GPUs play a crucial role in data centers, particularly for AI workloads due to their immense computing power. However, the high cost of GPUs, both in terms of upfront purchase and ongoing energy consumption, can be a barrier for organizations. One way to mitigate these costs is by utilizing cloud-based GPU hardware on a pay-as-you-go basis, allowing businesses to access GPU resources as needed without the hefty investment. This article explores the decision-making process between cloud-based GPU services and owning GPU hardware for data center operations.
When it comes to the role of graphics processing units, or GPUs, in data centers, there are two things to know. The first is that GPUs are critical to AI workloads because they provide the massive compute resources necessary for AI training and inference, hence the rise of GPU-filled data centers dedicated to AI. The second is that GPUs cost a lot of money. This is not just due to their price, which can be tens of thousands of dollars per device, but also because of the energy they require to operate.
