Intel Sets New Standard for AI Delivery With Gaudi 3 AI Accelerators

In the evolving world of AI and deep learning, the latest workloads demand continually better hardware performance without sacrificing efficiency, and the Intel Gaudi 3 processors exemplify the company's commitment to high-performance AI and machine learning. As part of Intel's Habana Labs AI accelerator lineup, Gaudi processors are specifically designed for deep learning training and inference generation, which are essential for modern applications. With significant improvements in performance and efficiency over previous generations and industry competitors, more customers are increasingly opting for Intel Gaudi AI accelerators over compute platforms from other vendors.

Here are some key reasons why:

1. Specialization for AI Workloads

Gaudi accelerators are purpose-built for AI workloads and intense learning training, which allows them to outperform traditional CPUs and even general-purpose GPUs in many AI tasks. Gaudi processors are optimized to support various popular AI applications, including:

• Large Language Models,
• Multi-modal models
• Enterprise Retrieval-Augmented Generation (RAG)
• Diffusion models (for images, i.e. with Stable Diffusion)
• Standard object recognition and classification
• Voice dubbing

2. Performance Improvement

Gaudi 3 builds on the architecture of its predecessors (Gaudi and Gaudi 2) and brings enhanced performance in terms of AI model training, power efficiency, and scalability. They're designed to deliver higher throughput and lower latency for large-scale AI workloads, critical for training complex models like transformers used in natural language processing (NLP), computer vision, and recommendation systems.

Some key performance improvements over Intel Gaudi 2 accelerators include:

• 2x AI Compute (FP8)
• 4x AI Compute (FP16)
• 2.6x Faster matrix math - (1.8 PetaFLOPS matrix processing at BF16 and FP8)
• 2x Network bandwidth - (24 200 GbE RoCE v2 NICs)
• 1.5x Faster HBM bandwidth
• 1.33x Larger HBM capacity

3. Cost-Effectiveness

One of the goals of the Gaudi architecture including Gaudi 3, is to provide a cost-effective alternative to GPU-based AI accelerators of other vendors. With the introduction of Gaudi 3, Intel aims to reduce the financial barrier for enterprises to deploy AI at scale by offering competitive performance at a lower cost per training run. For example, Guadi 3 accelerators have demonstrated up to 2x performance per dollar improvements versus popular GPU-based systems.

4. Integration with Intel's AI Ecosystem

Gaudi 3 accelerators are integrated into Intel's broader AI and data center strategy, complementing other Intel technologies such as Xeon processors and FPGAs. Therefore, they're a crucial part of Intel's push to capture more of the growing AI and machine learning market.

5. Scalability

Intel designed their Gaudi 3 AI accelerators to scale efficiently in large clusters to promote use in hyperscale data centers and AI labs that must handle massive AI workloads. In addition, its architecture supports large-scale model training with high data throughput and parallelism. Supporting growth, Gaudi 3 is built on two compute dies, which, combined, offer 8 MME engines, 64 TPC engines, and 24 x 200 Gbps RDMA NIC ports. As a result, Gaudi 3 accelerators can be deployed anywhere from single systems to large clusters.

6. Open Architecture

Whereas other manufacturers attempt to lock their customers in with proprietary technology, Intel Gaudi 3 AI accelerators are built on open architecture standards to provide operators the most flexibility. In their April announcement, Intel unveiled plans to develop an open platform for enterprise-level AI in partnership with Red Hat, SAP, and VMware. In addition, they announced a suite of Ethernet solutions optimized for AI, like AI connectivity chiplets and the AI NIC (network interface card).

7. Developer Tools

Intel Tiber Developer Cloud users can easily access the latest technology and enjoy a suite of tools to enable faster AI deployment at scale.

Some of Tiber's many advantages include:

• Toolkits and Libraries - such as the Intel AI Tools and HPC Toolkits, and Intel Quantum SDK
• AI Foundation Models - like Technology Innovation Institute (TII) Falcon LLM, MosaicML MPT, and HuggingFace Bloom
• AI Frameworks and Tooling - such as Intel Optimization for PyTorch, Intel Distribution of OpenVINO Toolkit, and Intel Optimization for TensorFlow

For a comprehensive list of all the Intel Tiber Developer Cloud offers, visit its page at Intel.com.

To Leverage Intel Gaudi 3 AI Accelerators in Your Latest Deployment, Partner with UNICOM Engineering

Intel Gaudi 3 AI accelerators address the growing demands of today's AI, HPC, and machine learning workloads. It provides a high-performing, scalable, and cost-effective solution for AI training, marking Intel's continuing commitment to AI innovation and data center solutions.

As an Intel Titanium Level OEM partner, UNICOM Engineering has deep expertise in bringing innovative HPC and AI solutions to market, equipped with the latest technology for breakthrough performance. Our experienced team is ready to assist with designing your solution and ensuring it is deployed on the optimal hardware to meet your needs.

Visit our website to schedule a consultation and learn more about how we can help you bring your HPC or AI solution to market.

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