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System administrator-level technical information

Error

This section represents old content from the <= v4.x FAQ that has not been properly converted to the new-style documentation. The content here was perfunctorily converted to RST, but it still needs to be:

  1. Converted from a question-and-answer style to a regular documentation style (like the rest of these docs).
  2. Removed from this section and folded into other sections in these docs.

To be clear, this section will eventually be deleted; do not write any new content in this section.

I'm a sysadmin; what do I care about Open MPI?

Several members of the Open MPI team have strong system administrator backgrounds; we recognize the value of having software that is friendly to system administrators. Here are some of the reasons that Open MPI is attractive for system administrators:

  • Simple, standards-based installation
  • Reduction of the number of MPI installations
  • Ability to set system-level and user-level parameters
  • Scriptable information sources about the Open MPI installation

See the rest of the questions in this FAQ section for more details.

Do I need multiple Open MPI installations?

Yes and no.

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. 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":

      1. The C constants MPI_F_STATUS_IGNORE and MPI_F_STATUSES_IGNORE

        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.

What are MCA Parameters? Why would I set them?

MCA parameters are a way to tweak Open MPI's behavior at run-time. For example, MCA parameters can specify:

  • Which interconnect networks to use
  • Which interconnect networks not to use
  • The size difference between eager sends and rendezvous protocol sends
  • How many registered buffers to pre-pin (e.g., for InfiniBand)
  • The size of the pre-pinned registered buffers
  • ...etc.

It can be quite valuable for a system administrator to play with such values a bit and find an "optimal" setting for a particular operating environment. These values can then be set in a global text file that all users will, by default, inherit when they run Open MPI jobs.

For example, say that you have a cluster with 2 ethernet networks one for NFS and other system-level operations, and one for MPI jobs. The system administrator can tell Open MPI to not use the NFS TCP network at a system level, such that when users invoke mpirun or mpiexec to launch their jobs, they will automatically only be using the network meant for MPI jobs.

See how to set MCA params <label-running-setting-mca-param-values> for information on how to set global MCA parameters.

Do my users need to have their own installation of Open MPI?

Usually not. It is typically sufficient for a single Open MPI installation (or perhaps a small number of Open MPI installations, depending on compiler interoperability) to serve an entire parallel operating environment.

Indeed, a system-wide Open MPI installation can be customized on a per-user basis in two important ways:

  • Per-user MCA parameters: Each user can set their own set of MCA parameters, potentially overriding system-wide defaults.
  • Per-user plug-ins: Users can install their own Open MPI plug-ins under $HOME/.openmpi/components. Hence, developers can experiment with new components without destabilizing the rest of the users on the system. Or power users can download 3rd party components (perhaps even research-quality components) without affecting other users.

I have power users who will want to override my global MCA parameters; is this possible?

Absolutely.

See how to set MCA params <label-running-setting-mca-param-values> for information how to set MCA parameters, both at the system level and on a per-user (or per-MPI-job) basis.

What MCA parameters should I, the system administrator, set?

This is a difficult question and depends on both your specific parallel setup and the applications that typically run there.

The best thing to do is to use the ompi_info command to see what parameters are available and relevant to you. Specifically, ompi_info can be used to show all the parameters that are available for each plug-in. Two common places that system administrators like to tweak are:

  • Only allow specific networks: Say you have a cluster with a high-speed interconnect (such as InfiniBand) and a low-speed ethernet network (e.g., 1Gpbps). The high-speed network is intended for MPI jobs; the control network is intended for NFS and other administrative-level tasks. In this case, you can simply turn off Open MPI's TCP support. The btl framework contains Open MPI's network support; in this case, you want to disable the tcp plug-in. You can do this by adding the following line in the file $prefix/etc/openmpi-mca-params.conf:

    btl = ^tcp

    This tells Open MPI to load all BTL components except tcp.

    Consider another example: your cluster has two TCP networks, one for NFS and administration-level jobs, and another for MPI jobs. You can tell Open MPI to ignore the TCP network used by NFS by adding the following line in the file $prefix/etc/openmpi-mca-params.conf:

    btl_tcp_if_exclude = lo,eth0

    The value of this parameter is the device names to exclude. In this case, we're excluding lo (localhost, because Open MPI has its own internal loopback device) and eth0.

  • Tune the parameters for specific networks: Each network plug-in has a variety of different tunable parameters. Use the ompi_info command to see what is available. You show all available parameters with:

    shell$ ompi_info --param all all

    Note

    Starting with Open MPI v1.8, ompi_info categorizes its parameters in levels, as defined by the MPI_T interface from the MPI standard. You will need to specify --level 9 (or --all) to show all MCA parameters. See this blog entry for further information.

    shell$ ompi_info --level 9
# or
shell$ ompi_info --all

    Beware: there are many variables available. You can limit the output by showing all the parameters in a specific framework or in a specific plug-in with the command line parameters:

    shell$ ompi_info --param btl all --level 9

    Shows all the parameters of all BTL components, and:

    shell$ ompi_info --param btl tcp --level 9

    Shows all the parameters of just the tcp BTL component.

I just added a new plugin to my Open MPI installation; do I need to recompile all my MPI apps?

If your installation of Open MPI uses shared libraries and components are standalone plug-in files, then no. If you add a new component (such as support for a new network), Open MPI will simply open the new plugin at run-time your applications do not need to be recompiled or re-linked.

I just upgraded my InfiniBand network; do I need to recompile all my MPI apps?

If your installation of Open MPI uses shared libraries and components are standalone plug-in files, then no. You simply need to recompile the Open MPI components that support that network and re-install them.

More specifically, Open MPI shifts the dependency on the underlying network away from the MPI applications and to the Open MPI plug-ins. This is a major advantage over many other MPI implementations.

MPI applications will simply open the new plugin when they run.

We just upgraded our version of Open MPI; do I need to recompile all my MPI apps?

It depends on which version of Open MPI your applications were initially compiled against and the target version of Open MPI to which you upgraded.

See the section on Open MPI's version numbering scheme </version-numbering> for more information.

I have an MPI application compiled for another MPI; will it work with Open MPI?

It is strongly unlikely. Open MPI does not attempt to interface to other MPI implementations, nor executables that were compiled for them. Sorry!

MPI applications need to be compiled and linked with Open MPI in order to run under Open MPI.