Rearchitecting Data Centers for AI Workloads

Rearchitecting Data Centers for AI Workloads

IT leaders know that cutting-edge infrastructure is essential for AI, but building and optimizing an AI-ready data center is no easy task.

Most AI projects fall short – not because of the models, but because traditional data center infrastructure can’t keep up. AI workloads place intense demands on storage, compute, networking and power far beyond what legacy systems were built to handle.

Download this paper to unlock 3 actionable strategies to rearchitect your data center for AI, complete with step-by-step guidance. You’ll learn how to address bottlenecks in data throughput, reduce training times, improve inference performance and meet compliance requirements.

Register Here for This Asset

What is most important for your organization’s data center this year? *

Do you have a planned data center initiative in the focus area selected above? *

Who is your company’s preferred on-prem server manufacturer? *

What is your role in data center initiatives at your organization? *

By claiming this asset, you agree to receive communications from AMD regarding products and offers. Your data will be handled in accordance with AMD’s privacy policy.