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Call for Co-Authors

Paper: From OpenUSD to DSX: NVIDIA's Modular Physical-Simulation Infrastructure for Digital Twins, Robotics, and AI Factories

Status: Working draft — actively seeking contributors

What This Paper Is About

This paper argues that NVIDIA's physical-simulation offering is best understood as a layered infrastructure — not a monolithic Omniverse application. The analysis combines a documentation-grounded architecture review, a development timeline, and three comparative case studies (DSX for AI factories, robotics via Isaac Sim and Newton, and CAE/CFD via Kit-CAE).

The central result is that NVIDIA's industrial significance lies in connecting interoperable scene data (OpenUSD), GPU-native simulation, and blueprint-packaged deployment rather than in any single simulator considered in isolation.

Why We Need Co-Authors

The current draft is written primarily from a systems architecture perspective. To make the paper genuinely useful to the community, we need domain depth that one author can't provide alone.

Open Contribution Areas

High Priority

Area What's Needed Ideal Contributor
OpenUSD standards & AOUSD Governance process details, spec evolution timeline, cross-vendor adoption data, interoperability testing results USD/AOUSD working group members, DCC tool developers
DSX production deployment Real-world deployment experiences, scaling observations, integration patterns, operational challenges Data center engineers, NVIDIA partners, infrastructure teams
Robotics workflows Sim-to-real transfer benchmarks, Isaac Lab training results, OSMO orchestration at scale Robotics researchers, Isaac Sim users, Physical AI teams
CAE/CFD digital twins PhysicsNeMo surrogate model accuracy data, Kit-CAE production readiness assessment, solver comparison CAE engineers, CFD researchers, ISVs

Valuable Additions

Area What's Needed Ideal Contributor
Newton & Warp benchmarking Performance comparisons, differentiable simulation use cases, integration examples Physics simulation researchers
Competitor analysis Structured comparison with Unity, MuJoCo ecosystem, Gazebo, cloud digital twin platforms Anyone with cross-platform experience
Industry adoption patterns How organizations are actually adopting (or struggling to adopt) this stack Enterprise users, system integrators, consultants
App Streaming & browser delivery Latency measurements, scalability data, user experience studies Infrastructure engineers, UX researchers

How to Contribute

Option 1: Full co-authorship

You contribute a section or case study and are listed as a co-author.

  1. Open an issue in this repo titled [Paper] Contribution: <your topic>
  2. Describe what you can contribute and your background
  3. We'll coordinate on scope, timeline, and the section outline
  4. You write the section; we integrate and align with the overall argument
  5. All co-authors review the final draft before submission

Option 2: Technical review

You review the draft and provide substantive feedback.

  1. Read the current draft
  2. Open issues for factual errors, missing nuances, or structural suggestions
  3. Reviewers are acknowledged in the paper

Option 3: Data or evidence contribution

You contribute data, benchmarks, or case evidence that strengthens the analysis.

  1. Open a PR adding your data to the paper/data/ directory
  2. Include a brief description of methodology and context
  3. Contributors are acknowledged; substantial contributions may warrant co-authorship

Ground Rules

  • Documentation-grounded: Claims must be traceable to official docs, published benchmarks, or described methodology. No unsourced marketing claims.
  • Balanced tone: The paper is analytical, not promotional. Honest assessment of maturity and limitations is as important as describing capabilities.
  • Open process: All contributions happen through GitHub issues and PRs. No private side channels for paper content.
  • Publication target: We're aiming for a venue that reaches both the simulation/digital-twin community and the broader AI infrastructure audience. Specific venue TBD based on final scope.

Current Draft

The working draft is available at draft.md. It represents the paper's current state and is subject to significant revision as co-authors join.

Timeline

Phase Target
Call for co-authors opens Now
Co-author onboarding & scope alignment 4 weeks
Section drafts due 8 weeks
Internal review & integration 10 weeks
Final draft for submission 12 weeks

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