Installation¶
Requirements¶
- Python 3.11+
- Palace EM simulation software
Optional:
- COBRA installed/importable if you use ORCA surrogate outputs in circuit optimization
Note
ORCA supports Python 3.11 to 3.14.
Clone Repository¶
Install ORCA¶
or explicitly:
To pick a specific PyTorch build, use uv sync with one of the build selectors from pyproject.toml instead of uv pip install:
pip installs the PyPI build of PyTorch (CUDA-bundled on Linux). For a CPU-only or a specific CUDA build, install torch first with the command from PyTorch.org; pip then keeps that version.
Simulation-only install
PyTorch and the other model-training packages are an optional extra. If you only want to generate layouts and run Palace simulations — on an HPC cluster, say — drop the [train] extra: pip install -e .. GDSGenerator, GDSConverter and PalaceSimulator work without it; ModelTrainer, OnnxExporter and ModelTester report the missing packages when used.
Verify Setup¶
Run the following check in your activated environment:
Expected behavior: ORCA GUI starts.
To verify the script workflow:
Warning
examples/main.py requires a working Palace installation and a valid geometry configuration.
External Tool Notes¶
Palace¶
- ORCA uses Palace as the EM simulation backend.
- Install Palace by following the official Palace installation instructions.
- Palace can be run directly or via an Apptainer/Singularity container.
COBRA (Optional)¶
- COBRA consumes ONNX surrogate models exported by ORCA for circuit-level optimization.
- See COBRA documentation for details.
Next Steps¶
- Continue with Getting Started -> Quickstart for a first run.
- Use User Guide -> Custom Classes to bring your own geometry.