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

> Technical reference for NeMo Curator's infrastructure components including distributed computing, memory management, and GPU acceleration

# Infrastructure References

Browse these references to configure distributed execution, memory use, GPU processing, checkpoints, workers, and containers across NeMo Curator modalities.

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## Infrastructure Components

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

Optimize memory usage when processing large datasets
partitioning
batching
monitoring

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

Use NVIDIA GPUs to accelerate data processing
cuda
rmm
performance

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

Continue interrupted operations across large datasets
checkpoints
recovery
batching

#### [Stage Worker Sizing](/reference/infra/stage-worker-sizing)

Configure fixed and autoscaling worker pools across Ray Data, Xenna, and Ray Actor Pool backends
workers
autoscaling
stage-overrides

#### [Container Environments](/reference/infra/container-environments)

Build your own NeMo Curator container and configure its dependencies, build arguments, and runtime environment.
docker
uv
environments

> Technical reference for NeMo Curator's infrastructure components including distributed computing, memory management, and GPU acceleration