# GPU offloading

Moving computationally intensive operations onto a GPU. Eugo applies this automatically when a GPU is available and the data transfer is worth its cost.

Source: https://university.eugo.io/glossary/gpu-offloading

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It is conditional by design: copying a small array to device memory and back costs more than the operation saves, so small arrays stay on the CPU. Verify where work executed rather than assuming.

## Related terms

- [GPU](https://university.eugo.io/glossary/gpu) — A graphics processing unit. Hardware with many parallel cores, well suited to large array and matrix operations.
- [Transfer cost](https://university.eugo.io/glossary/transfer-cost) — The time spent moving data between machines, or between host and GPU memory. Often the reason an operation is not worth accelerating.
- [Automatic optimization](https://university.eugo.io/glossary/automatic-optimization) — Transformations Eugo applies to your code as it runs: vectorization, GPU offloading, and low-level tuning, with no annotation from you.