4.11. Installation location

A common environment to run Open MPI is in a “Beowulf”-class or similar cluster (e.g., a bunch of 1U servers in a bunch of racks). Simply stated, Open MPI can run on a group of servers or workstations connected by a network. As mentioned in the prerequisites section there are several caveats however (for example, you typically must have an account on all the machines, you can ssh between the nodes without using a password, etc.).

Regardless of whether Open MPI is installed on a shared / networked filesystem or independently on each node, it is usually easiest if Open MPI is available in the same filesystem path on every node. For example, if you install Open MPI to /opt/openmpi-|ompi_ver| on one node, ensure that it is available in /opt/openmpi-|ompi_ver| on all nodes.


For simplicity, the Open MPI team strongly recommends that you install Open MPI at the same path location on all nodes in your cluster. This greatly simplifies the user experience of running MPI jobs across multiple nodes in your cluster.

It is possible to install Open MPI in unique path locations in the different nodes in your cluster, but it is not advisable.

This raises the question for Open MPI system administrators: where to install the Open MPI binaries, header files, etc.? This discussion mainly addresses this question for homogeneous clusters (i.e., where all nodes and operating systems are the same), although elements of this discussion apply to heterogeneous clusters as well.

4.11.1. Filesystem types

There are two common approaches. Network filesystem

Have a common filesystem, such as NFS, between all the machines to be used. Install Open MPI such that the installation directory is the same value on each node. This will greatly simplify user’s shell startup scripts (e.g., .bashrc, .cshrc, .profile etc.) — the PATH can be set without checking which machine the user is on. It also simplifies the system administrator’s job; when the time comes to patch or otherwise upgrade Open MPI, only one copy needs to be modified.

For example, consider a cluster of four machines: inky, blinky, pinky, and clyde.

  • Install Open MPI on inky’s local hard drive in the directory /opt/openmpi-VERSION. The system administrator then mounts inky:/opt/openmpi-VERSION on the remaining three machines, such that /opt/openmpi-VERSION on all machines is effectively “the same”. That is, the following directories all contain the Open MPI installation:

  • Install Open MPI on inky’s local hard drive in the directory /usr/local/openmpi-VERSION. The system administrator then mounts inky:/usr/local/openmpi-VERSION on all four machines in some other common location, such as /opt/openmpi-VERSION (a symbolic link can be installed on inky instead of a mount point for efficiency). This strategy is typically used for environments where one tree is NFS exported, but another tree is typically used for the location of actual installation. For example, the following directories all contain the Open MPI installation:


    Notice that there are the same four directories as the previous example, but on inky, the directory is actually located in /usr/local/openmpi-VERSION.

There is a bit of a disadvantage in this approach; each of the remote nodes have to incur NFS (or whatever filesystem is used) delays to access the Open MPI directory tree. However, both the administration ease and low cost (relatively speaking) of using a networked file system usually greatly outweighs the cost. Indeed, once an MPI application is past MPI initialization, it doesn’t use the Open MPI binaries very much. Local filesystem

If you are concerned with networked filesystem costs of accessing the Open MPI binaries, you can install Open MPI on the local hard drive of each node in your system. Again, it is highly advisable to install Open MPI in the same directory on each node so that each user’s PATH can be set to the same value, regardless of the node that a user has logged on to.

This approach will save some network latency of accessing the Open MPI binaries, but is typically only used where users are very concerned about squeezing every single cycle out of their machines, or are running at extreme scale where a networked filesystem may get overwhelmed by filesystem requests for Open MPI binaries when running very large parallel jobs.

4.11.2. Installing over a prior Open MPI installation


The Open MPI team does not recommend installing a new version of Open MPI over an existing / older installation of Open MPI.

In its default configuration, an Open MPI installation consists of several shared libraries, header files, executables, and plugins (dynamic shared objects — DSOs). These installation files act together as a single entity. The specific filenames and contents of these files are subject to change between different versions of Open MPI.


Installing one version of Open MPI does not uninstall another version.

If you install a new version of Open MPI over an older version, this may not overwrite all the files from the older version. Hence, you may end up with an incompatible muddle of files from two different installations — which can cause problems.

See updating Open MPI for more information about updating or upgrading an installation of Open MPI.

4.11.3. Relocating an Open MPI installation

It can be desirable to initially install Open MPI to one location (e.g., /path/to/openmpi) and then later move it to another location (e.g., /opt/myproduct/bundled-openmpi-a.b.c).


Open MPI hard-codes some directory paths in its executables based on installation paths specified by the configure script. For example, if you configure with an installation prefix of /opt/openmpi/, Open MPI encodes in its executables that it should be able to find its help files in /opt/openmpi/share/openmpi.

The “installdirs” functionality in Open MPI lets you change any of these hard-coded directory paths at run time (assuming that you have already adjusted your PATH and/or LD_LIBRARY_PATH environment variables to the new location where Open MPI now resides).

There are three methods. Move an existing Open MPI installation to a new prefix

Set the OPAL_PREFIX environment variable before launching Open MPI. For example, if Open MPI had initially been installed to /opt/openmpi and the entire openmpi tree was later moved to /home/openmpi, setting OPAL_PREFIX to /home/openmpi will enable Open MPI to function properly. “Stage” an Open MPI installation in a temporary location

When creating self-contained installation packages, systems such as RPM install Open MPI into temporary locations. The package system then bundles up everything under the temporary location into a package that can be installed into its real location later. For example, when creating an RPM that will be installed to /opt/openmpi, the RPM system will transparently prepend a “destination directory” (or “destdir”) to the installation directory. As such, Open MPI will think that it is installed in /opt/openmpi, but it is actually temporarily installed in (for example) /var/rpm/build.1234/opt/openmpi. If it is necessary to use Open MPI while it is installed in this staging area, the OPAL_DESTDIR environment variable can be used; setting OPAL_DESTDIR to /var/rpm/build.1234 will automatically prefix every directory such that Open MPI can function properly. Overriding individual directories

Open MPI uses the GNU-specified directories (per Autoconf/Automake), and can be overridden by setting environment variables directly related to their common names. The list of environment variables that can be used is:


















Note that not all of the directories listed above are used by Open MPI; they are listed here in entirety for completeness.

Also note that several directories listed above are defined in terms of other directories. For example, the $bindir is defined by default as $prefix/bin. Hence, overriding the $prefix (via OPAL_PREFIX) will automatically change the first part of the $bindir (which is how method 1 described above works). Alternatively, OPAL_BINDIR can be set to an absolute value that ignores $prefix altogether.

4.11.4. Installing Multiple Copies of Open MPI

Open MPI can handle a variety of different run-time environments (e.g., ssh, Slurm, PBS, etc.) and a variety of different interconnection networks (e.g., ethernet, InfiniBand, etc.) in a single installation. Specifically: because Open MPI is fundamentally powered by a component architecture, plug-ins for all these different run-time systems and interconnect networks can be installed in a single installation tree. The relevant plug-ins will only be used in the environments where they make sense.

Hence, there is no need to have one MPI installation for InfiniBand, one MPI installation for ethernet, one MPI installation for PBS, one MPI installation for ssh, etc. Open MPI can handle all of these in a single installation.

However, there are some issues that Open MPI cannot solve. Binary compatibility between different compilers is such an issue and may require installation of multiple versions of Open MPI.

Let’s examine this on a per-language basis (be sure see the big caveat at the end):

  • C: Most C compilers are fairly compatible, such that if you compile Open MPI with one C library and link it to an application that was compiled with a different C compiler, everything should “just work.” As such, a single installation of Open MPI should work for most C MPI applications.

  • C++: The same is not necessarily true for C++. While Open MPI does not currently contain any C++ code (the MPI C++ bindings were removed in a prior release), and C++ compilers should produce ABI-equivalent code for C symbols, obscure problem can sometimes arise when mixing compilers from different suites. For example, if you compile Open MPI with the XYZ C/C++ compiler, you may need to have the XYC C++ run-time libraries installed everywhere you want to run.

  • Fortran: There are multiple issues with Fortran.

    1. Fortran compilers do something called “symbol mangling,” meaning that the back-end symbols may have slightly different names than their corresponding global variables, subroutines, and functions. There are 4 common name mangling schemes in use by Fortran compilers. On many systems (e.g., Linux), Open MPI will automatically support all 4 schemes. As such, a single Open MPI installation should just work with multiple different Fortran compilers. However, on some systems, this is not possible (e.g., OS X), and Open MPI will only support the name mangling scheme of the Fortran compiler that was identified during configure.

    2. That being said, there are two notable exceptions that do not work across Fortran compilers that are “different enough”:


        will only compare properly to Fortran applications that were created with Fortran compilers that that use the same name-mangling scheme as the Fortran compiler with which Open MPI was configured.

      2. Fortran compilers may have different values for the logical

        .TRUE. constant. As such, any MPI function that uses the Fortran LOGICAL type may only get .TRUE. values back that correspond to the the .TRUE. value of the Fortran compiler with which Open MPI was configured.

    3. Similar to C++, linking object files that Fortran language features such as modules and/or polymorphism from different Fortran compilers is not likely to work. The mpi and mpi_f08 modules that Open MPI creates will likely only work with the Fortran compiler that was identified during configure (and used to build Open MPI).

The big caveat to all of this is that Open MPI will only work with different compilers if all the datatype sizes are the same. For example, even though Open MPI supports all 4 name mangling schemes, the size of the Fortran LOGICAL type may be 1 byte in some compilers and 4 bytes in others. This will likely cause Open MPI to perform unpredictably.

The bottom line is that Open MPI can support all manner of run-time systems and interconnects in a single installation, but supporting multiple compilers “sort of” works (i.e., is subject to trial and error) in some cases, and definitely does not work in other cases. There’s unfortunately little that we can do about this — it’s a compiler compatibility issue, and one that compiler authors have little incentive to resolve.