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What is Graphcore?

Leverage state-of-the-art IPU AI systems in the cloud to develop, train, and implement your models, collaborating with our cloud service partners. This strategy allows for a significant reduction in computing costs while providing seamless scalability to vast IPU resources as needed. Now is the perfect time to start your IPU journey, benefiting from on-demand pricing and free tier options offered by our cloud collaborators. We firmly believe that our Intelligence Processing Unit (IPU) technology will establish a new standard for computational machine intelligence globally. The Graphcore IPU is set to transform numerous sectors, showcasing tremendous potential for positive societal impact, including breakthroughs in drug discovery, disaster response, and decarbonization initiatives. As an entirely new type of processor, the IPU has been meticulously designed for AI computation tasks. Its unique architecture equips AI researchers with the tools to pursue innovative projects that were previously out of reach with conventional technologies, driving significant advancements in machine intelligence. Furthermore, the introduction of the IPU not only boosts research capabilities but also paves the way for transformative innovations that could significantly alter our future landscape. By embracing this technology, you can position yourself at the forefront of the next wave of AI advancements.

What is Amazon SageMaker HyperPod?

Amazon SageMaker HyperPod is a powerful and specialized computing framework designed to enhance the efficiency and speed of building large-scale AI and machine learning models by facilitating distributed training, fine-tuning, and inference across multiple clusters that are equipped with numerous accelerators, including GPUs and AWS Trainium chips. It alleviates the complexities tied to the development and management of machine learning infrastructure by offering persistent clusters that can autonomously detect and fix hardware issues, resume workloads without interruption, and optimize checkpointing practices to reduce the likelihood of disruptions—thus enabling continuous training sessions that may extend over several months. In addition, HyperPod incorporates centralized resource governance, empowering administrators to set priorities, impose quotas, and create task-preemption rules, which effectively ensures optimal allocation of computing resources among diverse tasks and teams, thereby maximizing usage and minimizing downtime. The platform also supports "recipes" and pre-configured settings, which allow for swift fine-tuning or customization of foundational models like Llama. This sophisticated framework not only boosts operational effectiveness but also allows data scientists to concentrate more on model development, freeing them from the intricacies of the underlying technology. Ultimately, HyperPod represents a significant advancement in machine learning infrastructure, making the model-building process both faster and more efficient.

Media

Media

Integrations Supported

AWS EC2 Trn3 Instances
AWS Trainium
Amazon SageMaker
Amazon Web Services (AWS)
Cirrascale
Hugging Face
Keras
PaddlePaddle
PyTorch
TensorFlow

Integrations Supported

AWS EC2 Trn3 Instances
AWS Trainium
Amazon SageMaker
Amazon Web Services (AWS)
Cirrascale
Hugging Face
Keras
PaddlePaddle
PyTorch
TensorFlow

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Graphcore

Date Founded

2016

Company Location

United Kingdom

Company Website

www.graphcore.ai/

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/sagemaker/ai/hyperpod/

Categories and 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)

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