Supermicro Showcases AMD Helios Rack Scale AI Platform at Computex

Jun 2, 2026
Supermicro is collaborating with AMD to present the new Helios rack scale platform at Computex. The system combines AMD Instinct MI455X GPUs and 6th Gen EPYC CPUs to support large-scale AI workloads with improved efficiency and scalability.
Supermicro Showcases AMD Helios Rack Scale AI Platform at Computex

Supermicro, in collaboration with Advanced Micro Devices, Inc. (AMD), will present the AMD Helios rack scale platform at Computex as announced in a press release. The platform is designed for large-scale AI workloads including model training, inference, and fine-tuning, and aims to provide improved scalability and operational efficiency.

The Helios system integrates AMD Instinct MI455X GPUs, 6th Gen AMD EPYC CPUs, and AMD Pensando networking technologies within an open rack scale architecture. It is unified by the AMD ROCm software stack and supports modular scalability from single racks to clusters. The system also includes features for open networking, advanced security, and integrated virtualization.

Supermicro’s implementation of the Helios platform uses its Data Center Building Block Solutions architecture, which shifts from traditional server designs to complete rack scale systems. The 72 GPU configuration is intended to deliver high compute density and power efficiency through advanced cooling and software acceleration. The platform will be displayed at the Supermicro booth in the Taipei Nangang Exhibition Center.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like Silicon Brief or Daily AI Brief.

Also, consider following us on social media:

Free newsletter

Silicon Brief

Weekly coverage of AI hardware developments including chips, GPUs, cloud platforms, and data center technology.

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more
Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.