403 Open source projects that are alternatives of or similar to Cuda Convnet2.torch

Clustering via Graphics Processor, using NVIDIA CUDA sdk to preform database clustering on the massively parallel graphics card processor

Fast Neural Machine Translation in C++

An implementation of the RoiAlign operation for Theano

Real-time video quality improvement for applications such as video-chat using Perceptual Losses

Pytorch Bindings for warp-ctc

Cooperative primitives for CUDA C++.

Efficient GPU kernels for block-sparse matrix multiplication and convolution

Kernel Tuning Toolkit

Real-time large scale dense visual SLAM system

CUDA implementation of the 2D fast Poisson solver

CUDA implementation of the Jacobi method

Making it easier to work with shaders

Implementation of a simple CNN using CUDA

R package for unleashing the power of NVIDIA GPU's

label-smooth, amsoftmax, focal-loss, triplet-loss, lovasz-softmax. Maybe useful

GraphVite: A General and High-performance Graph Embedding System

OpenCL integration for Python, plus shiny features

caffe implementation of "Arbitrary Style Transfer with Deep Feature Reshuffle"

Embedded language for high-performance array computations

3D Spatial Transformer Network

High-Performance Graph Primitives on GPUs

A collection of Bash scripts and Dockerfiles to install data science Tool, Lib and application

A flexible framework of neural networks for deep learning

Fast Clojure Matrix Library

an implementation of Video Frame Interpolation via Adaptive Separable Convolution using PyTorch

Large scale K-means and K-nn implementation on NVIDIA GPU / CUDA

Utilities for CUDA programming

Tests and benchmarks for cudnn (and in the future, other nvidia libraries)

Performance-optimized wheels for TensorFlow (SSE, AVX, FMA, XLA, MPI)

DES cracking using brute force algorithm and CUDA

source code for paper "Deep Discrete Supervised Hashing"

N body gravity attraction problem solver

An interval arithmetic and affine arithmetic library for NVIDIA CUDA

Image recognition and classification using Convolutional Neural Networks with TensorFlow

Python interface to GPU-powered libraries

Use the Intel D435 real-sensing camera to realize target detection based on the Yolov3 framework under the Opencv DNN framework, and realize the 3D positioning of the Objection according to the depth information. Real-time display of the coordinates in the camera coordinate system.ADD--Using Yolov5 By TensorRT model,AGX-Xavier,RealTime Object Detection

A fast, ergonomic and portable tensor library in Nim with a deep learning focus for CPU, GPU and embedded devices via OpenMP, Cuda and OpenCL backends

A CUDA project for Molecular Dynamics, Brownian Dynamics, Hydrodynamics... intended to simulate a very generic system constructing a simulation with modules.

NumPy aware dynamic Python compiler using LLVM

How fast can we brute force a 64-bit comparison?

💰 USB flash drive ISO image for Ethereum, Zcash and Monero mining with NVIDIA graphics cards and Ubuntu GNU/Linux (headless)

Bregman ADMM for mass transportation on GPU

The Hacker's Machine Learning Engine

Deformable ConvNets V2 (DCNv2) in PyTorch

Code and data for paper "Deep Painterly Harmonization": https://arxiv.org/abs/1804.03189

Slides and demo code for past presentations

Automatically exported from code.google.com/p/cuda-convnet2

Physically based renderer and simulation engine for real-time applications.

Reference implementation of real-time autoregressive wavenet inference

CUDA on Intel GPUs

Stereo Matching by Training a Convolutional Neural Network to Compare Image Patches

Experiments with CUDA and Rust

Atmospheric fluid dynamics solver optimized for GPUs.

Qualia is a deep learning framework deeply integrated with automatic differentiation and dynamic graphing with CUDA acceleration. Qualia was built from scratch.

Large octree map construction and rendering with CUDA and OpenGL

A GPU implementation of smallpt (http://www.kevinbeason.com/smallpt/) with Bounding Volume Hierarchy (BVH) tree.

This project is an old code for Chinese words split. It is written by CUDA at 2010, so it could not run well directly under you platform without an GPU card.

Fast Point Cloud Segmentation Using Permutohedral Lattices