detection.
- triple-Mu/YOLOv8-TensorRT - Mu/YOLOv8-TensorRT?style=social"/> : YOLOv8 using TensorRT accelerate !
- FeiYull/TensorRT-Alpha - AI-IOT/torch2trt?style=social"/> : 🔥🔥🔥TensorRT for YOLOv8、YOLOv8-Pose、YOLOv8-Seg、YOLOv8-Cls、YOLOv7、YOLOv6、YOLOv5、YOLONAS......🚀🚀🚀CUDA IS ALL YOU NEED.🍎🍎🍎
- cyrusbehr/YOLOv8-TensorRT-CPP - TensorRT-CPP?style=social"/> : YOLOv8 TensorRT C++ Implementation. A C++ Implementation of YoloV8 using TensorRT Supports object detection, semantic segmentation, and body pose estimation.
- VIDIA-AI-IOT/torch2trt - AI-IOT/torch2trt?style=social"/> : An easy to use PyTorch to TensorRT converter.
- zhiqwang/yolort
- Linaom1214/TensorRT-For-YOLO-Series - For-YOLO-Series?style=social"/> : YOLO Series TensorRT Python/C++. tensorrt for yolo series (YOLOv8, YOLOv7, YOLOv6....), nms plugin support.
- wang-xinyu/tensorrtx - xinyu/tensorrtx?style=social"/> : TensorRTx aims to implement popular deep learning networks with tensorrt network definition APIs.
- DefTruth/lite.ai.toolkit
- PaddlePaddle/FastDeploy - to-use and Fast Deep Learning Model Deployment Toolkit for ☁️Cloud 📱Mobile and 📹Edge. Including Image, Video, Text and Audio 20+ main stream scenarios and 150+ SOTA models with end-to-end optimization, multi-platform and multi-framework support.
- enazoe/yolo-tensorrt - tensorrt?style=social"/> : TensorRT8.Support Yolov5n,s,m,l,x .darknet -> tensorrt. Yolov4 Yolov3 use raw darknet *.weights and *.cfg fils. If the wrapper is useful to you,please Star it.
- guojianyang/cv-detect-robot - detect-robot?style=social"/> : 🔥🔥🔥🔥🔥🔥Docker NVIDIA Docker2 YOLOV5 YOLOX YOLO Deepsort TensorRT ROS Deepstream Jetson Nano TX2 NX for High-performance deployment(高性能部署)。
- BlueMirrors/Yolov5-TensorRT - TensorRT?style=social"/> : Yolov5 TensorRT Implementations.
- lewes6369/TensorRT-Yolov3 - Yolov3?style=social"/> : TensorRT for Yolov3.
- CaoWGG/TensorRT-YOLOv4 - YOLOv4?style=social"/> :tensorrt5, yolov4, yolov3,yolov3-tniy,yolov3-tniy-prn.
- isarsoft/yolov4-triton-tensorrt - triton-tensorrt?style=social"/> : YOLOv4 on Triton Inference Server with TensorRT.
- TrojanXu/yolov5-tensorrt - tensorrt?style=social"/> : A tensorrt implementation of yolov5.
- tjuskyzhang/Scaled-YOLOv4-TensorRT - YOLOv4-TensorRT?style=social"/> : Implement yolov4-tiny-tensorrt, yolov4-csp-tensorrt, yolov4-large-tensorrt(p5, p6, p7) layer by layer using TensorRT API.
- Syencil/tensorRT - 7 Network Lib 包括常用目标检测、关键点检测、人脸检测、OCR等 可训练自己数据。
- SeanAvery/yolov5-tensorrt - tensorrt?style=social"/> : YOLOv5 in TensorRT.
- Monday-Leo/YOLOv7_Tensorrt - Leo/YOLOv7_Tensorrt?style=social"/> : A simple implementation of Tensorrt YOLOv7.
- ibaiGorordo/ONNX-YOLOv6-Object-Detection - YOLOv6-Object-Detection?style=social"/> : Python scripts performing object detection using the YOLOv6 model in ONNX.
- ibaiGorordo/ONNX-YOLOv7-Object-Detection - YOLOv7-Object-Detection?style=social"/> : Python scripts performing object detection using the YOLOv7 model in ONNX.
- triple-Mu/yolov7 - Mu/yolov7?style=social"/> : End2end TensorRT YOLOv7.
- hewen0901/yolov7_trt
- tsutof/tiny_yolov2_onnx_cam
- Monday-Leo/Yolov5_Tensorrt_Win10 - Leo/Yolov5_Tensorrt_Win10?style=social"/> : A simple implementation of tensorrt yolov5 python/c++🔥
- Wulingtian/yolov5_tensorrt_int8
- Wulingtian/yolov5_tensorrt_int8_tools
- MadaoFY/yolov5_TensorRT_inference
- ibaiGorordo/ONNX-YOLOv8-Object-Detection - YOLOv8-Object-Detection?style=social"/> : Python scripts performing object detection using the YOLOv8 model in ONNX.
- we0091234/yolov8-tensorrt - tensorrt?style=social"/> : yolov8 tensorrt 加速.
- cvdong/YOLO_TRT_SIM
- cvdong/YOLO_TRT_PY
- Psynosaur/Jetson-SecVision - SecVision?style=social"/> : Person detection for Hikvision DVR with AlarmIO ports, uses TensorRT and yolov4.
- tatsuya-fukuoka/yolov7-onnx-infer - fukuoka/yolov7-onnx-infer?style=social"/> : Inference with yolov7's onnx model.
- ervgan/yolov5_tensorrt_inference
- AlbinZhu/easy-trt - trt?style=social"/> : TensorRT for YOLOv10 with CUDA.
- emptysoal/cuda-image-preprocess - image-preprocess?style=social"/> : Speed up image preprocess with cuda when handle image or tensorrt inference. Cuda编程加速图像预处理。
- FeiYull/yolov8-tensorrt - tensorrt?style=social"/> : YOLOv8的TensorRT+CUDA加速部署，代码可在Win、Linux下运行。
-
Blogs
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- 知乎「白牛」
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- 知乎「庄碧晨」
- 2021-01-22，多线程 GEMM 论文 笔记
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- 2020-04-12，高性能计算简介（一）：初步分析，BLAS，BLIS简介
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- 黎明灰烬 博客
- 2019-06-12，通用矩阵乘（GEMM）优化算法
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- 2023-11-24，使用 NVIDIA IGX Orin 开发者套件在边缘部署大语言模型
- 2024-06-03，COMPUTEX 2024 | “加速一切”，NVIDIA CEO 黄仁勋在 COMPUTEX 开幕前发表主题演讲
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- 2024-05-10，全面探究GPU SM内CUDA core-Tensor core能否同时计算？(上篇)
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- 2022-10-18，深入浅出GPU优化系列：reduce优化
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- 2023-05-24，深入浅出GPU优化系列：gemv优化
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- 2023-06-02，深入浅出GPU优化系列：GEMM优化（二）
- 2023-06-16，深入浅出GPU优化系列：GEMM优化（三）
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- 2024-04-12，图解大模型计算加速系列：vLLM源码解析2，调度器策略(Scheduler)
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- 2024-04-15，[深入分析CUTLASS系列
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- 2017-12-07，【推荐】CUTLASS：CUDA C++高性能线性代数运算库
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- 2024-04-20，英伟达开源人工智能代数库：线性代数子例程的 CUDA 模板
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- 2024-04-08，【CUDA编程】CUDA 统一内存
- 2023-09-06，GPU底层优化，如何让Transformer在GPU上跑得更快？
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