The architecture at the heart of the data center has changed to adapt to the requirements of AI workloads, with GPU clusters replacing traditional CPU racks for high performance.
Generative AI relies on training foundation models and performing inference tasks, which require the ability to perform calculations on vast datasets quickly, making GPUs more suitable than CPUs.
The popularity of AI technologies has ushered in a new era for the data center as workloads have become increasingly complex and power-intensive, necessitating a transformation.
Hardware accelerators such as neural processing units (NPUs) and tensor processing units (TPUs) complement GPUs, providing specialized computing power needed for AI training and inference tasks.
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