Installing and Using LEAP - LLNL/LEAP GitHub Wiki
Dependencies
To use LEAP, you must install the following packages
CUDA toolkit 11.7 or newer (See section below about compiling without a GPU or on Mac)
Linux: gcc compiler
Windows: Visual Studio 2019 (be sure to check the box that says "Desktop development with C++")
Installation
To install LEAP package, use pip command:
$ pip install .
It is strongly recommended to run "pip uninstall leapct" if you have installed the previous version. If you run into an installation error, please re-run the install with the "-v" argument, i.e.,
$ pip install -v .
If this doesn't help resolve your issue, please open an issue and we'll see if we can help.
Installation on Livermore Computing (Intel/Linux)
To install LEAP on Livermore Computing, proper modules should be loaded first. To enable GPU features, the installation should be performed under the compute node where nvidia-smi is available. For example,
$ salloc --partition=pbatch --time=1:00:00
$ module load gcc/8.3.0
$ module load cuda/11.7.0
$ pip install .
Installation on Livermore Computing (IBM PowerAI)
$ bsub -G mlct -W 1:00 -Is bash
$ module load gcc/8.3.0
$ module load cuda/11.7.0
$ pip install .
Building without a GPU or on Mac
If you are building on a Mac, you will have to install gcc. First, you need to swap the CMake file by renaming cpu_CMakeLists.txt to CMakeLists.txt (in the src folder). Then you can follow any of the install instructions above.
Usage
Please see our example scripts in the demo_leaptorch directory.
We also highly recommend looking at the example scripts in the demo_leapctype directory. These contain examples of specifying other geometries and other use cases.