Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

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

NetApp AIPod presents a holistic AI infrastructure solution aimed at simplifying the deployment and oversight of artificial intelligence workloads. By incorporating NVIDIA-validated turnkey solutions like the NVIDIA DGX BasePOD™ alongside NetApp's cloud-integrated all-flash storage, AIPod brings together analytics, training, and inference into one unified and scalable system. This integration allows organizations to efficiently execute AI workflows, encompassing everything from model training to fine-tuning and inference, while also prioritizing data management and security. With a preconfigured infrastructure tailored for AI operations, NetApp AIPod minimizes complexity, speeds up the path to insights, and ensures smooth integration in hybrid cloud settings. Furthermore, its design empowers businesses to leverage AI capabilities more effectively, ultimately enhancing their competitive edge in the market.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon Web Services (AWS)
Azure Databricks
Flyte
Keras
MXNet
Microsoft Azure
NVIDIA DIGITS
PyTorch
Python
TensorFlow

Integrations

Amazon Web Services (AWS)
Azure Databricks
Flyte
Keras
MXNet
Microsoft Azure
NVIDIA DIGITS
PyTorch
Python
TensorFlow

Pricing Details

Free
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Horovod

Website

horovod.ai/

Vendor Details

Company Name

NetApp

Founded

1992

Country

United States

Website

www.netapp.com/artificial-intelligence/aipod/

Product Features

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

Product Features

Artificial Intelligence

Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)

Data Management

Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

Alternatives

AWS Neuron Reviews

AWS Neuron

Amazon Web Services

Alternatives

AWS Neuron Reviews

AWS Neuron

Amazon Web Services
DeepSpeed Reviews

DeepSpeed

Microsoft