Differentiated IT Architecture in the Age of AI
As AI models move from development to production, the power demands of data centers are expected to double within the next few years. To meet this burgeoning need, an architecture-first strategy that considers the entire system is essential. This encompasses a full-stack view, where hardware and software are tightly integrated.
This integrated approach is critical to optimizing system performance and robustness for large-scale, mission-critical applications. The core of the solution resides in a system architecture that allows for extensions and accelerators that seamlessly integrate with the core computing units, providing a way of optimizing processing and scaling. This also has the benefit of potentially reducing data center space and power consumption.
Enterprise computing now requires an architecture that uniquely integrates processor units (PUs), memory, input/output (I/O), and network communications with data center infrastructure, maximizing processing capabilities and enabling scalable operations. The design should prioritize processing and scaling on demand while controlling data center costs.
The mainframe is playing a larger role in the AI landscape. It is evolving to accommodate and accelerate the newest innovations, including the next generation of AI accelerators. The new accelerators are projected to provide four times more compute power.
