Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
AWS Trainium represents a next-generation machine learning accelerator specifically designed for the training of deep learning models with over 100 billion parameters. Each Amazon Elastic Compute Cloud (EC2) Trn1 instance can utilize as many as 16 AWS Trainium accelerators, providing an efficient and cost-effective solution for deep learning training in a cloud environment. As the demand for deep learning continues to rise, many development teams often find themselves constrained by limited budgets, which restricts the extent and frequency of necessary training to enhance their models and applications. The EC2 Trn1 instances equipped with Trainium address this issue by enabling faster training times while also offering up to 50% savings in training costs compared to similar Amazon EC2 instances. This innovation allows teams to maximize their resources and improve their machine learning capabilities without the financial burden typically associated with extensive training.
Description
Amazon SageMaker HyperPod is a specialized and robust computing infrastructure designed to streamline and speed up the creation of extensive AI and machine learning models by managing distributed training, fine-tuning, and inference across numerous clusters equipped with hundreds or thousands of accelerators, such as GPUs and AWS Trainium chips. By alleviating the burdens associated with developing and overseeing machine learning infrastructure, it provides persistent clusters capable of automatically identifying and rectifying hardware malfunctions, resuming workloads seamlessly, and optimizing checkpointing to minimize the risk of interruptions — thus facilitating uninterrupted training sessions that can last for months. Furthermore, HyperPod features centralized resource governance, allowing administrators to establish priorities, quotas, and task-preemption rules to ensure that computing resources are allocated effectively among various tasks and teams, which maximizes utilization and decreases idle time. It also includes support for “recipes” and pre-configured settings, enabling rapid fine-tuning or customization of foundational models, such as Llama. This innovative infrastructure not only enhances efficiency but also empowers data scientists to focus more on developing their models rather than managing the underlying technology.
API Access
Has API
API Access
Has API
Integrations
AWS EC2 Trn3 Instances
AWS AI Factories
AWS Neuron
AWS Parallel Computing Service
AWS Trainium
Amazon EC2
Amazon EC2 Capacity Blocks for ML
Amazon EC2 G5 Instances
Amazon EC2 Inf1 Instances
Amazon EC2 P4 Instances
Integrations
AWS EC2 Trn3 Instances
AWS AI Factories
AWS Neuron
AWS Parallel Computing Service
AWS Trainium
Amazon EC2
Amazon EC2 Capacity Blocks for ML
Amazon EC2 G5 Instances
Amazon EC2 Inf1 Instances
Amazon EC2 P4 Instances
Pricing Details
No price information available.
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
Amazon Web Services
Founded
2006
Country
United States
Website
aws.amazon.com/machine-learning/trainium/
Vendor Details
Company Name
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/sagemaker/ai/hyperpod/
Product Features
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization