Egg aims to be an excellent grid generator.

Very early WIP.

A structured multi-block grid generator with a TMOP-style mesh smoother / untangler. Written as a C++23 core and a python driver. AdaptiveCpp SYCL compute for performance portable kernels from one source (OMP, ROCm, CUDA).

NOTE: AI has been used heavily to get this to a proof-of-concept working state.

Everything else (topology, geometry, TFI init, projection, visualization, pipeline orchestration) stays in Python.

For now, see DEVELOPING.md to get started.

The circle demos accept --device {auto,cpu,gpu} to select the SYCL device:

# CPU
uv run examples/circles/good-topo.py --tmop-sweeps 40 --device cpu
uv run examples/circles/untangle.py --tmop-sweeps 1000 --device cpu

# GPU
uv run examples/circles/good-topo.py --tmop-sweeps 40 --device gpu
uv run examples/circles/untangle.py --tmop-sweeps 1000 --device gpu

Common flags: --plot-live (PyVista animation), --plot-grid (matplotlib wireframe), --chunk N. Without a plot flag the demo runs headless and prints per-chunk progress.

A generic AdaptiveCpp build exposes all visible SYCL devices (the OpenMP host and the GPU). Use ACPP_VISIBILITY_MASK to restrict which backends are loaded:

# Force CPU only
ACPP_VISIBILITY_MASK=omp uv run ...

# Force GPU only (AMD)
ACPP_VISIBILITY_MASK=hip uv run ...

Set OMP_NUM_THREADS=N to control CPU parallelism.

These should be taken with a grain of salt for now. They are mostly AI generated, but have proved useful in the development so far.

# Python tests (C++-dependent tests skip if cpp_core is not built)
ACPP_VISIBILITY_MASK=omp uv run pytest tests/

# C++ unit tests (Boost.UT)
ctest --test-dir build

Parity tests cross-check the C++ sweep / untangle against the NumPy sequential solver (local_relaxation_sweep), on both CPU and GPU.