> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.nvidia.com/nemo/curator/v26.04/about/concepts/video/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/nemo/curator/_mcp/server.

# Video Concepts

## Docs

- [Architecture](https://docs.nvidia.com/nemo/curator/v26.04/about/concepts/video/architecture.md): Architecture overview of NeMo Curator's Ray-based distributed video curation system with autoscaling
- [Abstractions](https://docs.nvidia.com/nemo/curator/v26.04/about/concepts/video/abstractions.md): Key abstractions in video curation including stages, pipelines, and execution modes for scalable processing
- [Data Flow](https://docs.nvidia.com/nemo/curator/v26.04/about/concepts/video/data-flow.md): Understanding data flow in video curation pipelines including Ray object store and streaming optimization


> **Note:** This page contains both a page directory (above) and the landing page content (below). The page directory is generated for agent use and does not appear on the landing page.

> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.nvidia.com/nemo/curator/v26.04/about/concepts/video/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/nemo/curator/_mcp/server.

> Essential concepts for video data curation including distributed processing, pipeline stages, and execution modes

# Video Curation Concepts

This document covers the essential concepts for video data curation in NVIDIA NeMo Curator. These concepts assume basic familiarity with data science and machine learning principles.

## Core Concept Areas

Video curation in NVIDIA NeMo Curator focuses on these key areas:

#### [Architecture](/about/concepts/video/architecture)

Core concepts for distributed processing, Ray foundation, and auto-scaling

#### [Key Abstractions](/about/concepts/video/abstractions)

Stages, pipelines, and execution modes in video curation workflows

#### [Data Flow](/about/concepts/video/data-flow)

How data moves through the system from ingestion to output

## Notes on Modalities and Backends

Video pipelines in Curator run on Ray with the `XennaExecutor` integration for streaming and batch execution. Other modalities, such as text and image, also use RAPIDS and Curator’s distributed backends in parts of their workflows. Refer to the modality-specific guides for details.

## Infrastructure Components

The video curation concepts build on NVIDIA NeMo Curator's core infrastructure components. All modalities (text, image, video, and audio) use these components. These components include:

#### [Memory Management](/reference/infra/memory-management)

Optimize memory usage for large datasets
partitioning
batching
monitoring

#### [GPU Acceleration](/reference/infra/gpu-processing)

Leverage NVIDIA GPU acceleration for faster data processing
cuda
rmm
performance

#### [Resumable Processing](/reference/infra/resumable-processing)

Continue interrupted operations on large datasets
checkpoints
recovery
batching