Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Originally created by Uber, Horovod aims to simplify and accelerate the process of distributed deep learning, significantly reducing model training durations from several days or weeks to mere hours or even minutes. By utilizing Horovod, users can effortlessly scale their existing training scripts to leverage the power of hundreds of GPUs with just a few lines of Python code. It offers flexibility for deployment, as it can be installed on local servers or seamlessly operated in various cloud environments such as AWS, Azure, and Databricks. In addition, Horovod is compatible with Apache Spark, allowing a cohesive integration of data processing and model training into one streamlined pipeline. Once set up, the infrastructure provided by Horovod supports model training across any framework, facilitating easy transitions between TensorFlow, PyTorch, MXNet, and potential future frameworks as the landscape of machine learning technologies continues to progress. This adaptability ensures that users can keep pace with the rapid advancements in the field without being locked into a single technology.
Description
The Membrane Framework is a highly customizable multimedia solution designed for developers using Elixir, intended for the creation of real-time communication systems, media servers, streaming pipelines, and server-side audio-video processing. It offers a versatile approach to multimedia development by allowing the composition of pipelines that incorporate elements, bins, and plugins that manage various formats, codecs, protocols, containers, and external APIs. This framework is particularly effective for implementing WebRTC SFU architectures with flexible input and output options, enabling developers to apply processing, capture media at any stage, or generate additional outputs beyond WebRTC. Since it is built on the Elixir language, Membrane Framework provides advantages such as scalability, fault tolerance, and seamless integration with existing Elixir applications, including those based on the Phoenix web framework. Furthermore, it supports a range of features like server-side processing, transcoding, monitoring utilities, real-time communication, and tailored media workflows, offering developers extensive control over their projects. By leveraging Membrane Framework, teams can efficiently tackle complex multimedia challenges while maintaining high performance and reliability in their applications.
API Access
Has API
No
API Access
Has API
No
Integrations
Amazon Web Services (AWS)
Yes
Azure Databricks
Yes
Elixir
No
Flyte
Yes
Keras
Yes
MXNet
Yes
Microsoft Azure
Yes
PyTorch
Yes
Python
Yes
TensorFlow
Yes
Integrations
Amazon Web Services (AWS)
No
Azure Databricks
No
Elixir
Yes
Flyte
No
Keras
No
MXNet
No
Microsoft Azure
No
PyTorch
No
Python
No
TensorFlow
No
Pricing Details
Free
Free Trial
No
Free Version
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
No
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Horovod
Website
horovod.ai/
Vendor Details
Company Name
Software Mansion
Founded
2012
Country
Poland
Website
membrane.stream/
Product Features
Deep Learning
Convolutional Neural Networks
No
Document Classification
No
Image Segmentation
No
ML Algorithm Library
No
Model Training
No
Neural Network Modeling
No
Self-Learning
No
Visualization
No