Spark Framework

Horovod was originally developed by Uber to make distributed deep learning fast and easy to use, bringing model training time down from days and weeks to hours and minutes. With Horovod, an existing training script can be scaled up to run on hundreds of GPUs in just a few lines of Python code. Horovod can be installed on-premise or run out-of-the-box in cloud platforms, including AWS, Azure, and Databricks. Horovod can additionally run on top of Apache Spark, making it possible to unify data processing and model training into a single pipeline. Once Horovod has been configured, the same infrastructure can be used to train models with any framework, making it easy to switch between TensorFlow, PyTorch, MXNet, and future frameworks as machine learning tech stacks continue to evolve.

Atri framework is a full-stack web development framework to build Progressive Web Apps. Use our visual editor to increase your productivity. You can also add your custom React code. Currently, we support Python for backend development. We are planning to add support for NodeJS soon. Our CLI provides rich support for easy deployment at your platform of choice such as GitHub Pages, AWS, etc. Atri framework comes with a suite of productivity tools such as a visual editor, asset management tools, etc. that significantly reduce development time from months to hours. Atri framework is extending the definition of full-stack to include non-web developers in the development and maintenance of an app.