The 6 best cooling architectures for AI workloads

Many AI servers with accelerators (e.g., GPUs) used for training LLMs (large language models) and inference workloads, generate enough heat to necessitate liquid cooling.

The question, of course, becomes what cooling solution actually fits the needs of your server hardware today… and what solutions will prevent you from being constrained tomorrow.

In this white paper, compare the 6 most common heat rejection architectures for liquid cooling, and find out which is the best choice for your AI servers or cluster.

Vendor:: Schneider Electric
Posted:: Mar 5, 2024
Published:: Mar 5, 2024
Format:: HTML
Type:: White Paper

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