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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.
Description
Illustrate sample API requests and their corresponding responses while articulating the logic of API endpoints in plain language. Conduct tests on your API endpoints and adjust your prompt, response format, and request format as needed. With a simple click, deploy your API endpoints and seamlessly integrate them into your applications. Create and launch intricate application functionalities without needing to write any code, all within a minute. No need for individual LLM accounts; just register for Backengine and begin your development process. Your endpoints operate on our high-performance backend architecture, accessible instantly. All endpoints are designed to be secure and safeguarded, ensuring that only you and your applications can access them. Effortlessly manage your team members so that everyone can collaboratively work on your Backengine endpoints. Enhance your Backengine endpoints by incorporating persistent data, making it a comprehensive backend alternative. Additionally, you can utilize external APIs within your endpoints without the hassle of manual integration. This approach not only simplifies the development process but also enhances overall productivity.
API Access
Has API
API Access
Has API
Integrations
AWS EC2 Trn3 Instances
AWS Trainium
Amazon SageMaker
Amazon Web Services (AWS)
Integrations
AWS EC2 Trn3 Instances
AWS Trainium
Amazon SageMaker
Amazon Web Services (AWS)
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
$20 per month
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
Founded
1994
Country
United States
Website
aws.amazon.com/sagemaker/ai/hyperpod/
Vendor Details
Company Name
Backengine
Website
backengine.dev/
Product Features
Product Features
API Testing
Functional Testing
Fuzz Testing
Load Testing
Penetration Testing
Runtime and Error Detection
Security Testing
UI Testing
Validation Testing