Large-Scale Sweeps

In GPU computing, a large-scale sweep means running many experiments or model training jobs at once, each with slightly different settings - for example, different learning rates or architectures. Instead of training one model at a time, you test hundreds or thousands of variations in parallel to find the best results faster. This requires lots of GPUs, often distributed across cloud providers, so scheduling and cost optimization become crucial.