How Scale Computing Powers Edge AI Workloads via AMD

Scale Computing is expanding its infrastructure capabilities by integrating AMD CPU support into version 9.7 of its SC//HyperCore virtualisation suite. 

By incorporating AMD EPYC and AMD Ryzen processors, the edge computing provider aims to streamline data deployment right where generation occurs.

The move deepens an existing partnership between both technology providers.

While Scale Computing’s SC//Reliant edge computing as a service platform currently utilises AMD CPUs across retail and distributed settings, this release brings that hardware compatibility to the broader portfolio.

For enterprise customers, the release provides a long-sought solution to platform choice across edge, data centre and distributed enterprise environments. 

It allows organisations to simplify operations while running emerging AI-enabled workloads outside traditional centralised environments.

Expanding infrastructure choice

IT departments face increasing pressure to lower complexity, build operational resilience and prepare systems for AI applications.

The addition of AMD CPU-powered solutions gives these teams a new deployment pathway.

Craig Theriac, VP of Product Management at Scale Computing, explains that customers actively seek greater choice while modernising virtualisation platforms and planning for edge AI.

He says: “With SC//HyperCore virtualisation suite version 9.7, we are expanding support for AMD platforms in a way that directly aligns with our mission: making infrastructure simpler to deploy, easier to manage and more resilient across distributed environments.”

Meanwhile, Derek Dicker, Corporate VP of the Enterprise Business Group at AMD, points out that organisations need infrastructure capable of handling complex operations without creating management friction.

“Our collaboration with Scale Computing gives customers greater flexibility in how they deploy AMD CPU-powered infrastructure, combining AMD’s performance and efficiency with Scale Computing’s simplified approach to managing workloads from the data centre to the edge,” he says.

Powering edge AI workloads

As technologies like computer vision, analytics and automation move closer to source data, infrastructure must deliver dependable performance without adding management hurdles. 

Distributed sectors such as retail, healthcare and manufacturing require architecture capable of running traditional virtualised applications alongside new AI tasks.

AMD-powered hardware delivers performance and energy efficiency tailored for adverse operational conditions at the far edge, with form factors spanning from compact devices to robust rackmount units.

This flexibility allows Scale Computing customers to design tailored solutions without sacrificing scalability or resilience. 

Early technical evaluations reveal strong potential in consistent high-I/O thread handling, improved power efficiency, enhanced EPYC memory throughput and the use of embedded GPUs in AMD Ryzen AI platforms.

Furthermore, the update opens up fresh avenues for hardware OEMs, ODMs, resellers and technology partners. 

These third-party channel partners can now offer a distinct route to help clients modernise legacy systems and prepare for AI-driven edge requirements.