Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
It enables efficient training on Amazon Elastic Compute Cloud (Amazon EC2) Trn1 instances powered by AWS Trainium. Additionally, for model deployment, it facilitates both high-performance and low-latency inference utilizing AWS Inferentia-based Amazon EC2 Inf1 instances along with AWS Inferentia2-based Amazon EC2 Inf2 instances. With the Neuron SDK, users can leverage widely-used frameworks like TensorFlow and PyTorch to effectively train and deploy machine learning (ML) models on Amazon EC2 Trn1, Inf1, and Inf2 instances with minimal alterations to their code and no reliance on vendor-specific tools. The integration of the AWS Neuron SDK with these frameworks allows for seamless continuation of existing workflows, requiring only minor code adjustments to get started. For those involved in distributed model training, the Neuron SDK also accommodates libraries such as Megatron-LM and PyTorch Fully Sharded Data Parallel (FSDP), enhancing its versatility and scalability for various ML tasks. By providing robust support for these frameworks and libraries, it significantly streamlines the process of developing and deploying advanced machine learning solutions.
Description
Our accelerator hardware is specifically crafted to enhance the performance and efficiency of deep learning, while prioritizing usability for developers. SynapseAI aims to streamline the development process by providing support for widely-used frameworks and models, allowing developers to work with the tools they are familiar with and prefer. Essentially, SynapseAI and its extensive array of tools are tailored to support deep learning developers in their unique workflows, empowering them to create projects that align with their preferences and requirements. Additionally, Habana-based deep learning processors not only safeguard existing software investments but also simplify the process of developing new models, catering to both the training and deployment needs of an ever-expanding array of models that shape the landscape of deep learning, generative AI, and large language models. This commitment to adaptability and support ensures that developers can thrive in a rapidly evolving technological environment.
API Access
Has API
No
API Access
Has API
No
Integrations
Amazon Web Services (AWS)
Yes
AWS Deep Learning AMIs
Yes
AWS Deep Learning Containers
Yes
AWS Trainium
Yes
Amazon EC2 Capacity Blocks for ML
Yes
Amazon EC2 G5 Instances
Yes
Amazon EC2 Inf1 Instances
Yes
Amazon EC2 P4 Instances
Yes
Amazon EC2 P5 Instances
Yes
Amazon EC2 Trn1 Instances
Yes
Integrations
Amazon Web Services (AWS)
Yes
AWS Deep Learning AMIs
No
AWS Deep Learning Containers
No
AWS Trainium
No
Amazon EC2 Capacity Blocks for ML
No
Amazon EC2 G5 Instances
No
Amazon EC2 Inf1 Instances
No
Amazon EC2 P4 Instances
No
Amazon EC2 P5 Instances
No
Amazon EC2 Trn1 Instances
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
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
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
Yes
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
Yes
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
Amazon Web Services
Founded
2006
Country
United States
Website
aws.amazon.com/machine-learning/neuron/
Vendor Details
Company Name
Habana Labs
Founded
2016
Country
Israel
Website
habana.ai/training-software/
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
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No
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