Pawsey provides and maintains a number of prebuilt libraries and applications on Setonix, most of which are installed and managed through Spack. This page outlines how users can use Spack to install additional software or different builds of existing software that are not provided by Pawsey supported modules.
Before you begin
Read Software Stack Policies before proceeding with any local installations.
Before using Spack to install a package, run the following command to check whether it is already available:
module avail <package-name>
To familiarise yourself with Spack features and concepts, read the Spack documentation (external site).
Please keep in mind that versions listed in examples may change as new software stacks are deployed.
Motivation for using Spack
Spack provides a simple interface for installing packages. Amongst other benefits, Spack provides human-readable installation commands, is able to automatically build the dependency tree for a large number of packages, and allows different installation configurations to be selected. As a result, Spack lessens the need to know the variety of installation procedures in use, such as automake
and cmake
.
Spack at Pawsey
Spack has been configured by Pawsey staff to work out of the box for most usage scenarios. In particular, the following aspects have been tuned:
- Usage of available compilers
- Usage of available performance libraries
- Awareness of system-wide packages
- Directory trees for installed packages and modules
- Naming convention and features of generated modulefiles
Spack is used at Pawsey to deploy a significant fraction of the scientific software stack including HPC applications and HPC libraries, as well as some compilers and utilities.
Installing Python and R packages
The Spack setup at Pawsey is capable of handling both system-wide and user package installations. However, the current implementation does not properly generate user modulefiles for interpreted languages such as Python and R.
For Python package installations, we recommend using pip or setuptools, see: Installing Python Packages
For R package installations, we recommend using the R package manager, see: Installing R Packages
Installing GPU applications
The 0.17.0 version of Spack currently deployed on Setonix does not support installations of applications depending on ROCm, the AMD GPU computing platform. We will soon deploy a new software stack with a more recent version of Spack.
Using Spack
First, the Spack module has to be loaded:
$ module load spack/0.21.0
Users can invoke Spack with the spack
command. spack
accepts a subcommand, or Spack command, as the first argument:
$ spack <subcommand>
Use the following subcommands in order:
- Use
list
to look for package recipes. - Use
info
to inspect available options for a given package. Use
spec
to test installation and required dependencies for a given package.Always test an installation with
spec
before runninginstall
.- Finally, proceed with the
install
subcommand for a given package.
A comprehensive list of Spack commands can be inspected by using variations of the help
subcommand.
$ spack help
$ spack help --all
$ spack <subcommand> -h
Solving the "Disk Quota Exceeded' error
All spack install ...
commands, and any other command generating files on the /software
filesystem, must be executed using the sg
Linux utility to make sure the process is run with the correct group ID. All files under /software
must have the Linux group of the project they are created by, to contribute towards the correct quota limit. If you fail to do so, these files are accounted for in your personal quote that is meant to limit /home
usage and is much more limited. The syntax is the following:
sg <yourprojectcode> -c 'spack install <spec>'
.
For instance, Pawsey staff may install the namd
scientific software using the command
sg pawsey0001 -c 'spack install namd'.
Example installation process with NAMD
Suppose we want to install the NAMD software for molecular dynamics simulations. First, let's search Spack for an appropriate package.
$ spack list namd ==> 1 packages. namd
Spack has found one package called namd
. It sounds like it's the one we're looking for.
The namd
package in Spack has several build time options and dependencies. These options can be explored by using the info
subcommand.
$ spack info namd MakefilePackage: namd Description: NAMD is a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems. Homepage: http://www.ks.uiuc.edu/Research/namd/ Tags: None Preferred version: 2.14 file:///group/pawsey0001/mulan/spack-builds/spack/bin/NAMD_2.14_Source.tar.gz Safe versions: master [git] https://charm.cs.illinois.edu/gerrit/namd.git on branch master 2.15a1 [git] https://charm.cs.illinois.edu/gerrit/namd.git at tag release-2-15-alpha-1 2.14 file:///group/pawsey0001/mulan/spack-builds/spack/bin/NAMD_2.14_Source.tar.gz 2.13 file:///group/pawsey0001/mulan/spack-builds/spack/bin/NAMD_2.13_Source.tar.gz 2.12 file:///group/pawsey0001/mulan/spack-builds/spack/bin/NAMD_2.12_Source.tar.gz Variants: Name [Default] Allowed values Description ================ ==================== ============================================ cuda [off] on, off Build with CUDA cuda_arch [none] none, 52, 12, 61, CUDA architecture 37, 60, 30, 11, 10, 20, 86, 35, 72, 62, 70, 13, 53, 32, 50, 75, 80, 21 fftw [3] none, 2, 3, mkl, Enable the use of FFTW/FFTW3/MKL FFT/AMDFFTW amdfftw interface [none] none, tcl, python Enables TCL and/or python interface Installation Phases: edit build install Build Dependencies: amdfftw charmpp cuda fftw intel-mkl python tcl Link Dependencies: amdfftw charmpp cuda fftw intel-mkl python tcl Run Dependencies: None Virtual Packages: None
The info
output lists the build time options under Variants
, along with the build and link dependencies of the package.
The dependencies required can be explored by running the spec
subcommand:
$ spack spec namd # default installation of namd and the libraries it depends on Input spec -------------------------------- namd Concretized -------------------------------- namd@2.14%gcc@11.2.0~cuda cuda_arch=none fftw=3 interface=none patches=cdcbc3846be1dfd6dbf958177c703e15ef5343e1461ed68d02be8fd0512429d5 arch=linux-sles15-zen3 ^charmpp@6.10.2%gcc@11.2.0~cuda~omp~papi+production~pthreads+shared+smp~syncft~tcp~tracing backend=netlrts build-target=LIBS pmi=none arch=linux-sles15-zen3 ^fftw@3.3.8.8%gcc@11.2.0+mpi~openmp~pfft_patches precision=double,float arch=linux-sles15-zen3
Spack will produce the default installation, listing for each package that needs to be installed the full compilation options. Focusing on namd
, Spack reports the following information:
- The package and version (
namd@2.14)
- The compiler and version (
%gcc@11.2.0
) - Information related to the variants and the architecture that the package will be built for (in this example, the linux-sles15 operating system using the zen3 CPU architecture)
Variants are listed with the following specifiers:
+
indicates that the compilation option is enabled~
(no prepending space) or-
(with prepending space) indicate that the compilation option is disabled- Variants with multiple values are listed as
option_name=value
In this case, when namd
is compiled cuda
is disabled, fftw
is set to 3 (use fftw3
library) and no interface has been used.
Dependencies are preceded by a ^
. For instance, here namd
depends on charmpp@6.10.2
and fftw@3.3.8.8
, with each dependency listing which compiler and variants it will be built with.
Explore changes in the build process with spec
by adding the variants to the package name.
$ spack spec namd +cuda fftw=mkl interface=python #setting a specific variant Input spec -------------------------------- namd+cuda fftw=mkl interface=python Concretized -------------------------------- namd@2.14%gcc@11.2.0+cuda cuda_arch=none fftw=mkl interface=python patches=cdcbc3846be1dfd6dbf958177c703e15ef5343e1461ed68d02be8fd0512429d5 arch=linux-sles15-zen3 ^charmpp@6.10.2%gcc@11.2.0~cuda~omp~papi+production~pthreads+shared+smp~syncft~tcp~tracing backend=netlrts build-target=LIBS pmi=none arch=linux-sles15-zen3 ^cuda@11.3.0%gcc@11.2.0~dev arch=linux-sles15-zen3 ^libxml2@2.9.10%gcc@11.2.0~python arch=linux-sles15-zen3 ^libiconv@1.16%gcc@11.2.0 arch=linux-sles15-zen3 ^pkgconf@1.4.2%gcc@11.2.0 arch=linux-sles15-zen3 ^xz@5.2.4%gcc@11.2.0~pic libs=shared,static arch=linux-sles15-zen3 ^zlib@1.2.11%gcc@11.2.0+optimize+pic+shared arch=linux-sles15-zen3 ^intel-mkl@2020.4.304%gcc@11.2.0~ilp64+shared threads=none arch=linux-sles15-zen3 ^cpio@2.12%gcc@11.2.0 patches=d22633c368b8aedf4c08b23b6fbaa81a52404c8943ab04926404083ac10f1a4b arch=linux-sles15-zen3 ^python@3.6.13%gcc@11.2.0+bz2+ctypes+dbm~debug+libxml2+lzma+nis~optimizations+pic+pyexpat+pythoncmd+readline+shared+sqlite3+ssl~tix~tkinter~ucs4+uuid+zlib arch=linux-sles15-zen3 ^tcl@8.6.11%gcc@11.2.0 arch=linux-sles15-zen3
Finally, install the package.
The spack
command shown in terminal 5 will try to install and build all of the required packages in the user location configured by Pawsey, which is:
/software/projects/<project-id>/<user-id>/setonix/software/<arch>/<compiler>/<package>-<version>-<unique_hash>
In this example:
<arch> = linux-sles15-zen3
<compiler> = gcc-11.2.0
<package>-<version>-<unique_hash> = namd-2.12-x3jinxvmanf5dm6zujstnpalmlzi4hy5/
$ # Before install, check the spec using specific version of fftw $ spack spec namd@2.12 ~cuda fftw=3 interface=python ^fftw@3.3.4 +mpi +openmp +pfft_patches ^mpich@3.4.1 Input spec -------------------------------- namd@2.12~cuda fftw=3 interface=python ^fftw@3.3.4+mpi+openmp+pfft_patches Concretized -------------------------------- namd@2.12%gcc@11.2.0~cuda cuda_arch=none fftw=3 interface=python arch=linux-sles15-zen3 ^charmpp@6.7.1%gcc@11.2.0~cuda~omp~papi+production~pthreads+shared+smp~syncft~tcp~tracing backend=netlrts build-target=LIBS patches=92d507d8b72ac01f114f7772510049cc7656f93daeadef46e1f2b00ad8533d2b,e636c3f88a6944c87d910d4c8fdf25146b60f57e09228497a6cc01c7dbae9569 pmi=none arch=linux-sles15-zen3 ^fftw@3.3.4%gcc@11.2.0+mpi+openmp+pfft_patches patches=4c813199aa39c0d2b23259ee3c3a58c9c96a3c0d09fe3485a33f299b95e0d9e7 precision=double,float arch=linux-sles15-zen3 ^autoconf@2.69%gcc@11.2.0 arch=linux-sles15-zen3 ^automake@1.15.1%gcc@11.2.0 arch=linux-sles15-zen3 ^libtool@2.4.6%gcc@11.2.0 arch=linux-sles15-zen3 ^mpich@3.4.1%gcc@11.2.0~argobots+fortran+hwloc+hydra+libxml2+pci+romio+slurm~verbs+wrapperrpath device=ch4 netmod=ofi pmi=pmi arch=linux-sles15-zen3 ^python@3.6.13%gcc@11.2.0+bz2+ctypes+dbm~debug+libxml2+lzma+nis~optimizations+pic+pyexpat+pythoncmd+readline+shared+sqlite3+ssl~tix~tkinter~ucs4+uuid+zlib arch=linux-sles15-zen3 ^tcl@8.6.11%gcc@11.2.0 arch=linux-sles15-zen3 ^zlib@1.2.11%gcc@11.2.0+optimize+pic+shared arch=linux-sles15-zen3 $ # the spec looks okay, let's install it $ sg <projectcode> -c 'spack install namd@2.12 ~cuda fftw=3 interface=python ^fftw@3.3.4 +mpi +openmp +pfft_patches'
Spack would normally download the source code for any packages that it needs to install. The source code for NAMD has a particular restriction that it cannot be downloaded by spack
but must be obtained separately:
$ sg <projectcode> -c 'spack install namd@2.12 ~cuda fftw=3 interface=python ^fftw@3.3.4 +mpi +openmp +pfft_patches' ... ==> Installing namd-2.12-tey6bdfijoegx3dkxfc553nckfecmhku ==> No binary for namd-2.12-tey6bdfijoegx3dkxfc553nckfecmhku found: installing from source ... ==> Error: FetchError: Manual download is required for namd. Refer to http://www.ks.uiuc.edu/Research/namd/ for download instructions.
This can be addressed by first manually downloading the source tarball into your current directory where spack
will detect it.
Install a package for the entire project team
Pawsey introduced a new Spack subcommand, spack project
, to perform package installations for the entire project team, rather than just a single user.
$ spack project spec <arguments>
$ spack project install <arguments>
The key differences compared to spack
are the locations where packages are installed and modulefiles are created:
- Software:
/software/projects/<project-id>/setonix/<datetag>/software/<arch>/<compiler>/<package>-<version>-<unique_hash>
- Modulefiles:
/software/projects/<project-id>/setonix/<datetag>/modules/<cpu-arch>/<compiler-name>/<compiler-version>/<package>/<version>-<unique_hash>.lua
Install a package for different types of hardware nodes
Pawsey systems are made up of different types of hardware nodes; for instance, Setonix includes login, compute, data-mover and visualisation nodes.
If you need to install a package with Spack for usage on a specific node, the best way to proceed is to perform the installation on that specific type of node. For instance, to install applications for your HPC jobs, use a compute node via a Slurm allocation; to install a utility for the data-mover nodes, use a data-mover node.
Using Spack-installed software
Spack-installed software can be executed by any of these methods:
- Calling the executable with the full path
- Using
spack load
- Generating a modulefile with Spack and using it (recommended)
Using spack load
The load/unload
command provides a simple fashion of updating the PATH
environment variable to include software built by Spack. You can investigate the installed software using the find
subcommand and then use the load
command once you have identified the software to use. If several different versions of the package have been built by Spack, you will need to specify the desired spec:
$ spack find -vd fftw # list the variants and dependencies of fftw -- linux-sles15-zen3 / gcc@11.2.0 ----------------------------- fftw@3.3.7~mpi~openmp~pfft_patches precision=double,float fftw@3.3.7~mpi+openmp~pfft_patches precision=double,float fftw@3.3.8~mpi~openmp~pfft_patches precision=double,float $ spack load fftw # try loading any fftw ==> Error: fftw matches multiple packages. Matching packages: m4vsnhq fftw@3.3.7%gcc@11.2.0 arch=linux-sles15-zen3 ax6d2kl fftw@3.3.7%gcc@11.2.0 arch=linux-sles15-zen3 7mlxv4g fftw@3.3.8%gcc@11.2.0 arch=linux-sles15-zen3 Use a more specific spec. $ spack load fftw@3.3.7 # try loading a specific version ==> Error: fftw@3.3.7 matches multiple packages. Matching packages: m4vsnhq fftw@3.3.7%gcc@11.2.0 arch=linux-sles15-zen3 ax6d2kl fftw@3.3.7%gcc@11.2.0 arch=linux-sles15-zen3 Use a more specific spec. $ spack load fftw@3.3.7+openmp # load the version and variant that uniquely identifies the package
Once a path has been updated you can use the executable.
Generating and using a modulefile
To generate modulefiles for Spack-built packages use the idiomatic syntax below. You will then be able to see them with module avail
and use them with module load/unload
.
The spack
command shown in Terminal 8 will generate the modulefiles in the user location configured by Pawsey, which is:
/software/projects/<project-id>/<user-id>/setonix/<datetag>/modules/<cpu-arch>/<compiler-name>/<compiler-version>/<package>/<version>-<unique_hash>.lua
In this example:
<cpu-arch> = zen3
<compiler-name> = gcc
<compiler-version> = 11.2.0
$ sg <projectcode> -c 'spack module lmod refresh --delete-tree -y' # generate LUA modulefiles for Lmod ==> Regenerating lmod module files $ # list the fftw modules available $ module avail fftw fftw/3.3.7-aormek7 fftw/3.3.7-ibdoa45 fftw/3.3.8-ggtdo27 $ # load a particular fftw library $ module load fftw/3.3.7-aormek7 $ # to determine if this module is the correct variant one can examine the module file itself $ head -4 /software/projects/pawsey0xxx/user/setonix/modules/zen3/gcc/11.2.0/fftw/3.3.7-aormek7.lua | tail -1 -- fftw@3.3.7%gcc@11.2.0~mpi~openmp~pfft_patches precision=double,float arch=linux-sles15-zen3/aormek7 $ # compare this to other 3.3.7 module $ head -4 /software/projects/pawsey000x/user/setonix/modules/zen3/gcc/11.2.0/fftw/3.3.7-ibdoa45.lua | tail -1 -- fftw@3.3.7%gcc@11.2.0~mpi+openmp+pfft_patches patches=8132c27659f992311dcf3d1500056e0f9400aa22f6824124e3607dbaa8dfe3c0 precision=double,float arch=linux-sles15-zen3/ibdoa45
Installing a software package from a user-modified source code
It is quite common for users to modify or patch the code of popular applications such as LAMMPS and Gromacs. You can use Spack to install the modified code as long as there exists a recipe for it (otherwise you can always create one). Here is an example on how to install a modified Gromacs source code.
First, we need a Spack recipe that takes a tar file from the current working directory rather than the Internet (note that this is a long command so next line won't display properly in a small window):
$ cp -r /software/setonix/2023.08/spack/var/spack/repos/builtin/packages/gromacs $MYSOFTWARE/setonix/spack_repo/packages
Then open the file
$ vim $MYSOFTWARE/setonix/spack_repo/packages/gromacs/package.py
And replace the url
property with the following line
$ url = "file://{0}/gromacs.5.1.2.tar.gz".format(os.getcwd())
Now you can use spack to install your custom version. You will need to tar your code as if it were an official distribution, but name the tar file with a non-official version, for instance gromacs.5.1.2custom.tar.gz
. Then run the usual spack install command:
$ spack install gromacs@5.1.2custom
in the same directory of the tar file.
Software built with Spack
Spack makes use of dynamic libraries and rpath
when building software. The use of rpath
means that executables contain the paths in which libraries are searched for at runtime. The result of using rpath
is that runtime are reproducible as executables will always point to the same library regardless of environment at runtime. A consequence of this is that if software has been built with not the desired version and build of library, it is not easy to have the executable use a different version. The package must be rebuilt with the different version of the library.
The use of rpath
has a positive impact on the behaviour of executables provided by modules compared to Pre-Setonix systems (see Modules).
Learning more about Spack
Spack comes with a high-quality and detailed set of documentation and tutorial pages:
We recommend referring to these resources for information on topics that are not covered in this Pawsey Spack page, such as:
- Spack configuration and customisation
- Creation and debugging of packages
- Use of Spack to develop an in-house code inside a Spack environment (developer workflow)