850 Open source projects that are alternatives of or similar to Deepnet

stdgpu: Efficient STL-like Data Structures on the GPU

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CUDA bindings for Ruby

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

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

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

CUDA integration for Python, plus shiny features

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Clojure library for CUDA development

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Particle-in-Cell Simulations for the Exascale Era ✨

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Rusty wrapper for the CUDA Driver API

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Rust wrapper for ArrayFire

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

GPGPU microprocessor architecture

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A community run, 5-day PyTorch Deep Learning Bootcamp

Open3D: A Modern Library for 3D Data Processing

BitCracker is the first open source password cracking tool for memory units encrypted with BitLocker

H2Oai GPU Edition

High-Performance Graph Primitives on GPUs

This guide should help fellow researchers and hobbyists to easily automate and accelerate there deep leaning training with their own Kubernetes GPU cluster.

Taking a pretrained GloVe model, and using it as a TensorFlow embedding weight layer **inside the GPU**. Therefore, you only need to send the index of the words through the GPU data transfer bus, reducing data transfer overhead.

⚡️Optimizing einsum functions in NumPy, Tensorflow, Dask, and more with contraction order optimization.

A flexible framework of neural networks for deep learning

Library for faster pinned CPU <-> GPU transfer in Pytorch

Reference implementation for "Massively Parallel Rendering of Complex Closed-Form Implicit Surfaces" (SIGGRAPH 2020)

LuxCore source repository

Fast Neural Machine Translation in C++

OpenCL integration for Python, plus shiny features

A TensorFlow-inspired neural network library built from scratch in C# 7.3 for .NET Standard 2.0, with GPU support through cuDNN

ThunderGBM: Fast GBDTs and Random Forests on GPUs

Embedded language for high-performance array computations

Open deep learning compiler stack for cpu, gpu and specialized accelerators

Python interface to GPU-powered libraries

A High Level Python Deep Reinforcement Learning library. Great for beginners, prototyping and quickly comparing algorithms

Cooperative primitives for CUDA C++.

ThunderSVM: A Fast SVM Library on GPUs and CPUs

Image recognition and classification using Convolutional Neural Networks with TensorFlow

Experiments with CUDA and Rust

Some CUDA design patterns and a bit of template magic for CUDA

50% faster, 50% less RAM Machine Learning. Numba rewritten Sklearn. SVD, NNMF, PCA, LinearReg, RidgeReg, Randomized, Truncated SVD/PCA, CSR Matrices all 50+% faster

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

CARLsim is an efficient, easy-to-use, GPU-accelerated software framework for simulating large-scale spiking neural network (SNN) models with a high degree of biological detail.

GraphVite: A General and High-performance Graph Embedding System

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Gradient Boosting powered by GPU(NVIDIA CUDA)

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Multi-dimensional arrays (tensors) and numerical definitions for Elixir