Resource Library

The telecommunications landscape is shifting as accelerated computing becomes mainstream. This transformation unlocks the potential to monetize the telco edge with AI applications, by offering GPU infrastructure to internal and 3rd party users while simultaneously running 5G/6G Radio-Area-Network (RAN) software. This unified approach is no longer a future concept – it's a critical business imperative for creating new revenue streams and monetizing the edge. But how can you build a platform that can generate new revenue while meeting the strict demands of RAN? Join experts from Supermicro and Aarna.ml for a deep dive into a comprehensive reference architecture for AI RAN distributed inference. We will unveil a complete, cloud-native solution designed to transform your edge sites into dynamic, monetizable AI platforms that can also run RAN software.

Supermicro and NVIDIA are transforming retail by delivering edge AI solutions that bring intelligence directly into the store.

STAC recently performed a STAC-ML™ Markets (Inference) benchmark audit on a stack including an NVIDIA GH200 Grace Hopper Superchip in a Supermicro ARS-111GL-NHR server. (ID: SMC250910)

The latest advancements in AI come with new infrastructure challenges, such as increased power requirements and thermal management. Supermicro’s Data Center Building Block Solutions (DCBBS) delivers everything required to rapidly outfit liquid cooled AI data centers.

Liquid-Cooled GPU Servers Reduce Power Consumption and Increase Performance

As the adoption of AI use cases in retail, manufacturing, smart spaces, and other industries continues to expand, enterprise infrastructure performance at the edge needs to keep up. Finding the right balance between performance and TCO is vital for a successful and sustainable business case. Additionally, enterprises are embracing specialized AI models for predictive, generative, physical, and agentic AI, making low-latency data processing for real-time decision-making even more critical. Join us as we discuss Edge AI use cases to demonstrate how businesses can drive growth and operational excellence and how Supermicro's edge portfolio is designed to deliver the required AI performance at the edge.

Closer to Data, Ahead of Tomorrow’s Intelligence

Traditional retail is more competitive than ever. As AI advances, retailers have the opportunity to unlock new efficiencies and incredible shopper experiences. But success isn’t guaranteed. It requires enterprise-grade edge systems with rack-simplicity. That’s where Supermicro and AMD come in.

This white paper explores how Intel’s Trust Domain Extensions (TDX) and NVIDIA Confidential Computing with Supermicro’s HGX B200-based systems together provide a powerful, secure, and scalable platform for next-generation AI infrastructure.

Supermicro ARS-E103-JONX: Performance Optimized, Fanless System for AI at the Edge

Power-efficient Performance for the Distributed Network

Supermicro and Algo-Logic Deliver Ultra-Low Latency execution of sophisticated trading strategies of Futures and Options. The system leverages an AI cluster, an analytics server with precise timestamping, and hardware-accelerated trade execution.

As AI/ML, Agentic AI, and Retrieval-Augmented Generation (RAG) workloads grow in complexity and demand, the performance of underlying storage systems becomes mission-critical. To keep GPUs fully utilized, storage must deliver exceptional performance in both sequential and random operations. With their excellent performance, NVMe PCIe drives are ideal for mission-critical applications.

Supermicro and AMD offer solutions to address the numerous challenges involved with successfully transitioning enterprise generative AI initiatives from Proof of concept to production, providing high-performance servers optimized for AI training and inferencing.

Supercharged AI & HPC workloads drive critical business momentum