1592 Open source projects that are alternatives of or similar to Chainer

An extensible HPC framework for CUDA, OpenCL and native CPU.

OptiX Path Tracer

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PyGraphistry is a Python library to quickly load, shape, embed, and explore big graphs with the GPU-accelerated Graphistry visual graph analyzer

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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.

ArrayFire: a general purpose GPU library.

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Social Distancing and Face Mask Detection using TensorFlow. Install all required Libraries and GPU drivers as well. Refer to README.md or REPORT for know to installation requirement

Data visualisation in Python based on OptiX 7.2 ray tracing framework.

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FLAME GPU 2 is a GPU accelerated agent based modelling framework for C++ and Python

monolish: MONOlithic LInear equation Solvers for Highly-parallel architecture

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an implementation of parallel linear BVH (LBVH) on GPU

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

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Dockerfiles for OpenCV compiled with CUDA, opencv_contrib modules and Python 3 bindings

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Python bindings for ArrayFire: A general purpose GPU library.

CUDA programming in Julia.

Rust wrapper for ArrayFire

This is a list of useful libraries and resources for CUDA development.

Simple utilities to enable code reuse and portability between CUDA C/C++ and standard C/C++.

a reimplementation of LiteFlowNet in PyTorch that matches the official Caffe version

BriefMatch real-time GPU optical flow

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A collection of GICP-based fast point cloud registration algorithms

Source code of PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).

Minimal runtime core of Caffe, Forward only, GPU support and Memory efficiency.

Thin C++-flavored wrappers for the CUDA Runtime API

ILGPU JIT Compiler for high-performance .Net GPU programs

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cuDF - GPU DataFrame Library

An open-source tool for sequence learning in NLP built on TensorFlow.

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