CP2K can be built and installed with Spack. Spack is a package manager designed to support multiple versions and configurations on a wide variety of platforms and environments, with focus on HPC.

To install CP2K with Spack, you need to install Spack.

Install CP2K with Spack

A barebone version of CP2K can be installed with Spack as follows:

spack install cp2k

This command will build CP2K, as well as all the necessary dependencies. If it is the first time you run this command, building all the dependencies might take a while.

In order to use CP2K installed with Spack, you can simply type

spack load cp2k

This command will add the appropriate directories to PATH and MANPATH. See using installed Spack packages for more information.

Customizing Installation


Spack allows to fully customize an installation. The CP2K Spack package has several options for customization (called “variants”, see Spack package variants). For example, to install CP2K with libint and libxc, one can type

spack install cp2k +libint +libxc

+VARIANT will enable a boolean variant, while ~VARIANT will disable a boolean variant. Non boolean variants can be specified with the VARIANT=VALUE syntax (see Spack package variants for more details). The previous installation command takes care of building CP2K with libint and libxc support. More importantly, it takes care of building the appropriate versions of libint and libxc to work with CP2K (Fortran support, …).


Versions in Spack can be specified with @ following the package name (see [version specifier]). The following installs version 2023.2 of CP2K:

spack install cp2k@2023.2

A more complete installation of CP2K can be installed with the following:

spack install cp2k@2023.2 +libint +libxc +dlaf +sirius +cosma +spglib lmax=6 

The cp2k@2023.2 +libint +libxc +dlaf +sirius +cosma +spglib lmax=6 string is called a spec in Spack lingo.

CUDA and ROCm Support

The cuda and rocm variants are available for CP2K. Therefore, CUDA support can be enabled with +cuda and ROCm support can be enabled with +rocm. cuda_arch and amdgpu_target allow specifying the GPU architecture:

spack install cp2k +cuda cuda_arch=80
spack install cp2k +rocm amdgpu_target=gfx90a

Spack is designed to support the installation of different versions of the same software, therefore there is no problem with running both commands above. However, spack load cp2k will no longer work, you will need to be a bit more specific:

spack load cp2k +cuda

Managing Dependencies

Sometimes you need to control dependencies too. Dependencies are also Spack packages, and their installation can be configured in the same way as for CP2K. A dependency spec is defined by ^.

For example, if you want to install CP2K with CUDA support but DBCSR without CUDA support you can do

spack install cp2k +cuda cuda_arch=80 ^dbcsr ~cuda

Another example, is the choice of vendor libraries. In order to use Intel oneAPI MKL, it can be specified as a dependency:

spack install cp2k ^intel-oneapi-mkl +cluster

This command will build CP2K with Intel oneAPI MKL. +cluster is a variant of the Intel oneAPI Spack package enabling cluster support (ScaLAPACK, BLACS, …).

Developer Workflow

Spack has support for developer workflows. One way to use Spack to develop CP2K, is to use Spack to install all the necessary dependencies and then build CP2K manually.

To install only the dependencies of CP2K (and not CP2K itself) you can use

spack install --only=dependencies CP2K_SPEC

Once all dependencies are installed, you can get a shell with all the dependencies set up:

spack build-env CP2K_SPEC -- bash

From here, you can iterate CP2K development using the native build system as Spack would use it.