Intel Gaudi 2 AI Accelerator

Purpose-Built AI Processors for the cloud

Intel Gaudi processors are designed to deliver cost-efficient and easy-to-implement AI workloads in the cloud.

Efficiency

With the demands of generative AI and large language models for massive and efficient AI compute, Intel Gaudi processors offer proven, price/performance advantages to cloud service providers, enabling them to deliver cost-efficient training and inference at any scale. SynapseAI software and Intel Gaudi accelerator hardware were architected for training and inference performance and efficiency, so end-users can train and deploy larger data sets and retrain models more frequently, increasing deep learning workload accuracy and applicability.

Usability

The Intel team is committed to making it easy for cloud service providers and their end-customers to develop and deploy Intel Gaudi accelerator models with relative ease and support. Our SynapseAI software platform integrates PyTorch and TensorFlow frameworks, and supports the growing array of generative AI, large language, computer vision and natural language models. We provide data scientists and developers with documentation, “how to” guides and videos, community and Intel Gaudi accelerator support forums, and tools on the Habana Developer Site and on the Habana GitHub.

Scalability

Twenty-four 100-Gigabit ports of RDMA over Converged Ethernet (RoCE) are integrated into every Intel Gaudi 2 processor, giving cloud providers flexible and expandable networking capacity, enabling optimization of networking within the server node with all-to-all processor connectivity. And, integrated RoCE on every Intel Gaudi 2 accelerator gives CSPs and their customers a near-infinite array of cost-effective options for scaling out across nodes and racks, with versatile AI compute capacity based on affordable, industry-standard Ethernet technology.

Purpose-Built AI Processors in the Data Center

Whether it’s a data center you’re building on-premises at your company or a supercomputer for academic research

First and second-generation Intel Gaudi accelerators deliver tangible benefits to make training AI models more cost-effective and easy to build and scale.

Efficiency

Deep learning training and inference on first- and second-generation Intel Gaudi AI accelerators benefit from substantial price/performance advantage – so you get more training and inference compute while spending less for your on-premises deployments. Architected from the ground up and optimized for deep learning performance and efficiency, Intel Gaudi platform solutions enable more customers to run more deep learning workloads with speed and performance, while containing operational costs.

Usability

We’re focused on giving data scientists, developers and IT and systems administrators all they need to ease the development and deployment on-premise of solutions based on Intel Gaudi AI accelerators. Our SynapseAI® Software Platform is optimized for building and implementing deep learning models on Intel Gaudi accelerators on PyTorch and TensorFlow frameworks on a wide array of models including generative AI, large language, computer vision and natural language models. And the Habana Developer and Habana GitHub sites provide a wide array of content – documentation, scripts, how-to videos, reference models and tools–to help you get started, enabling you to easily build new or migrate existing models to systems built on Intel Gaudi accelerators.

Scalability

With the advent of generative AI and large language models has come the leap size and complexity of workloads. Now, it’s more essential than ever for data centers to be able to easily and cost-effectively scale-up and scale-out capacity—with some systems requiring up to hundreds or even thousands of processors to run training and deployments with with speed and accuracy. First- and second-generation Intel Gaudi processors were designed like no other—expressly to address scalability—with twenty-four 100-Gigabit Ethernet ports of RDMA over Converged Ethernet (RoCE) integrated into every Intel Gaudi 2 processor. The result is massive and flexible scaling capacity based on the industry’s networking standard already employed in virtually all data centers.