Engineering simulation,
10× faster.
To power the next decade of engineering simulation — where every design is run a thousand times, not once.
- 5×
- OpenFOAM GPU
- 10×+
- CPU node · HBM
Validated cell-by-cell against OpenFOAM v2412. Built on CUDA 13.
- OpenFOAM v2412
- CUDA 13
Installation
brae is production-ready on NVIDIA GPUs, run it on your workstation, a cluster, or the cloud, and drops straight into your existing OpenFOAM workflow. One command to install:
curl -fsSL https://brae.sh/install.sh | shRequires NVIDIA GPU · CUDA 12.4
The whole solve stays on the GPU.
Mesh, fields, pressure–velocity coupling, every linear solve, on the device from the first iteration to the last.
Offload solvers rebuild the matrix on the CPU and copy it across every step. That migration tax is what brae doesn't pay.
The honest chart.
simpleFoam, motorBike, 35M cells. Measured on a single NVIDIA GB10.
Solver runtime — normalized, lower is better
same GPU · same case
- 5× faster
- Parity
Engineering is becoming continuous simulation.
Simulation moved from a final check to the core design loop. Optimization, generative design, digital twins, and now AI surrogate training don't run a case once, they run it thousands of times. CPU clusters can't keep up on cost, power, or wall-clock.
No 1,000-core cluster.
One GPU.
A CFD run that ties up a CPU cluster, with its licenses, power draw, and queue times, runs on a single GPU in your workstation. Same physics, validated to under 1% of OpenFOAM. Faster wall-clock, a fraction of the energy, none of the cluster.
- Same accuracy
- Validated field-by-field against OpenFOAM v2412, to under 1%.
- Faster
- 5× OpenFOAM's GPU path. An order of magnitude over a CPU node on HBM.
- Cheaper & greener
- ~3× the simulation-per-watt of a CPU socket. One box replaces a rack.