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Intel is launching new Xeon 6 processors with performance cores as well as Gaudi 3 AI accelerators to stay competitive in the AI wars.
The new Xeon 6 processors have performance cores (P-cores) that can double AI vision performance and the Gaudi 3 AI accelerators have 20% more throughput.
As AI continues to revolutionize industries, enterprises are increasingly in need of infrastructure that is both cost-effective and available for rapid development and deployment. To meet this demand head-on, Intel today launched Xeon 6 with Performance-cores (P-cores) and Gaudi 3 AI accelerators, bolstering the company’s commitment to deliver powerful AI systems with optimal performance per watt and lower total cost of ownership (TCO).
“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 executive vice president and general manager of the data center and AI group at Intel, in a statement. “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.”
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Introducing Intel Xeon 6 with P-cores and Gaudi 3 AI accelerators
Intel Gaudi 3
Intel’s latest advancements in AI infrastructure include two major updates to its data center portfolio. These include Intel Xeon6 with P-cores. They’re designed to handle compute-intensive workloads with exceptional efficiency, Xeon 6 delivers twice the performance of its predecessor.
It features increased core count, double the memory bandwidth and AI acceleration capabilities embedded in every core. This processor is engineered to meet the performance demands of AI from edge to data center and cloud environments.
The Intel Gaudi 3 AI accelerator is specifically optimized for large-scale generative AI, Gaudi 3 boasts 64 Tensor processor cores (TPCs) and eight matrix multiplication engines (MMEs) to accelerate deep neural network computations.
It includes 128 gigabytes (GB) of HBMe2 memory for training and infe …