AI clusters move at the speed of their network. AMD Pensando Vulcano 800 AI NIC delivers up to 2.4 Tbps per GPU and up to 13% faster AI job completion—all in a unique 3 NICs-per-GPU architecture built for AMD Helios. Learn more: amd.com/en/solutions/ai/netw…

Scaling AI infrastructure isn't just a compute problem. 7 questions show why the network is where deployments can break down — or break through. Learn more: bit.ly/4euVaWE

What's a DPU? While CPUs handle apps, DPUs tackle networking, storage and security. The result is efficiency and infrastructure that scales. Learn how CPUs, GPUs, DPUs and AI NICs work together: bit.ly/4eqI3av

Learn why data movement = compute power: amd.com/en/blogs/2025/what-i…

Your network may be bottlenecking AI performance.

AI NICs help solve this problem. They are purpose-built to optimize data flow across AI clusters, helping reduce delays and improve utilization.

As clusters scale to thousands of GPUs, packets queue and performance can suffer.

Your GPUs are only as fast as the data feeding them. As AI clusters scale, networking becomes critical to performance. AI NICs are built to keep data moving efficiently, helping maximize throughput and minimize bottlenecks ↓

@Jabil's new server solution features AMD Solarflare X4 Ethernet Adapters—built for ultra-low latency financial trading. With advanced kernel bypass and hardware acceleration, they help power performance where precision matters most. Learn more: bit.ly/4eoBAfW

As AI scales across hundreds of GPUs, communication becomes critical to performance. Enter AI networking. In our new blog “What is AI Networking?”, we break down how it enables efficient, scalable AI infrastructure. Learn more: amd.com/en/blogs/what-is-ai-…