-
Notifications
You must be signed in to change notification settings - Fork 12
Installing and Using LEAP
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++")
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.
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 .
$ bsub -G mlct -W 1:00 -Is bash
$ module load gcc/8.3.0
$ module load cuda/11.7.0
$ pip install .
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.
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.