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Latency-dependent liquid cooling use cases
Liquid cooling enables companies to use compute power more efficiently. Thus, the most common use cases are applications that require the greatest compute intensity. But computing massive amounts of data also requires predictable, low-latency, high-throughput access to that data. To better understand different compute-intensive liquid cooling use cases, we need to understand what data we need access to and where that data lives.
Compute-intensive workloads at the core
Some compute-intensive, latency-sensitive use cases should be placed on your core IT infrastructure. These are the use cases that require seamless access to data lakes and data transfer across hybrid cloud architectures to enhance overall performance. Examples might include AI model fine tuning, multi-vector simulations or HPC clusters that are latency dependent to both cloud data and global networks. Because such applications require high-throughput, low-latency access to data, clouds and networks, you should put them close to your data storage, cloud and network ecosystem. A cloud-dense data center with global carrier access is ideal for these use cases, and liquid cooling can then be employed to support the required compute power.
Compute-intensive workloads are increasing, but #LiquidCooling can help. Read about some of the top use cases for liquid cooling in data centers: https://eqix.it/4dge5Cu