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Intel Gaudi 3 AI Accelerator

High-performance AI accelerator designed for AI workloads.

#Artificial Intelligence
#machine learning
#deep learning
#high performance computing
#accelerator
Intel Gaudi 3 AI Accelerator

Product Details

Intel® Gaudi® 3 AI Accelerator is a high-performance artificial intelligence accelerator launched by Intel. It is built on the efficient Intel® Gaudi® platform and has excellent MLPerf benchmark performance, designed to handle demanding training and inference tasks. The accelerator supports AI applications such as large language models, multimodal models, and enterprise RAGs in the data center or cloud, running on Ethernet infrastructure you may already have. Whether you need a single accelerator or thousands of accelerators, Intel Gaudi 3 can play a critical role in your AI success.

Main Features

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Provides high-performance AI computing, supporting FP8 and BF16 computing.
2
Compatible with existing Ethernet infrastructure, requiring no additional investment in proprietary technology.
3
Provides more I/O connectivity than H100, optimizing cost efficiency.
4
Supports massive vertical and horizontal scaling.
5
Supports community-based open software and industry-standard Ethernet networking.
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Simplify the entire process from proof of concept to production.
7
Supports the use of PyTorch library, making it easy for existing teams to use.
8
Supports rapid migration of existing GPU models.

How to Use

1
1. Visit Intel’s official website and search for Intel® Gaudi® 3 AI Accelerator.
2
2. Choose the appropriate model and configuration based on your needs.
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3. Purchase through the Intel Tiber™ Developer Cloud or OEM partners.
4
4. Read the white paper and development documentation to learn how to deploy and use the accelerator.
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5. Use software tools and resources provided by Intel for model migration and development.
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6. Integrate the accelerator into existing data center or cloud infrastructure.
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7. Use accelerators to perform AI model training and inference tasks.
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8. Get support and best practices through Intel’s developer community.

Target Users

The target audience is enterprise users who need to handle large amounts of AI workloads, such as data center operators, cloud service providers, and AI research and development teams. These users typically require high-performance, scalable, and cost-effective solutions to optimize their AI applications.

Examples

Used for large-scale language model training to improve training efficiency.

Provide efficient AI inference services in cloud services.

Used in enterprise resource planning (ERP) systems to optimize data processing and analysis.

Quick Access

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Categories

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› AI model
› AI model inference training

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