When we think about data centers today, we often picture rows of GPU-packed racks run by companies like Microsoft, Google, Amazon, and Meta, and used by AI labs such as OpenAI and Anthropic. Much of that hardware does one of two jobs: training new models or running finished ones to answer requests from millions of people around the world.
A supercomputer is built from many of the same parts but for a different purpose. It is typically owned by a government lab or university and designed for scientific simulation, such as modeling climate, nuclear physics, or new materials. That work demands high-precision math and very fast communication between processors. Rather than serving the masses, a supercomputer is shared among researchers, whose large jobs wait in a queue and run according to a schedule.
