This is the Windows app named Hivemind whose latest release can be downloaded as 1.1.10_macOSandLinuxARMsupport.zip. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named Hivemind 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:
Hivemind
DESCRIPTION:
Hivemind is a PyTorch library for decentralized deep learning across the Internet. Its intended usage is training one large model on hundreds of computers from different universities, companies, and volunteers. Distributed training without a master node: Distributed Hash Table allows connecting computers in a decentralized network. Fault-tolerant backpropagation: forward and backward passes succeed even if some nodes are unresponsive or take too long to respond. Decentralized parameter averaging: iteratively aggregate updates from multiple workers without the need to synchronize across the entire network. Train neural networks of arbitrary size: parts of their layers are distributed across the participants with the Decentralized Mixture-of-Experts. If you have succesfully trained a model or created a downstream repository with the help of our library, feel free to submit a pull request that adds your project to the list.
Features
- Before installing, make sure that your environment has Python 3.7+
- Decentralized parameter averaging
- Fault-tolerant backpropagation
- Distributed training without a master node
- Train neural networks of arbitrary size
- By default, hivemind uses the precompiled binary of the go-libp2p-daemon library
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/hivemind.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.