High-Performance Computing

Overview

High-performance computing, or HPC, is the field concerned with aggregating computing power so that many processors can attack a single problem together. It has long underpinned scientific endeavors that exceed any one machine, weather forecasting, molecular modeling, physics simulation, and its hard-won techniques for connecting and coordinating large numbers of nodes are precisely the techniques modern AI training now relies upon.

How it works

An HPC system links many compute nodes through a high-speed, low-latency interconnect such as InfiniBand, backed by parallel storage capable of feeding all of them at once. Software distributes a problem across the nodes, which compute their portions and exchange results continually so the cluster behaves as a single large machine. The defining engineering challenge is communication: keeping the nodes coordinated without the network becoming the bottleneck.

Why it matters

Large-scale AI training is, in practice, an HPC workload. Spreading a model across dozens or hundreds of GPUs and keeping them synchronized is the same problem supercomputing has solved for decades, which is why AI clusters borrow HPC's interconnects, topologies, and parallel file systems wholesale. Understanding the discipline clarifies why the network and storage around the GPUs matter as much as the GPUs themselves.