Intel Unveils Next-Generation AI Solutions with the Launch of Xeon 6 and Gaudi 3
NEWS HIGHLIGHTS
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Intel launches Xeon 6 with Performance-cores (P-cores), doubling the performance for AI and HPC workloads. - New Gaudi 3 AI accelerators offer up to 20 percent more throughput and 2x price/performance vs H100 for inference of LLaMa 2 70B1.
“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
Introducing
Intel’s latest advancements in AI infrastructure include two major updates to its data center portfolio:
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Intel ® Xeon® 6 with P-cores: Designed to handle compute-intensive workloads with exceptional efficiency, Xeon 6 delivers twice the performance of its predecessor2. 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.
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Intel ® Gaudi® 3 AI Accelerator: 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 HBM2e memory for training and inference, and 24 200 Gigabit (Gb) Ethernet ports for scalable networking. Gaudi 3 also offers seamless compatibility with the PyTorch framework and advanced Hugging Face transformer and diffuser models.Intel recently announced a collaboration with IBM to deployIntel Gaudi 3 AI accelerators as a service on IBM Cloud. Through this collaboration,Intel and IBM aim to lower the total cost of ownership to leverage and scale AI, while enhancing performance.
Enhancing AI Systems with TCO Benefits
Deploying AI at scale involves considerations such as flexible deployment options, competitive price-performance ratios and accessible AI technologies. Intel’s robust x86 infrastructure and extensive open ecosystem position it to support enterprises in building high-value AI systems with an optimal TCO and performance per watt. Notably, 73% of GPU-accelerated servers use
Bridging the Gap from Prototypes to Production with Co-Engineering Efforts
Transitioning generative AI (Gen AI) solutions from prototypes to production-ready systems presents challenges in real-time monitoring, error handling, logging, security and scalability.
These solutions, built on the Open Platform Enterprise AI (OPEA) platform, integrate OPEA-based microservices into a scalable RAG system, optimized for Xeon and Gaudi AI systems, designed to allow 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 offers business solutions to tackle challenges such as access, cost, complexity, security, efficiency and scalability across AI, cloud and edge environments. The Intel® Tiber™ Developer Cloud now provides preview systems of
New service offerings include SeekrFlow, an end-to-end AI platform from Seekr for developing trusted AI applications. The latest updates feature
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Source: IDC Server Tracker report, based on Q1’24 system volume.
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Bats Jafferji
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bats.jafferji@intel.com
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