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DGL - Download

Free download DGL Windows app to run online win Wine in Ubuntu online, Fedora online or Debian online

This is the Windows app named DGL whose latest release can be downloaded as 0.7.2.zip. It can be run online in the free hosting provider OnWorks for workstations.

Download and run online this app named DGL with OnWorks for free.

Follow these instructions in order to run this app:

- 1. Downloaded this application in your PC.

- 2. Enter in our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.

- 3. Upload this application in such filemanager.

- 4. Start any OS OnWorks online emulator from this website, but better Windows online emulator.

- 5. From the OnWorks Windows OS you have just started, goto our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.

- 6. Download the application and install it.

- 7. Download Wine from your Linux distributions software repositories. Once installed, you can then double-click the app to run them with Wine. You can also try PlayOnLinux, a fancy interface over Wine that will help you install popular Windows programs and games.

Wine is a way to run Windows software on Linux, but with no Windows required. Wine is an open-source Windows compatibility layer that can run Windows programs directly on any Linux desktop. Essentially, Wine is trying to re-implement enough of Windows from scratch so that it can run all those Windows applications without actually needing Windows.

SCREENSHOTS:

DGL


DESCRIPTION:

Build your models with PyTorch, TensorFlow or Apache MXNet. Fast and memory-efficient message passing primitives for training Graph Neural Networks. Scale to giant graphs via multi-GPU acceleration and distributed training infrastructure. DGL empowers a variety of domain-specific projects including DGL-KE for learning large-scale knowledge graph embeddings, DGL-LifeSci for bioinformatics and cheminformatics, and many others. We are keen to bringing graphs closer to deep learning researchers. We want to make it easy to implement graph neural networks model family. We also want to make the combination of graph based modules and tensor based modules (PyTorch or MXNet) as smooth as possible. DGL provides a powerful graph object that can reside on either CPU or GPU. It bundles structural data as well as features for a better control. We provide a variety of functions for computing with graph objects including efficient and customizable message passing primitives for Graph Neural Networks.



Features

  • A GPU-ready graph library
  • Models, modules and benchmarks for GNN researchers
  • Easy to learn and use
  • Scalable and efficient
  • Plenty of learning materials for all kinds of users from ML researcher to domain experts
  • Optimizes the whole stack to reduce the overhead in communication, memory consumption and synchronization


Programming Language

Python



This is an application that can also be fetched from https://sourceforge.net/projects/dgl.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.


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