Containerized data centers and liquid cooling

According to DIGITIMES, the data center industry is witnessing an increasing adoption of containerized solutions and liquid cooling systems. These developments are driven by the need to efficiently manage the increasing power density and growing energy efficiency requirements, especially in relation to artificial intelligence and machine learning workloads.

Containerized data centers offer flexibility and scalability, enabling rapid deployment and easy resource management. Liquid cooling, on the other hand, is essential for dissipating the heat generated by high-density components, such as GPUs used for training and inference of large language models (LLM). The adoption of these technologies can significantly impact the TCO (Total Cost of Ownership) of data centers, reducing energy costs and improving space utilization.

For those evaluating on-premise deployments, there are significant trade-offs between CapEx and OpEx to consider. AI-RADAR offers analytical frameworks on /llm-onpremise to evaluate these aspects.