Search results

• cdf-simulation

  Component-owned guidance for CDF Simulation requests submitted directly or through Airflow-triggered DIG Flow Catalog prompts — golden THT board, THT pin-geometry variation, good/clean SMT images, structural pose defects, and solder texture defects, from

  Skill
• cudaq-guide

  Use for CUDA-Q setup, simulation targets, QPU access, and @cudaq.kernel authoring guidance.

  Skill
• using-ovnewton

  Connect the Newton physics engine to an Omniverse simulation or ovstage with ovnewton. Use when importing a populated ovstage into Newton, stepping its physics, synchronizing stage edits, or publishing simulation state for Omniverse rendering.

  Skill
• cdf-defect-image-generation

  Generate synthetic PCB inspection images on Kubernetes with the SMT Defect Image Generation (DIG) DAG in CDF Orchestration. The DAG renders components in simulation, turns the renders into realistic golden images (sim2real), and uses AnomalyGen to add tex

  Skill
• nvalchemi-toolkit

  Build and change NVIDIA ALCHEMI Toolkit (nvalchemi) workflows for atomistic simulation and machine-learned interatomic potentials (MLIPs). Use for batched structure relaxation, molecular dynamics, reaction paths, training or fine-tuning an MLIP, atomistic

  Skill
• nvflare-autofl

  Use for agent-assisted Auto-FL optimization of an existing NVFLARE job in simulation, POC, or production. Do not use for code conversion, diagnosis-only work, or deployment setup.

  Skill
• nvflare-diagnose-job

  Use when the user asks why a reported NVFLARE job failure signal occurred: the job failed, stalled, timed out, lost clients, ended with EXECUTION_EXCEPTION, or produced suspicious errors. Diagnose in simulation, POC, or production by collecting bounded ev

  Skill
• omniverse-cad-to-simready

  Coordinate the end-to-end CAD/source-asset to SimReady workflow. Use for broad requests such as CAD to SimReady, source asset to simulation-ready USD, or prop packaging that require conversion, material/physics assignment, SimReady conformance, validation

  Skill
• physical-ai-physics-selection

  Choose a physics engine and integration for robot learning, manipulation, assembly, differentiable optimization, or other Physical AI simulation. Compare Newton, PhysX, MuJoCo/MJX, Bullet/PyBullet, VSim Robotics, Genesis, and Drake. Evaluate Newton first

  Skill
• warp-eval

  Evaluate whether an existing hot path is a credible NVIDIA Warp candidate. Use for irregular or spatial queries, particle or geometry simulation, branch-heavy loops, many small launches, host fallbacks, or large intermediates. CPU-only code and absent GPU

  Skill