Pushing The Limits Of HPC And AI Is Becoming A Sustainability Headache
The Next Platform, Friday, November 17,2023
'If you want more performance, you need to buy more hardware, and that means a bigger system; that means more energy dissipation and more cooling demand,' University of Utah professor Daniel Reed explained as a recent session at the SC23 supercomputing conference in Denver.
As Moore's law continues to slow, delivering more powerful HPC and AI clusters means building larger, more power hungry facilities.
Today, the largest supercomputing clusters on the Top500 are consuming more than 20 megawatts and many datacenter campuses, particularly those built to support demand for AI training and inference, are even larger. Some projections suggest that by 2027 a capability-class supercomputer will require on the order of 120 megawatts of power.