CUDA® is a parallel computing platform and programming model developed by NVIDIA for general computing on graphical processing units (GPUs). With CUDA, developers are able to dramatically speed up computing applications by harnessing the power of GPUs.
TornadoVM: A practical and efficient heterogeneous programming framework for managed languages
Repository containing ready-made laboratory works in the specialty of computing machines, systems and networks
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:
Classes enabling finmath-lib to run its Monte-Carlo models on Cuda GPUs
A git repository containing an NLP example using DL4J (cuda) in Java
XDCS Distributed Computing Software
Support for offloading parallel-for loops in Java to NVIDIA CUDA compatible cards.
In this repository you can find all of my projects for Parallel Processing Course when I was in 2nd semester of my master's at SUT.
A simple parallel histogram equalization in CUDA and Java.
A git repository containing an NLP example using DL4J (cuda) in Java
Java CUDA Mandelbrot explorer
Multiprocessors course final project
Graph representation in the form of adjacency list for CUDA implementation which allows arrays of arbitrary sizes to be created and hence can represent graph using adjacency list
Created by Nvidia
Released June 23, 2007