GreenNode adds NVIDIA H200 (141GB HBM3e) and RTX PRO 6000 Blackwell (96GB GDDR7) to its AI Cloud, delivering high-performance, cost-optimized GPU infrastructure for enterprises in Vietnam & SEA.

In this guide, we’ll break down what a GPU cluster is, how it works, and what’s involved in building one. You’ll learn about core components, architecture design, real-world use cases, and best practices for deploying scalable GPU infrastructure. Let’s dive in!

Compare NVIDIA H100 vs H200 GPUs in specs, performance, and AI workloads. Discover which GPU fits your needs in 2025.

This project reminded us that building AI Cluster infrastructure at scale isn't just a technical challenge — it’s a people challenge

In the dynamic realm of artificial intelligence (AI), NVIDIA and AMD take the lead, challenging the limits of computational capability. Both corporations have introduced formidable AI chips, yet the comparison between MI250X vs H100 prompts the question of superiority. This article will analyze performance metrics, statistics, and features of both chips to ascertain the ultimate champion in the realm of AI processing.

In this article, GreenNode will share our experience with multinode setups—specifically using NVIDIA’s H100 GPUs and InfiniBand technology—to address specific use cases for our clients.

Then what is SLURM for AI and how this high-scalable workload manager works on Linux clusters? In this blog, we’ll guide you through SLURM concept and how to set up a SLURM cluster tailored for AI projects.

Struggling with GPU underperformance? Learn the root causes and practical steps to fix GPU underperformance and maximize compute efficiency for AI and HPC workloads.

The landscape of GPU-accelerated computing in the business realm is on the brink of significant expansion. A notable trend gaining momentum is the integration of generative AI, enabling the creation of human-like text and diverse images. This surge in interest is propelled by transformative technologies like transformer models, seamlessly embedding AI into everyday applications, ranging from conversational interfaces to the generation of complex protein structures.