.. _uses: Use Cases +++++++++ Examples By Category ==================== .. raw:: html
Distributed Python examples for queues, pools, pipelines, and shared state
Distributed data sharing with a DDict-focused walkthrough
Collect and inspect Dragon runtime and application metrics
Workflow patterns for AI loops, MPI orchestration, Parsl, and Batch DAGs
AI examples for data loading, agents, and inference-oriented workflows
Process a large dataset in parallel
Orchestrate executing a serial executable with many different arguments
Orchestrate a parameter sweep for an MPI application
Set up PyTorch distributed launch, rank info, and data loading on GPUs
Track application state to enable fault tolerance and recovery
Run on a collection of servers or a supercomputer
Use a Jupyter notebook with Dragon
Running functions and processes that use specific GPUs
Visualize and analyze system and custom metrics
Build a simple end-to-end workflow with Batch, DDict, and external jobs
Connect and run workflows across multiple systems
Multi-agent LLM pipelines with tools, HITL, and tracing
Serve shared vLLM backends with Dragon queues and GPUs
Schedule parallel tasks and DAG-shaped dependencies with the Batch API
Use Dragon logging to inspect runtime behavior and application issues
Write Code in C++ that shares Data and Objects with Python