403 Open source projects that are alternatives of or similar to Learn Cuda Programming

A fast (?) random sampling drawing library

Docker scripts for building ONNX Runtime with TensorRT and OpenVINO in manylinux environment

continuous energy monte carlo neutron transport in general geometries on GPUs

GPU-accelerated data science and visualization in node

Script to remotely check GPU servers for free GPUs

Lane detection for the Nvidia Jetson TX2 using OpenCV4Tegra

bazel.cmake mimics the behavior of bazel to simplify the usability of CMake

Implementation of LIBELAS in cuda.

Various C/C++ examples. DirectX, OpenGL, CUDA, Vulkan, OpenCL.

A GPU-powered real-time analytics storage and query engine.

Experimental parallel compression algorithm

A Deep Learning Amazon Web Service (AWS) AMI that is open, free and works. Run in less than 5 minutes. TensorFlow, Keras, PyTorch, Theano, MXNet, CNTK, Caffe and all dependencies.

Implementation of the KinectFusion approach in modern C++14 and CUDA

Explore the Capabilities of the TensorRT Platform

All-in-one mixed multi-GPU (nVidia, AMD, Intel) & CPU miner solves proof of work to mine supported EIP918 tokens in a single instance (with API).

JIT Compilation for Multiple Architectures: C++, OpenMP, CUDA, HIP, OpenCL, Metal

A domain-specific language and compiler for image processing

Simple physically based path tracer based on Nvidia's Optix Ray Tracing Engine

Archlinux PKGBUILDs for Data Science, Machine Learning, Deep Learning, NLP and Computer Vision

Tengine is a lite, high performance, modular inference engine for embedded device

A cross-platform CUDA/C++14 starter project with google test and google benchmark support.

Robotics with GPU computing

Fork of CUDA GPU memtest 👓

DeepSpeech neon implementation

TensorFlow builds compiled on windows with avx and avx2 extensions

an implementation of softmax splatting for differentiable forward warping using PyTorch

monolish: MONOlithic LInear equation Solvers for Highly-parallel architecture

Super simple & easy Windows 10 cryptocurrency miner made by NiceHash.

gprMax is open source software that simulates electromagnetic wave propagation using the Finite-Difference Time-Domain (FDTD) method for numerical modelling of Ground Penetrating Radar (GPR)

SDK for GPU accelerated genome assembly and analysis

CUDA bindings for Ruby

Automatic parallelization of Python/NumPy, C, and C++ codes on Linux and MacOSX

[内测中]前向式Python环境快捷封装工具，快速将Python打包为EXE并添加CUDA、NoAVX等支持。

Distributed multigrid linear solver library on GPU

JetScan : GPU accelerated portable RGB-D reconstruction system

🌲 Aimbot powered by real-time object detection with neural networks, GPU accelerated with Nvidia. Optimized for use with CS:GO.

PyTorch/TorchScript compiler for NVIDIA GPUs using TensorRT

Morphing and Sampling Network for Dense Point Cloud Completion (AAAI2020)

A stream processing framework for high-throughput applications.

Modular C++ Toolkit for Performance Analysis and Logging. Profiling API and Tools for C, C++, CUDA, Fortran, and Python. The C++ template API is essentially a framework to creating tools: it is designed to provide a unifying interface for recording various performance measurements alongside data logging and interfaces to other tools.

Astrophysics program simulating the evolution of star systems based on the fast multipole method on adaptive Octrees

a reimplementation of Optical Flow Estimation using a Spatial Pyramid Network in PyTorch

GPU-accelerated N-Body particle simulator with visualizer.

Build and run Docker containers leveraging NVIDIA GPUs

PopSift is an implementation of the SIFT algorithm in CUDA.

cuML - RAPIDS Machine Learning Library

Code accompanying my blog post on k-means in Python, C++ and CUDA

gmonitor is a GPU monitor (Nvidia only at the moment)

CUDA tool set for non-C++ languages that provides similar functionality like Thrust, with NVRTC at its core.

Achieve peak performance on x86 CPUs and NVIDIA GPUs

Dragon: A Computation Graph Virtual Machine Based Deep Learning Framework.

Crowdsourcing video experiments (such as collaborative benchmarking and optimization of DNN algorithms) using Collective Knowledge Framework across diverse Android devices provided by volunteers. Results are continuously aggregated in the open repository:

geometry processing and shape analysis framework

Your 🔵 Superintelligence

Implementation of Newcombe et al. CVPR 2015 DynamicFusion paper

Instant neural graphics primitives: lightning fast NeRF and more

Implementation of Cuda to OpenGL rendering

An efficient C++17 GPU numerical computing library with Python-like syntax

Target-dependent sentiment classification in news articles reporting on political events. Includes a high-quality data set of over 11k sentences and a state-of-the-art classification model.