SDK Simulator User Guide

The DPS SDK is a Kubernetes-based development environment for testing power management solutions without physical hardware. It ships with three deployment profiles so you can pick the right starting point for your goals.

Deployment Profiles

• Default - Blank DPS environment with no topology or simulators running. Recommended starting point for hands-on dpsctl exercises and API exploration.
• Hardware Emulation - 144 emulated DGX GB300 nodes across 8 racks with pseudorandom hardware responses. Best for general API development, integration validation, and automated playbooks.
• Workload-Aware - Same 144-node GB300 topology, but the BMC simulator calls a pluggable workload model over gRPC to return realistic GPU power traces. Best for power-aware analysis and workload optimization studies. See the Workload-Aware Simulation guide.

What’s Included

Emulated Infrastructure (Hardware Emulation and Workload-Aware)

• 144 DGX GB300 Compute Nodes - Organized across 8 racks (18 nodes per rack)
• Complete Power Distribution Hierarchy - Utility, Switchboard, Floor PDUs, Rack PSUs, Compute Systems
• BMC Simulator - Provides Redfish API endpoints for all emulated nodes
• Pre-configured Power Policies - GB300-High (5600 W), GB300-Med (3200 W), and GB300-Low (1600 W)

For detailed information about the simulator’s datacenter topology, see the Simulator Topology Guide.

Monitoring and Visualization

• Grafana Dashboards - Real-time metrics for datacenter power, resource groups, and system operations
• Prometheus - Time-series metrics collection and alerting
• Pyroscope - Continuous profiling for performance analysis
• Web UI - Interactive interface for managing DPS

Automated Simulation Playbooks

• Resource Group Simulation - Automated workload lifecycle testing with configurable parameters
• Grid Simulation - Domain-level power management and grid integration testing
• Load Shedding Simulation - Power reduction events and recovery scenarios
• Combined Simulations - Run multiple scenarios simultaneously for thorough testing

Use Cases

The simulator is ideal for:

• Learning DPS - Explore concepts, APIs, and workflows in a safe environment
• SDK Development - Build and test custom integrations without hardware dependencies
• Partner Integration - Develop grid or optimization integrations
• Quick Start - Jump-start your custom datacenter deployment

Quick Start

System Requirements:

• Linux (Ubuntu/Debian) or macOS
• Minimum 8 GB RAM, 20 GB free disk space
• Internet connection for dependencies

Setup Instructions:

1. Download and unarchive the DPS SDK files from the NVIDIA NVOnline Portal.

2. Install SDK dependencies. From the SDK directory, run:

   cd dps-sdk
   task setup

   This installs docker, kubectl, k3d, helm, helm-git, uv, and dpsctl.

3. Deploy the Default profile. This is the recommended starting point - a blank DPS environment with no topology loaded:

   task deploy

4. Configure your shell for dpsctl. Paste these exports once to avoid repeating connection flags on every command:

   export DPSCTL_HOST=api.dps.sdk
   export DPSCTL_PORT=80
   export DPSCTL_INSECURE_TLS_SKIP_VERIFY=true

5. Continue with the Default-profile playbook. The Simulator Playbooks guide walks you through importing the topology, creating resource groups, and setting grid load targets with dpsctl.

Other Deployment Paths

• Hardware Emulation (automated playbooks):

  task sdk
  task sim

  task sdk creates the k3d cluster and deploys DPS; task sim imports the topology and runs the combined resource-groups plus grid simulation.

• Workload-Aware (realistic power traces): See the Workload-Aware Simulation guide for the full deployment flow.

Access Services

After deployment, the SDK exposes these endpoints:

Next Steps

• Simulator Playbooks - Default-profile walkthroughs and Hardware Emulation automated simulations.
• Simulator Topology Guide - GB300 datacenter topology reference.
• Workload-Aware Simulation - Deploy and use the surrogate workload model.

• SDK Simulator Topology
• SDK Simulator Playbooks
• Workload-Aware Simulation