As artificial intelligence (AI) continues to reshape industries, Intel has launched the Xeon 6 with Performance-cores (P-cores) and Gaudi 3 AI accelerators, reaffirming its commitment to delivering high-performance AI systems with improved efficiency and lower total cost of ownership (TCO).
Meeting the Demands of Modern Data Centers
“Demand for AI is leading to a massive transformation in the data center, and the industry is asking for choice in hardware, software, and developer tools,” said Justin Hotard, Intel’s executive vice president and general manager of the Data Center and Artificial Intelligence Group. “With our launch of Xeon 6 with P-cores and Gaudi 3 AI accelerators, Intel is enabling an open ecosystem that allows our customers to implement all of their workloads with greater performance, efficiency, and security.”
Introducing Intel Xeon 6 with P-cores and Gaudi 3 AI Accelerators
Intel’s latest offerings focus on enhancing its data center portfolio, highlighted by two key advancements:
- Intel® Xeon® 6 with P-cores
The Xeon 6 processor is engineered for compute-intensive workloads, delivering twice the performance of its predecessor. With an increased core count, doubled memory bandwidth, and AI acceleration capabilities embedded in each core, this processor is designed to handle the performance demands of AI across edge, data center, and cloud environments.
- Intel® Gaudi® 3 AI Accelerator
Optimized specifically for large-scale generative AI, the Gaudi 3 features 64 Tensor processor cores (TPCs) and eight matrix multiplication engines (MMEs) to enhance deep neural network computations. It is equipped with 128 gigabytes (GB) of HBM2e memory, 24 200 Gigabit (Gb) Ethernet ports for scalable networking, and seamless compatibility with the PyTorch framework, as well as advanced Hugging Face transformer and diffuser models. Intel’s collaboration with IBM aims to deploy Gaudi 3 as a service on IBM Cloud, significantly lowering TCO while enhancing performance.
Enhancing AI Systems with TCO Benefits
Implementing AI at scale requires a focus on flexible deployment options, competitive price-performance ratios, and accessible AI technologies. Intel’s robust x86 infrastructure and extensive open ecosystem empower enterprises to construct high-value AI systems, optimizing TCO and performance per watt. Notably, 73% of GPU-accelerated servers utilize Intel Xeon as the host CPU.
Intel collaborates with leading OEMs like Dell Technologies and Supermicro to develop co-engineered systems tailored to meet specific customer needs, thereby facilitating effective AI deployments. Currently, Dell Technologies is working on RAG-based solutions leveraging Gaudi 3 and Xeon 6.
Bridging the Gap from Prototypes to Production
Transitioning generative AI (Gen AI) solutions from prototypes to production-ready systems presents challenges in areas such as real-time monitoring, error handling, logging, security, and scalability. Intel addresses these hurdles through co-engineering efforts with OEMs and partners, delivering production-ready retrieval-augmented generation (RAG) solutions.
These RAG solutions are built on the Open Platform Enterprise AI (OPEA) platform, integrating OPEA-based microservices into a scalable system optimized for Xeon and Gaudi AI systems. This design allows customers to easily integrate applications from Kubernetes, Red Hat OpenShift AI, and Red Hat Enterprise Linux AI.
Expanding Access to Enterprise AI Applications
Intel’s Tiber portfolio provides business solutions aimed at overcoming challenges related to access, cost, complexity, security, efficiency, and scalability across AI, cloud, and edge environments. The Intel® Tiber™ Developer Cloud now offers preview systems of Intel Xeon 6 for technology evaluation and testing. Additionally, select customers will receive early access to Gaudi 3 for validating AI model deployments, with Gaudi 3 clusters slated for rollout next quarter for large-scale production.
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