# Introduction

## Overview of Deep Lake's High-Performance Compute Engine built in C++

#### Compute Engine offers high-performance implementations of compute-heavy Deep Lake features, such as distributed dataloading, large queries, and indexing. **The engine is built in C++ and the user-interface is in Python.**

{% hint style="danger" %}
The Deep Lake Compute Engine is only accessible to registered and authenticated users, and it applies usage restrictions based on your Deep Lake Plan.
{% endhint %}

### Features Optimized in the Compute Engine:

{% content-ref url="/pages/qNbf22ZNhBj9ifUAZEPz" %}
[Performant Dataloader](/v3.7.2/performance-features/performant-dataloader.md)
{% endcontent-ref %}

{% content-ref url="/pages/fjjI8Q8rEsEXVKk2EiDY" %}
[Tensor Query Language (TQL)](/v3.7.2/performance-features/querying-datasets.md)
{% endcontent-ref %}

{% content-ref url="/pages/sUeSQxIPKV6wWfNnDgXr" %}
[Index for ANN Search](/v3.7.2/performance-features/index-for-ann-search.md)
{% endcontent-ref %}

{% content-ref url="/pages/K9qimPNhP6GEAAQ41OSr" %}
[Managed Tensor Database](/v3.7.2/performance-features/managed-database.md)
{% endcontent-ref %}


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs-v3.activeloop.ai/v3.7.2/performance-features/introduction.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.