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
Amazon SageMaker Model Training streamlines the process of training and fine-tuning machine learning (ML) models at scale, significantly cutting down both time and costs while eliminating the need for infrastructure management. Users can leverage top-tier ML compute infrastructure, benefiting from SageMaker’s capability to seamlessly scale from a single GPU to thousands, adapting to demand as necessary. The pay-as-you-go model enables more effective management of training expenses, making it easier to keep costs in check. To accelerate the training of deep learning models, SageMaker’s distributed training libraries can divide extensive models and datasets across multiple AWS GPU instances, while also supporting third-party libraries like DeepSpeed, Horovod, or Megatron for added flexibility. Additionally, you can efficiently allocate system resources by choosing from a diverse range of GPUs and CPUs, including the powerful P4d.24xl instances, which are currently the fastest cloud training options available. With just one click, you can specify data locations and the desired SageMaker instances, simplifying the entire setup process for users. This user-friendly approach makes it accessible for both newcomers and experienced data scientists to maximize their ML training capabilities.
API Access
Has API
No
API Access
Has API
No
Integrations
Amazon SageMaker
Yes
Amazon Web Services (AWS)
Yes
AWS Deep Learning AMIs
Yes
AWS Deep Learning Containers
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 SageMaker
Yes
Amazon Web Services (AWS)
Yes
AWS Deep Learning AMIs
No
AWS Deep Learning Containers
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)
Yes
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
Yes
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
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/sagemaker/train/
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
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