Tech-Guide
How to Get Your Data Center Ready for AI? Part Two: Cluster Computing
In part one of GIGABYTE Technology’s Tech Guide on how you can prepare your data center for the era of AI, we explored the advanced cooling solutions that will help you compute faster with a smaller carbon footprint. In part two, we delve into the key role that cluster computing plays in AI data centers. As the datasets used in AI development become more massive and complex, data centers need servers that will not only perform superbly at critical tasks, but also work with one another to be more than the sum of their parts. This is the basis of cluster computing. GIGABYTE can help you leverage it in your AI data center.
Server and Rack-level Cluster Computing: Two Case Studies
A part of the Talos computing cluster that GIGABYTE built for the University of Rey Juan Carlos. Not only does GIGABYTE have suitable products for different nodes in the cluster, but GIGABYTE also provides cluster management software, free of charge.
The computing cluster that GIGABYTE built for Yang Ming Chiao Tung University allows up to 500 users to compute simultaneously and reduces the time it takes to test IC designs from multiple hours to a matter of minutes.
Data Center-level Cluster Computing: Introducing the GIGAPOD
The GIGAPOD took center stage at COMPUTEX 2024. The nine racks contain 32 GPU Servers housing hundreds of advanced GPUs linked through blazing-fast interconnections, allowing them to compute as a single cohesive unit and tackle the most demanding AI workloads.
The GIGAPOD presents three additional added-value features for its users: bespoke GPU configurations according to customer needs, the choice of liquid cooling for even better performance and stability, and software suites for management and AI development.
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# Artificial Intelligence (AI)
# Machine learning (ML)
# AI Training
# AI Inference
# Generative AI (GenAI)
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