In the rapidly evolving AI landscape, GPUs have become indispensable, driving advancements from deep learning to complex data analytics. The latest AMD Instinct™ accelerators are purpose-built for exceptional performance and efficiency, delivering leadership capabilities across foundation model training, fine-tuning, and inference. However, AI is not a one-size-fits-all challenge—nor is enterprise IT infrastructure.

While GPUs remain essential for large-scale generative AI, 5^th Gen AMD EPYC™ CPUs are the world’s best CPU for enterprise AI[i] that provide a scalable, cost-effective path for AI-enhanced applications and host node performance. With high-frequency processing, leadership memory capacity, and seamless x86 compatibility, AMD delivers an evolutionary path to AI acceleration, enabling organizations to integrate, scale, and modernize their infrastructure at their own pace—with little disruption.

With increased core counts, memory capacity and I/O expandability, many IT leaders are looking to modernize their IT infrastructure with single socket (1P) server solutions. 1P servers can provide cost-effective, performant, and energy efficient solutions for most workloads. So, how do you know if 1P solutions are right for you? This blog takes a look at things to consider and which workloads are best suited for 1P and 2P platforms.

Granite Rapids In an ever-evolving technology landscape, enterprise IT managers must consider many factors when selecting hardware, including performance vs. power efficiency, security and compliance, scalability and future proofing, cloud vs. on-prem, total cost of ownership (TCO), and more. Choosing the right processor is crucial to optimizing performance, efficiency, and cost—for any deployment model. One feature that can help boost performance and efficiency, offered across nearly all AMD EPYC™ processors, is simultaneous multithreading (SMT), which allows a single physical CPU core to execute multiple threads simultaneously.

IT leaders are under pressure to manage shrinking budgets, optimize compute-intensive AI workloads, and implement viable sustainability strategies.  These competing imperatives are not easily rationalized!  Together AMD and Nutanix can help your IT department overcome these and other challenges.  This blog post briefly illustrates how Nutanix Hyperconverged infrastructure (HCI) and virtualization software running on AMD EPYC™ processors will help you lower software licensing costs, optimize workload performance and reduce your carbon footprint. 

Discover how upgrading to AMD EPYC processors can help resolve IT challenges, boost performance, reduce costs, and simplify migration in today's demanding data center landscape. In this blog, learn about the compelling TCO benefits, VMware collaboration, and innovative features they offer that address workload demands and efficiency goals, paving the way for a future-ready data center. Dive in to learn how transitioning to AMD EPYC can recoup expenses in as little as two months and transform your organization's IT infrastructure.

As the leader in silicon-to-systems design solutions, including electronic design automation (EDA) tools, an impressive portfolio of silicon-proven semiconductor intellectual property (IP), and pre-silicon hardware-assisted verification solutions, Synopsys is a key provider to drive semiconductor innovation.  Such contributions have broad impact to help the industry meet the unprecedented demands of high-performance computing, artificial intelligence (AI), and ever-upgrading devices and software.

In a recent AMD Tech Talk podcast hosted by AMD’s Jim Greene, Synopsys’ Senior Director of Product and Solutions Marketing, Todd Koelling, explained how Synopsys’ tools and expertise are enhanced with AI capabilities to empower semiconductor and systems companies to develop increasingly complex, yet energy-efficient AI processors, GPUs and accelerator chips. In this brief blog post, we’ll look at what Synopsys does and how AMD and Synopsys have collaborated in multiple areas to deliver state-of-the-art, high-complexity, energy-efficient chips.

Choosing the right infrastructure when deploying AI for business use cases is key. As the complexity of AI workloads increases, enterprises need to make informed decisions about memory footprint and compute capabilities, especially when dealing with multimodal AI that requires multiple models working together.  I recently had the pleasure of talking with Steen Graham of Metrum Ai about solving real-world AI challenges and the future of enterprise AI for the AMD EPYC TechTalk podcast series, available here. You can also find highlights from the interview below.  

• When AMD introduced the 1st generation of the AMD EPYC™ processor, we redefined what was possible. Previous, monolithic approaches to processor design were shuffled off the stage in favor of innovative approaches to meet the ever-increasing demands of modern datacenters.

Each successive generation of AMD EPYC processors has delivered both incremental and step-function levels of improvement in performance, scalability and energy efficiency. With the launch of the highly anticipated 5th generation based on AMD “Zen5” and “Zen5c” processor cores, I can confidently state that the AMD legacy of innovation and leadership is secure.

BeeKeeperAI operates a privacy-preserving, confidential computing platform that protects data and enables secure collaborations. At a time when security threats seem ubiquitous, BeeKeeperAI, with the help of security technologies built into AMD EPYC processors, help safeguard data. I had a great time speaking with Alan Czeszynski, BeeKeeperAI's marketing and product development leader. The full podcast can be accessed here.     

I recently had the pleasure of speaking about the future of AI, large language models (LLM) and retrieval augmented generation (RAG) with my colleague, Meena Arunachalam,  AMD AI Systems Engineering Director and Fellow. We were able to pack a lot into our discussion, so I have highlighted just a handful of Meena’s invaluable insights and recommendations in this blog post.  For more detail, you can listen to the podcast here .