The Rise of Accelerator-Based Data Centers: Opportunities and Challenges

Emerging applications such as generative artificial intelligence (AI) and deep neural networks are extremely computationally intensive, making traditional CPU-based infrastructure insufficient for handling complexity and scale. Accelerators like GPUs and field-programmable gate arrays have become essential to efficiently process the vast datasets and complex models that these applications require. Hyperscale data centers deploy thousands of accelerators to meet workload demand; however, as more enterprises recognize the strategic importance of owning and customizing their generative AI models, many are shifting toward deploying accelerator-based data centers on their premises. This shift presents unique opportunities, including improved data security, latency reduction, and the flexibility to customize models in-house. However, it also introduces significant challenges, including high initial capital expenditure, the need for specialized infrastructure and cooling solutions, and the complexity of managing these advanced resources. IT professionals need to analyze several factors (technological, economic, and operational) carefully before deploying accelerators in their premises.