In today’s discussions surrounding enterprise IT strategy, generative AI and artificial intelligence (AI) play a dominant role. The emergence of AI applications has sparked interest as organizations seek solutions to various challenges, presenting opportunities for enhanced efficiency in businesses, improved healthcare services, and better governance. While some may view these claims as exaggerated industry hype, they do hold true.
The growing importance of AI has prompted organizations to embark on their AI journey eagerly. Every IT solution provider is now emphasizing AI, whether or not it aligns with the organization’s needs. This trend also sends a clear message to established players like AMD and Intel to innovate in the AI space or risk falling behind, as evidenced by the soaring market value of companies like Nvidia.
In November 2023, AMD entered this arena with the introduction of its MI300-series AI startups. The high demand in the industry has led to challenges in meeting the production needs for the MI300X GPU. Following suit, Intel unveiled its Gaudi 3 AI pedal, raising questions about its performance, compatibility with IT infrastructures, and potential competition with Nvidia’s H100/H200 and AMD’s MI300X.
The Complexity and Costs of AI
While some IT organizations have succeeded in adopting AI, many struggle to scale up their AI initiatives. Despite the existence of relational AI for some time, only 10% of businesses utilized it in 2023. The primary hurdles cited by 46% of AI professionals, according to a cnvrg study, include infrastructure limitations that impede the development of large language models.
The equipment shortage issue, reminiscent of Nvidia’s challenges, further exacerbates the difficulties faced by organizations. Clients often report significant delays, sometimes up to 12 months, in acquiring Nvidia H100s, impacting both cloud-based and on-premises IT providers. Additionally, the unique challenges of creating and managing AI environments, coupled with the complexities of handling organization-specific data while complying with data privacy regulations, contribute to project failures and wasted resources.
These challenges have led to a surge in demand for cloud services such as CoreWeave, Lambda Labs, and Gemini, as well as enhancements in offerings from major cloud providers like Vultr. This landscape sets the stage for Intel’s value proposition with Gaudi 3.
Overview and Advantages of Gaudi 3
Unlike traditional GPUs, Gaudi 3 is designed as an AI accelerator pedal tailored for accelerating AI training, inference, and decision-making processes. Its architecture, featuring 64 fifth-generation vector control cores and eight matrix math engines, delivers high performance. Backed by 128GB of high-bandwidth memory, 7 TB/s bandwidth, 96MB of SRAM with 12 TB/s throughput, and 24 200Gb Ethernet ports, Gaudi 3 offers a robust solution for AI workloads.
Available in three form factors—an OCP accelerator module-compliant card, a PCIe card, and a universal baseboard with eight accelerators—Gaudi 3 is optimized for efficient training and inference tasks. Intel claims that Gaudi 3 outperforms Nvidia’s H100 in training Llama 2 designs by 7x and accelerates GPT-3 training by 1.4x.
The impressive performance claims extend to inference tasks, with Gaudi 3 showcasing faster speeds for various models compared to Nvidia. While performance metrics are yet to be disclosed, Gaudi 3’s power efficiency, reportedly 2.3 times that of the H100, positions it as a cost-effective solution for enterprise AI deployments.
Competing with Established Players
In a nutshell, Gaudi 3 competes effectively with industry giants like Nvidia and AMD in the business AI segment. Focused on delivering high performance at a competitive price point and lower power consumption, Gaudi 3 emphasizes performance per dollar and performance per watt metrics. While pricing details are pending, Gaudi 3’s power efficiency surpasses that of the H100, making it an attractive option for enterprise data centers.
Intel’s extensive ecosystem of hardware, software, and channel partners enhances the appeal of Gaudi 3, offering a comprehensive solution to address the complexities and costs associated with AI adoption in enterprises. As Gaudi 3 prepares for its market debut in the latter half of the year, its potential impact on the AI landscape remains a point of anticipation.
Concluding Remarks
AI holds immense promise, yet its implementation poses challenges in terms of complexity and costs for enterprise IT. Intel’s Gaudi 3 platform emerges as a promising solution to address these challenges, leveraging its advanced hardware capabilities and robust ecosystem support. As Gaudi 3 enters the market, its performance and adoption within enterprise IT environments will be closely monitored to gauge its efficacy in driving AI advancements.
