> 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/reference/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/nemo/curator/_mcp/server.

# Reference

## Docs

- [Overview](https://docs.nvidia.com/nemo/curator/v26.04/reference/infra.md): Technical reference for NeMo Curator's infrastructure components including distributed computing, memory management, and GPU acceleration
- [Memory Management](https://docs.nvidia.com/nemo/curator/v26.04/reference/infra/memory-management.md): Strategies and best practices for managing memory when processing large datasets with NeMo Curator
- [Monitoring](https://docs.nvidia.com/nemo/curator/v26.04/reference/infra/monitoring.md): Set up Prometheus and Grafana to monitor NeMo Curator pipelines on single-user and multi-user Ray clusters
- [GPU Processing](https://docs.nvidia.com/nemo/curator/v26.04/reference/infra/gpu-processing.md): Guide to leveraging NVIDIA GPU acceleration in NeMo Curator for faster data processing and memory optimization
- [Resumable Processing](https://docs.nvidia.com/nemo/curator/v26.04/reference/infra/resumable-processing.md): Implementation guide for resumable processing to handle interrupted large-scale data operations in NeMo Curator
- [Execution Backends](https://docs.nvidia.com/nemo/curator/v26.04/reference/infra/execution-backends.md): Choose and configure execution backends for NeMo Curator pipelines
- [Per-Stage Runtime Environments](https://docs.nvidia.com/nemo/curator/v26.04/reference/infra/per-stage-runtime.md): Isolate Python dependencies per pipeline stage using Ray runtime environments
- [Container Environments](https://docs.nvidia.com/nemo/curator/v26.04/reference/infra/container-environments.md): Reference documentation for container environments, configurations, and deployment variables in NeMo Curator
- [Related Tools](https://docs.nvidia.com/nemo/curator/v26.04/reference/related-tools.md): Overview of NVIDIA AI ecosystem tools that integrate with NeMo Curator for end-to-end model development workflows


> **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/reference/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/nemo/curator/_mcp/server.

> Comprehensive technical reference for NeMo Curator APIs, infrastructure components, and integration tools

# References

NeMo Curator's reference documentation provides comprehensive technical details, API references, and integration information to help you maximize your NeMo Curator implementation. Use these resources to understand the technical foundation of NeMo Curator and integrate it with other tools and systems.

## API Quicklinks

Browse the generated [Python API reference](/api/reference/api-reference) for NeMo Curator modules, or use the **API Reference** tab for curated overviews of pipelines, stages, tasks, and executors.

## Infrastructure Components

Explore the foundational infrastructure that powers NeMo Curator. Learn how to scale, optimize, and manage large data workflows efficiently.

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

Optimize memory usage when processing large datasets
partitioning
batching
monitoring

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

Leverage NVIDIA GPUs for faster data processing
cuda
rmm
performance

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

Continue interrupted operations across large datasets
checkpoints
recovery
batching

## Integration & Tools

Discover related tools and integrations in the NVIDIA AI ecosystem that complement NeMo Curator, enabling seamless workflows from data curation to model training and deployment.

#### [Related Tools](/reference/related-tools)

Learn about complementary tools in the NVIDIA ecosystem
nemo-framework
triton-server
tao-toolkit