These commands run without issue (after cloning the repo):
git submodule update --init --recursive
mkdir -p build; cd build
My error occurs after this command, and is related to the version of cmake:
cmake -DCMAKE_BUILD_TYPE=Release -DENABLE_USER=YES -DEigen3_DIR=$EIGEN_BASE/share/eigen3/cmake -DCMAKE_INSTALL_PREFIX=$HOME -Wno-dev ..
CMake Error at CMakeLists.txt:1 (cmake_minimum_required):
CMake 3.21 or higher is required. You are running version 3.16.3
-- Configuring incomplete, errors occurred!
Thank you in advance for any help you can give!
Dylan Nelson
9 Aug
I guess you can install (from source) a newer version of cmake (into your home directory).
However the EXP configuration states that such a version is required for CUDA, MPI, and other functionality - of course, none of this is possible in the Lab. For running such a complex piece of software, probably you are better off using your own compute resources, and downloading (a subset of) the TNG data that you need to do so.
Neil Ash
9 Aug
Thank you Dylan! I had a feeling that was the best option. I believe that my intended use case is not computationally intensive, but I will speak with the EXP team to find out whether this is the case.
Hello,
I am trying to install the EXP code within the JupyterLab workspace. I follow the recommended installation steps as outlined in their installation guide here:
https://exp-docs.readthedocs.io/en/latest/intro/install.html
These commands run without issue (after cloning the repo):
My error occurs after this command, and is related to the version of cmake:
Thank you in advance for any help you can give!
I guess you can install (from source) a newer version of cmake (into your home directory).
However the EXP configuration states that such a version is required for CUDA, MPI, and other functionality - of course, none of this is possible in the Lab. For running such a complex piece of software, probably you are better off using your own compute resources, and downloading (a subset of) the TNG data that you need to do so.
Thank you Dylan! I had a feeling that was the best option. I believe that my intended use case is not computationally intensive, but I will speak with the EXP team to find out whether this is the case.