DimensionLab

Bounded scientific array selection, streaming statistics and reproducible storage benchmarks.

Frontier data model and dataset format: the frontier-dataset specification, the plugin contract, and reference readers/writers in Rust and Python.

Curated hub of public physics-AI datasets and benchmarks: catalog, fetchers and converters to the Frontier dataset format.

Connector plugins that turn CFD/CAE solver output (OpenFOAM, VTK, Fluent, STAR-CCM+, CGNS, LS-DYNA, ...) into Frontier datasets. Write your own in an afternoon.

Frontier Python SDK: offline-first experiment tracking for physics ML, the native Rust core, and the NVIDIA PhysicsNeMo bridge.

Editor core and GPU text view for physics-ML configs, recipes and logs: rope document, undo tree, hunks with per-hunk approval, tree-sitter syntax, JSON-Schema diagnostics, provenance events, and a wgpu renderer that draws into the host's render pass.

Statecharts as data with an event log: a pure, deterministic kernel (state, event) -> (state, effects), replay, fork, restore and explanations. no_std + alloc, runs natively and in WebAssembly. Not specific to Frontier.

GPU-accelerated (wgpu) rendering core for meshes, fields and neural-network topology: native, browser (WebGPU) and headless.

NVIDIA PhysicsNeMo plugin for DimensionLab Frontier: logging, model registry, checkpoint compatibility and dataset adapters. Installable independently of the platform.

Frontier for Zed: JSON schemas, snippets and the Frontier MCP context server for physics-ML training configs, RunSpecs, data-prep recipes, pipelines, hub entries and plugin manifests. A Zed extension (extension.toml plus a small wasm32-wasip2 crate), installable as a dev extension today and submitted to the Zed extension registry later.