# GPU Module

_This page explains what the GPU module is and when to use it._
> **Note — If you would like to evaluate KDB-X GPU acceleration, please email [devrel@kx.com](mailto:devrel@kx.com) with your request.**
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## Key features

The GPU module:

- Supports moving data to and from the GPU with the ability to append data in batches.
- Supports a restricted set of qSQL queries on the GPU using standard q syntax.
- Supports sorting of in-memory tables on the GPU using standard q syntax.
- Supports as-of joins with attributes on the GPU using standard q syntax.

## When to use the GPU module

Use the GPU module whenever you:

- Have workflows that benefit from parallelization across many threads.
- Have data resident in memory on the GPU and want improved performance.

## Key terms

The following terms describe how data is stored, moved, and interpreted between the CPU and GPU:

- **On-device:** Data resident in GPU VRAM, represented in q as `foreign`.
- **On-host:** Data resident in CPU RAM, accessible to standard q operations.
- **Foreign:** The q representation of an on-device object.
- **Mixed residency:** A table where some columns are on-device and others on-host.
- **Grouped attribute:** A q attribute (`` `g# ``) required for certain GPU operations such as `.gpu.bin` and `.gpu.aj`.
- **VRAM:** GPU memory, distinct from system RAM.
- **CUDA kernel:** A function executed in parallel across GPU threads, distinct from the OS kernel.

## Next steps

- To get started with the GPU module, refer to the [Quickstart](quickstart/quickstart.md).
- Check the [GPU Release Notes](./release-notes/changelog.md) for version history and fixes.