11.4. Running MPI applications


11.4.1. What prerequisites are necessary for running an Open MPI job?

In general, Open MPI requires that its executables are in your PATH on every node on which you will run and if Open MPI was compiled was dynamic libraries (which is the default), the directory where its libraries are located must be in your LD_LIBRARY_PATH on every node.

For example, if Open MPI was installed with a prefix of /opt/openmpi, then the following should be in your PATH and LD_LIBRARY_PATH

Environment variable

Value to add

PATH

/opt/openmpi/bin

LD_LIBRARY_PATH

/opt/openmpi/lib

Error

TODO Josh H points out that we might also want to mention OMPIHOME for PRRTE’s .ini file here. Leaving this as a future to-do item, since PRRTE’s .ini file support does not exist yet.

Depending on your environment, you may need to set these values in your shell startup files (e.g., .bashrc, .cshrc, etc.).

Note

There are exceptions to this rule — see this FAQ entry for a description of the --prefix option to mpirun.

See this FAQ entry for more details on how to add Open MPI to your PATH and LD_LIBRARY_PATH.

Additionally, Open MPI requires that jobs can be started on remote nodes without any input from the keyboard. For example, if using ssh as the remote agent, you must have your environment setup to allow execution on remote nodes without entering a password or passphrase.


11.4.2. What ABI guarantees does Open MPI provide?

See this section for a description of Open MPI’s versioning and ABI scheme. The short version is:

  1. Open MPI is source code compatible across all versions. This means that you can compile and link your compliant MPI application against any version of Open MPI that supports the version of the MPI standard to which your application was written.

  2. Open MPI provided forward application binary interface (ABI) compatibility within a major series for MPI applications starting with v1.3.2. Prior to that version, no ABI guarantees were provided.

  3. Open MPI reserves the right to break ABI compatibility at new major release series.


11.4.3. Do I need a common filesystem on all my nodes?

No, but it certainly makes life easier if you do.

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 above, there are several prerequisites, however (for example, you typically must have an account on all the machines, you can or 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 location on every node. For example, if you install Open MPI to /opt/openmpi-$ver_current on one node, ensure that it is available in /opt/openmpi-$ver_current on all nodes.

The where to install FAQ question contains some suggestions on where to install Open MPI.


11.4.4. How do I add Open MPI to my PATH and LD_LIBRARY_PATH?

Open MPI must be able to find its executables in your PATH on every node (if Open MPI was compiled as dynamic libraries, then its library path must appear in LD_LIBRARY_PATH as well). As such, your configuration/initialization files need to add Open MPI to your PATH / LD_LIBRARY_PATH properly.

How to do this may be highly dependent upon your local configuration; you may need to consult with your local system administrator. Some system administrators take care of these details for you, some don’t. YMMV. Some common examples are included below, however.

You must have at least a minimum understanding of how your shell works to get Open MPI in your PATH / LD_LIBRARY_PATH properly. Note that Open MPI must be added to your PATH and LD_LIBRARY_PATH in the following situations:

  1. When you login to an interactive shell

    If your interactive login environment is not configured properly, executables like mpicc will not be found, and it is typically obvious what is wrong. The Open MPI executable directory can manually be added to the PATH, or the user’s startup files can be modified such that the Open MPI executables are added to the PATH every login. This latter approach is preferred.

    All shells have some kind of script file that is executed at login time to set things like PATH and LD_LIBRARY_PATH and perform other environmental setup tasks. This startup file is the one that needs to be edited to add Open MPI to the PATH and LD_LIBRARY_PATH. Consult the manual page for your shell for specific details (some shells are picky about the permissions of the startup file, for example). The table below lists some common shells and the startup files that they read/execute upon login:

    Shell

    Interactive login startup files

    bash

    .bash_profile if it exists, or .bash_login if it exists, or .profile if it exists

    (in that order). Note that some Linux distributions automatically come with

    .bash_profile scripts for users that automatically execute .bashrc as well.

    Consult the bash(1) man page for more information.

    zsh

    .zshrc followed by .zshenv

    sh (or Bash

    named sh)

    .profile

    csh

    .cshrc followed by .login

    tcsh

    .tcshrc if it exists, .cshrc if it does not, followed by .login

  2. When you login to non-interactive shells on remote nodes

    If your non-interactive remote environment is not configured properly, executables like mpirun will not function properly, and it can be somewhat confusing to figure out.

    The startup files in question here are the ones that are automatically executed for a non-interactive login on a remote node (e.g., ssh othernode ps). Note that not all shells support this, and that some shells use different files for this than listed for interactive logins. Some shells will supersede non-interactive login startup files with files for interactive logins. That is, running non-interactive login startup file may automatically invoke interactive login startup file. The following table lists some common shells and the startup file that is automatically executed, either by Open MPI or by the shell itself:

    Shell

    Non-interactive login startup files

    bash

    .bashrc if it exists

    zsh

    .zshrc followed by .zshenv

    sh (or Bash

    named sh)

    This shell does not execute any file automatically,

    so Open MPI will execute the .profile script

    before invoking Open MPI executables on remote nodes

    csh

    .cshrc

    tcsh

    .tcshrc if it exists, .cshrc if it does not


11.4.5. What if I can’t modify my PATH and/or LD_LIBRARY_PATH?

There are some situations where you cannot modify the PATH or LD_LIBRARY_PATH — e.g., some ISV applications prefer to hide all parallelism from the user, and therefore do not want to make the user modify their shell startup files. Another case is where you want a single user to be able to launch multiple MPI jobs simultaneously, each with a different MPI implementation. Hence, setting shell startup files to point to one MPI implementation would be problematic.

In such cases, you have two options:

  1. Use mpirun’s --prefix command line option (described below).

  2. Modify the wrapper compilers to include directives to include run-time search locations for the Open MPI libraries.

mpirun’s --prefix command line option takes as an argument the top-level directory where Open MPI was installed. While relative directory names are possible, they can become ambiguous depending on the job launcher used; using absolute directory names is strongly recommended.

For example, say that Open MPI was installed into /opt/openmpi-$ver_current. You would use the --prefix option thusly:

shell$ mpirun --prefix /opt/openmpi-$ver_current -n 4 a.out

This will prefix the PATH and LD_LIBRARY_PATH on both the local and remote hosts with /opt/openmpi-$ver_current/bin and /opt/openmpi-$ver_current/lib, respectively. This is usually unnecessary when using resource managers to launch jobs (e.g., Slurm, Torque, etc.) because they tend to copy the entire local environment — to include the PATH and LD_LIBRARY_PATH — to remote nodes before execution. As such, if PATH and LD_LIBRARY_PATH are set properly on the local node, the resource manager will automatically propagate those values out to remote nodes. The --prefix option is therefore usually most useful in ssh-based environments (or similar).

It is possible to make this the default behavior by passing to configure the flag --enable-mpirun-prefix-by-default. This will make mpirun behave exactly the same as mpirun --prefix $prefix ..., where $prefix is the value given to --prefix in configure.

Finally, note that specifying the absolute pathname to mpirun is equivalent to using the --prefix argument. For example, the following is equivalent to the above command line that uses --prefix:

shell$ /opt/openmpi-$ver_current/bin/mpirun -n 4 a.out

11.4.6. How do I launch Open MPI parallel jobs?

Similar to many MPI implementations, Open MPI provides the commands mpirun and mpiexec to launch MPI jobs. Several of the questions in this FAQ category deal with using these commands.

Note, however, that in Open MPI, mpirun and mpiexec are exactly identical. Specifically, they are symbolic links to a common back-end launcher command.

Note

The name of the back-end launcher command has changed over time (it used to be orterun, it is now prte). This back-end name is largely irrelevant to the user.

The rest of this FAQ usually refers only to mpirun, even though the same discussions also apply to mpiexec (because they are both, in fact, the same command).


11.4.7. How do I run a simple SPMD MPI job?

Open MPI provides both mpirun and mpiexec commands. A simple way to start a single program, multiple data (SPMD) application in parallel is:

shell$ mpirun -n 4 my_parallel_application

This starts a four-process parallel application, running four copies of the executable named my_parallel_application.

The rsh starter component accepts the --hostfile option (and its synonym, the --machinefile option) to indicate on which hosts to start the processes:

shell$ cat my_hostfile
host01.example.com
host02.example.com
shell$ mpirun --hostfile my_hostfile -n 4 my_parallel_application

This command will launch one copy of my_parallel_application on each of host01.example.com and host02.example.com.

More information about the --hostfile option, and hostfiles in general, is available in this FAQ entry.

Note, however, that not all environments require a hostfile. For example, Open MPI will automatically detect when it is running in batch / scheduled environments (such as Slurm, PBS/Torque, SGE, LoadLeveler), and will use host information provided by those systems.

Also note that if using a launcher that requires a hostfile and no hostfile is specified, all processes are launched on the local host.


11.4.8. How do I run an MPMD MPI job?

Both the mpirun and mpiexec commands support multiple program, multiple data (MPMD) style launches, either from the command line or from a file. For example:

shell$ mpirun -n 2 a.out : -n 2 b.out

This will launch a single parallel application, but the first two processes will be instances of the a.out executable, and the second two processes will be instances of the b.out executable. In MPI terms, this will be a single MPI_COMM_WORLD, but the a.out processes will be ranks 0 and 1 in MPI_COMM_WORLD, while the b.out processes will be ranks 2 and 3 in MPI_COMM_WORLD.

mpirun (and mpiexec) can also accept a parallel application specified in a file instead of on the command line. For example:

shell$ mpirun --app my_appfile

where the file my_appfile contains the following:

# Comments are supported; comments begin with #
# Application context files specify each sub-application in the
# parallel job, one per line.  The first sub-application is the 2
# a.out processes:
-n 2 a.out
# The second sub-application is the 2 b.out processes:
-n 2 b.out

This will result in the same behavior as running a.out and b.out from the command line.

Note that mpirun and mpiexec are identical in command-line options and behavior; using the above command lines with mpiexec instead of mpirun will result in the same behavior.


11.4.9. How do I specify the hosts on which my MPI job runs?

There are three general mechanisms:

  1. The --hostfile option to mpirun.

    Use this option to specify a list of hosts on which to run. Note that for compatibility with other MPI implementations, --machinefile is a synonym for --hostfile. See this FAQ entry for more information about the --hostfile option.

  2. The --host option to mpirun.

    This option can be used to specify a list of hosts on which to run on the command line. See this FAQ entry for more information about the --host option.

  3. Running in a scheduled environment.

    If you are running in a scheduled environment (e.g., in a Slurm, Torque, or LSF job), Open MPI will automatically get the lists of hosts from the scheduler.

Important

The specification of hosts using any of the above methods has nothing to do with the network interfaces that are used for MPI traffic. The list of hosts is only used for specifying which hosts on which to launch MPI processes.


11.4.10. How can I diagnose problems when running across multiple hosts?

When you are able to run MPI jobs on a single host, but fail to run them across multiple hosts, try the following:

  1. Ensure that your launcher is able to launch across multiple hosts. For example, if you are using ssh, try to ssh to each remote host and ensure that you are not prompted for a password. For example:

    shell$ ssh remotehost hostname
    remotehost
    

    If you are unable to launch across multiple hosts, check that your SSH keys are setup properly. Or, if you are running in a managed environment, such as in a Slurm, Torque, or other job launcher, check that you have reserved enough hosts, are running in an allocated job, etc.

  2. Ensure that your PATH and LD_LIBRARY_PATH are set correctly on each remote host on which you are trying to run. For example, with ssh:

    shell$ ssh remotehost env | grep -i path
    PATH=...path on the remote host...
    LD_LIBRARY_PATH=...LD library path on the remote host...
    

    If your PATH or LD_LIBRARY_PATH are not set properly, see this FAQ entry for the correct values. Keep in mind that it is fine to have multiple Open MPI installations installed on a machine; the first Open MPI installation found by PATH and LD_LIBARY_PATH is the one that matters.

  3. Run a simple, non-MPI job across multiple hosts. This verifies that the Open MPI run-time system is functioning properly across multiple hosts. For example, try running the hostname command:

    shell$ mpirun --host remotehost hostname
    remotehost
    shell$ mpirun --host remotehost,otherhost hostname
    remotehost
    otherhost
    

    If you are unable to run non-MPI jobs across multiple hosts, check for common problems such as:

    1. Check your non-interactive shell setup on each remote host to ensure that it is setting up the PATH and LD_LIBRARY_PATH properly.

    2. Check that Open MPI is finding and launching the correct version of Open MPI on the remote hosts.

    3. Ensure that you have firewalling disabled between hosts (Open MPI opens random TCP and sometimes random UDP ports between hosts in a single MPI job).

    4. Try running with the plm_base_verbose MCA parameter at level 10, which will enable extra debugging output to see how Open MPI launches on remote hosts. For example:

      mpirun --mca plm_base_verbose 10 --host remotehost hostname``
      
  4. Now run a simple MPI job across multiple hosts that does not involve MPI communications. The hello_c program in the examples directory in the Open MPI distribution is a good choice. This verifies that the MPI subsystem is able to initialize and terminate properly. For example:

    shell$ mpirun --host remotehost,otherhost hello_c
    Hello, world, I am 0 of 1, (Open MPI v$ver_current, package: Open MPI jsquyres@example.com Distribution, ident: $ver_current, DATE)
    Hello, world, I am 1 of 1, (Open MPI v$ver_current, package: Open MPI jsquyres@example.com Distribution, ident: $ver_current, DATE)
    

    If you are unable to run simple, non-communication MPI jobs, this can indicate that your Open MPI installation is unable to initialize properly on remote hosts. Double check your non-interactive login setup on remote hosts.

  5. Now run a simple MPI job across multiple hosts that does does some simple MPI communications. The ring_c program in the examples directory in the Open MPI distribution is a good choice. This verifies that the MPI subsystem is able to pass MPI traffic across your network. For example:

    shell$ mpirun --host remotehost,otherhost ring_c
    Process 0 sending 10 to 0, tag 201 (1 processes in ring)
    Process 0 sent to 0
    Process 0 decremented value: 9
    Process 0 decremented value: 8
    Process 0 decremented value: 7
    Process 0 decremented value: 6
    Process 0 decremented value: 5
    Process 0 decremented value: 4
    Process 0 decremented value: 3
    Process 0 decremented value: 2
    Process 0 decremented value: 1
    Process 0 decremented value: 0
    Process 0 exiting
    

    If you are unable to run simple MPI jobs across multiple hosts, this may indicate a problem with the network(s) that Open MPI is trying to use for MPI communications. Try limiting the networks that it uses, and/or exploring levels 1 through 3 MCA parameters for the communications module that you are using. For example, if you’re using the TCP BTL, see the output of:

    ompi_info --level 3 --param btl tcp
    

11.4.11. I get errors about missing libraries. What should I do?

When building Open MPI with the compilers that have libraries in non-default search path locations, you may see errors about those compiler’s support libraries when trying to launch MPI applications if their corresponding environments were not setup properly.

For example, you may see warnings similar to the following:

# With the Intel compiler suite
shell$ mpirun -n 1 --host node1.example.com mpi_hello
prted: error while loading shared libraries: libimf.so: cannot open shared object file: No such file or directory
--------------------------------------------------------------------------
A daemon (pid 11893) died unexpectedly with status 127 while
attempting to launch so we are aborting.
...more error messages...

# With the PGI compiler suite
shell$ mpirun -n 1 --host node1.example.com mpi_hello
prted: error while loading shared libraries: libpgcc.so: cannot open shared object file: No such file or directory
...more error messages...

# With the PathScale compiler suite
shell$ mpirun -n 1 --host node1.example.com mpi_hello
prted: error while loading shared libraries: libmv.so: cannot open shared object file: No such file or directory
...more error messages...

Specifically, Open MPI first attempts to launch a “helper” daemon prted on node1.example.com, but it failed because one of prted’s dependent libraries was not able to be found. The libraries shown above (libimf.so, libpgcc.so, and libmv.so) are specific to their compiler suites (Intel, PGI, and PathScale, respectively). As such, it is likely that the user did not setup the compiler library in their environment properly on this node.

Double check that you have setup the appropriate compiler environment on the target node, for both interactive and non-interactive logins.

Note

It is a common error to ensure that the compiler environment is setup properly for interactive logins, but not for non-interactive logins.

Here’s an example of a user-compiled MPI application working fine locally, but failing when invoked non-interactively on a remote node:

# Compile a trivial MPI application
head_node$ cd $HOME
head_node$ mpicc mpi_hello.c -o mpi_hello

# Run it locally; it works fine
head_node$ ./mpi_hello
Hello world, I am 0 of 1.

# Run it remotely interactively; it works fine
head_node$ ssh node2.example.com

Welcome to node2.
node2$ ./mpi_hello
Hello world, I am 0 of 1.
node2$ exit

# Run it remotely *NON*-interactively; it fails
head_node$ ssh node2.example.com $HOME/mpi_hello
mpi_hello: error while loading shared libraries: libimf.so: cannot open shared object file: No such file or directory

In cases like this, check your shell script startup files and verify that the appropriate compiler environment is setup properly for non-interactive logins.


11.4.12. Can I run non-MPI programs with mpirun / mpiexec?

Yes.

For example:

shell$ mpirun -n 2 --host a,b uptime

This will launch a copy of the Unix command uptime on the hosts a and b.

Other questions in the FAQ section deal with the specifics of the mpirun command line interface; suffice it to say that it works equally well for MPI and non-MPI applications.


11.4.13. Can I run GUI applications with Open MPI?

Yes, but it will depend on your local setup and may require additional setup.

In short: you will need to have graphics forwarding (e.g., X11 forwarding) enabled from the remote processes to the display where you want output to appear. In a secure environment, you can simply allow all X requests to be shown on the target display and set the DISPLAY environment variable in all MPI processes’ environments to the target display, perhaps something like this:

shell$ hostname
my_desktop.secure-cluster.example.com
shell$ xhost +
shell$ mpirun -n 4 -x DISPLAY=my_desktop.secure-cluster.example.com a.out

However, this technique is not generally suitable for unsecure environments (because it allows anyone to read and write to your display). A slightly more secure way is to only allow X connections from the nodes where your application will be running:

shell$ hostname
my_desktop.secure-cluster.example.com
shell$ xhost +compute1 +compute2 +compute3 +compute4
compute1 being added to access control list
compute2 being added to access control list
compute3 being added to access control list
compute4 being added to access control list
shell$ mpirun -n 4 -x DISPLAY=my_desktop.secure-cluster.example.com a.out

(assuming that the four nodes you are running on are compute1 through compute4).

Other methods are available, but they involve sophisticated X forwarding through mpirun and are generally more complicated than desirable.


11.4.14. Can I run ncurses-based / curses-based / applications with funky input schemes with Open MPI?

Maybe. But probably not.

Open MPI provides fairly sophisticated stdin / stdout / stderr forwarding. However, it does not work well with curses, ncurses, readline, or other sophisticated I/O packages that generally require direct control of the terminal.

Every application and I/O library is different — you should try to see if yours is supported. But chances are that it won’t work.

Sorry. :-(


11.4.15. What other options are available to mpirun?

mpirun supports the --help option which provides a usage message and a summary of the options that it supports. It should be considered the definitive list of what options are provided.

Several notable options are:

  • --hostfile: Specify a hostfile for launchers (such as the rsh launcher) that need to be told on which hosts to start parallel applications. Note that for compatibility with other MPI implementations, –machinefile is a synonym for --hostfile.

  • --host: Specify a host or list of hosts to run on (see this FAQ entry for more details).

  • -n: Indicate the number of processes to start.

  • --mca: Set MCA parameters (see how to set MCA params for more details).

  • --wdir DIRECTORY: Set the working directory of the started applications. If not supplied, the current working directory is assumed (or $HOME, if the current working directory does not exist on all nodes).

  • -x ENV_VARIABLE_NAME: The name of an environment variable to export to the parallel application. The -x option can be specified multiple times to export multiple environment variables to the parallel application.


11.4.16. How do I use the --hostfile option to mpirun?

Error

TODO For cross reference, this is the PRRTE man page section about --hostfile: https://github.com/openpmix/prrte/blob/b70a6f1a8d424e396c40c999a656b04e76cc0f91/src/tools/prte/prte-map.1.md?plain=1#L236 A subsequent commit removed this markdown file; the commit message refers to moving the markdown file to another git repo, but I didn’t chase down where it went.

The --hostfile option to mpirun takes a filename that lists hosts on which to launch MPI processes.

Important

The hosts listed in a hostfile have nothing to do with which network interfaces are used for MPI communication. They are only used to specify on which hosts to launch MPI processes.

Hostfiles are simple text files with hosts specified, one per line. Each host can also specify a default and maximum number of slots to be used on that host (i.e., the maximum number of processes that will be launched on that node). Comments are also supported, and blank lines are ignored. For example:

# This is an example hostfile.  Comments begin with #.
#
# Since no slots are specified, the number of slots defaults to the
# number of processor cores available on the machine.
foo.example.com

# We want to allow launching a maximum of 2 processes on this host
# (e.g., potentially because it has two processor cores):
bar.example.com slots=2

Slots are discussed in much more detail in this FAQ entry.

Hostfiles works in two different ways:

  1. Exclusionary: If a list of hosts to run on has been provided by another source (e.g., by a hostfile or a batch scheduler such as Slurm, PBS/Torque, SGE, etc.), the hosts provided by the hostfile must be in the already-provided host list. If the hostfile-specified nodes are not in the already-provided host list, mpirun will abort without launching anything.

    In this case, hostfiles act like an exclusionary filter — they limit the scope of where processes will be scheduled from the original list of hosts to produce a final list of hosts.

    For example, say that a scheduler job contains hosts node01 through node04. If you run:

    shell$ cat my_hosts
    node03
    shell$ mpirun -n 1 --hostfile my_hosts hostname
    

    This will run a single copy of hostname on the host node03.

    However, presuming your job was allocated only to node03 and you run the following:

    shell$ cat my_hosts
    node17
    shell$ mpirun -n 1 --hostfile my_hosts hostname
    

    This is an error (because node17 is not allocated to your job), and mpirun will abort.

    Finally, note that in exclusionary mode, processes will only be executed on the hostfile-specified hosts, If this ends up causing an oversubscription situation, mpirun will abort by default.

  2. Inclusionary: If a list of hosts has not been provided by another source, then the hosts provided by the --hostfile option will be used as the original and final host list.

    In this case, --hostfile acts as an inclusionary agent; all --hostfile-supplied hosts become available for scheduling processes. For example (assume that you are not in a scheduling environment where a list of nodes is being transparently supplied):

    shell$ cat my_hosts
    node01.example.com slots=1
    node02.example.com slots=1
    node03.example.com slots=1
    shell$ mpirun -n 3 --hostfile my_hosts hostname
    

    This will launch a single copy of hostname on the hosts node01.example.com, node02.example.com, and node03.example.com.

Note, too, that --hostfile is essentially a per-application switch. Hence, if you specify multiple applications (as in an MPMD job), --hostfile can be specified multiple times:

shell$ cat hostfile_1
node01.example.com
shell$ cat hostfile_2
node02.example.com
shell$ mpirun -n 1 --hostfile hostfile_1 hostname : -n 1 --hostfile hostfile_2 uptime
node01.example.com
 06:11:45 up 1 day,  2:32,  0 users,  load average: 21.65, 20.85, 19.84

Notice that hostname was launched on node01.example.com and uptime was launched on node02.example.com.


11.4.17. How do I use the --host option to mpirun?

The --host option to mpirun takes a comma-delimited list of hosts on which to run. For example:

shell$ mpirun -n 3 --host a,b,c hostname

Will launch one copy of hostname on each of hosts a, b, and c. Specifically: each host defaults to 1 slot, unless specified by the :N suffix. For example:

shell$ mpirun --host a,b:2,c:3 hostname

Will launch one copy of hostname on a, two copies of hostname on b, and three copies of hostname and c.

Slots are discussed in much more detail in this FAQ entry.

Important

The hosts specified by the --host option have nothing to do with which network interfaces are used for MPI communication. They are only used to specify on which hosts to launch MPI processes.

--host works in two different ways:

  1. Exclusionary: If a list of hosts to run on has been provided by another source (e.g., by a hostfile or a batch scheduler such as Slurm, PBS/Torque, SGE, etc.), the hosts provided by the --host option must be in the already-provided host list. If the --host-specified nodes are not in the already-provided host list, mpirun will abort without launching anything.

    In this case, the --host option acts like an exclusionary filter — it limits the scope of where processes will be scheduled from the original list of hosts to produce a final list of hosts.

    For example, say that the hostfile my_hosts contains the hosts node1 through node4. If you run:

    shell$ mpirun -n 1 --hostfile my_hosts --host node3 hostname
    

    This will run a single copy of hostname on the host node3. However, if you run:

    shell$ mpirun -n 1 --hostfile my_hosts --host node17 hostname
    

    This is an error (because node17 is not listed in my_hosts); mpirun will abort.

    Finally, note that in exclusionary mode, processes will only be executed on the --host-specified hosts. If this ends up causing an oversubscription situation, mpirun will abort by default.

  2. Inclusionary: If a list of hosts has not been provided by another source, then the hosts provided by the --host option will be used as the original and final host list.

    In this case, --host acts as an inclusionary agent; all --host-supplied hosts become available for scheduling processes. For example (assume that you are not in a scheduling environment where a list of nodes is being transparently supplied):

    shell$ mpirun -n 3 --host a,b,c hostname
    

    This will launch a single copy of hostname on the hosts a, b, and c.

Note, too, that --host is essentially a per-application switch. Hence, if you specify multiple applications (as in an MPMD job), --host can be specified multiple times:

shell$ mpirun -n 1 --host a hostname : -n 1 --host b uptime

This will launch hostname on host a and uptime on host b.


11.4.18. What are “slots”?

Slots are Open MPI’s representation of how many processes can be launched on a given host.

Open MPI maintains the number of slots for each host in a given parallel job, and — by default — will not let you launch more processes on a host than it has slots.

Important

It is common to set the number of slots on a host to be less than or equal to the number of processor cores on that host.

But it is important to realize that Open MPI’s concept of slots is actually unrelated to the number of physical processor cores on a host.

Specifically: the number of slots on a host can be less than, equal to, or more than the number of processor cores on a host.

If you wish to run more processes on a host than it has slots, see the FAQ entry on oversubscription.


11.4.19. How are the number of slots calculated?

The number of slots on a host depends on a few factors:

  1. If the host is specified by a job scheduler (e.g., Slurm, PBS/Torque, etc.), the job scheduler specifies the number of slots for that host.

  2. If the host is specified in a hostfile:

    1. If the slots parameter is specified, that value is used for the number of slots on that host.

    2. Otherwise:

      1. If --map-by :HWTCPUS was specified, the number of slots defaults to the number of hardware threads on that host.

      2. Otherwise, the number of slots defaults to the number of processor cores on that host.

  3. If the host is specified via the --host command line option:

    1. If the :N suffix is specified, N is used for the number of slots on that host.

    2. Otherwise, the number of slots defaults to 1.

    3. If the same host name is specified multiple times, the slots value for that host is increased by N if :N is specified, or increased by 1 if :N is not specified.

Caution

The exact scheme used to determine the number of slots has varied between different major versions of Open MPI. The scheme described above is relevant for Open MPI v5.0.x.

Max slot counts, however, are rarely specified by schedulers. The max slot count for each node will default to “infinite” if it is not provided (meaning that Open MPI will oversubscribe the node if you ask it to — see more on oversubscribing in this FAQ entry).

Error

TODO Ralph: do we still have the concept of “max slots”? Issue is open: https://github.com/openpmix/prrte/issues/770.

Here are some examples, all from unscheduled environments:

  1. Use a hostfile and specify the slots parameter.

    shell$ cat my-hostfile
    node01.example.come slots=4
    shell$ mpirun --hostfile my-hostfile hostname
    node01
    node01
    node01
    node01
    

    This launched 4 processes because slots=4 was specified in the hostfile.

  2. Use a hostfile and do not specify the slots parameter (assume that node01.example.com has 2 processor cores):

    shell$ cat my-hostfile
    node01.example.come
    shell$ mpirun --hostfile my-hostfile hostname
    node01
    node01
    

    This launched 2 processes because slots was not specified, and node02 has 2 processor cores.

  3. Use --host:

    shell$ mpirun --host node01.example.com hostname
    node01
    

    This launched 1 processes because --host with no :N suffix increments the slot count for that host by 1.

  4. Use --host with a :N suffix:

    shell$ mpirun --host node01.example.com:2 hostname
    node01
    node01
    

    This launched 2 processes because :2 was specified on the command line.

  5. Use --host with a :N suffix, and mention the host multiple times:

    shell$ mpirun --host node01.example.com:2,node01.example.com hostname
    node01
    node01
    node01
    

    This launched 3 processes because :2 was specified on the command line, and then node01.example.com was specified an additional time, incrementing the slot count for that host to 3.


11.4.20. How do I control how my processes are scheduled across hosts?

The short version is that if you are not oversubscribing your hosts (i.e., trying to run more processes than slots available on that host), scheduling is pretty simple and occurs either on a by-slot or by-node round robin schedule. If you’re oversubscribing, the issue gets much more complicated — keep reading.

The more complete answer is: Open MPI schedules processes to nodes by asking two questions from each application on the mpirun command line:

  1. How many processes should be launched?

  2. Where should those processes be launched?

The “how many” question is directly answered with the -n switch to mpirun. If -n is not specified on the mpirun command line, its value is the sum of the slots on all the nodes.

The “where” question is a little more complicated, and depends on three factors:

  1. The final node list (e.g., after -hostname / --host exclusionary or inclusionary processing)

  2. The scheduling policy (which applies to all applications in a single job)

  3. The default and maximum number of slots on each host

Error

TODO Ralph: do we still have the concept of “max slots”? Issue is open: https://github.com/openpmix/prrte/issues/770.

Open MPI currently supports two scheduling policies: by slot and by node:

  1. By slot: This is the default scheduling policy, but can also be explicitly requested by using either the --map-by slot option to mpirun or by setting the MCA parameter rmaps_default_mapping_policy to the string slot.

    In this mode, Open MPI will schedule processes on a node until all of its default slots are exhausted before proceeding to the next node. In MPI terms, this means that Open MPI tries to maximize the number of adjacent ranks in MPI_COMM_WORLD on the same host without oversubscribing that host.

    For example:

    shell$ cat my-hosts
    node0 slots=2 max_slots=20
    node1 slots=2 max_slots=20
    shell$ mpirun --hostfile my-hosts -n 8 --map-by slot hello | sort
    Hello World I am rank 0 of 8 running on node0
    Hello World I am rank 1 of 8 running on node0
    Hello World I am rank 2 of 8 running on node1
    Hello World I am rank 3 of 8 running on node1
    Hello World I am rank 4 of 8 running on node0
    Hello World I am rank 5 of 8 running on node0
    Hello World I am rank 6 of 8 running on node1
    Hello World I am rank 7 of 8 running on node1
    
  2. By node: This policy can be requested either by using the --map-by node option to mpirun or by setting the MCA parameter rmaps_default_mapping_policy to the string “node”.

    In this mode, Open MPI will schedule a single process on each node in a round-robin fashion (looping back to the beginning of the node list as necessary) until all processes have been scheduled. Nodes are skipped once their default slot counts are exhausted.

    For example:

    shell$ cat my-hosts
    node0 slots=2 max_slots=20
    node1 slots=2 max_slots=20
    shell$ mpirun --hostname my-hosts -n 8 --map-by node hello | sort
    Hello World I am rank 0 of 8 running on node0
    Hello World I am rank 1 of 8 running on node1
    Hello World I am rank 2 of 8 running on node0
    Hello World I am rank 3 of 8 running on node1
    Hello World I am rank 4 of 8 running on node0
    Hello World I am rank 5 of 8 running on node1
    Hello World I am rank 6 of 8 running on node0
    Hello World I am rank 7 of 8 running on node1
    

In both policies, if the default slot count is exhausted on all nodes while there are still processes to be scheduled, Open MPI will trigger an oversubscription condition.

If :OVERSUBSCRIBE is added as a modifier to the --map-by option (e.g., mpirun --map-by node:OVERSUBSCRIBE ...see this FAQ item for more details), Open MPI will continue to loop through the list of nodes again and try to schedule one more process to each node until all processes are scheduled. Nodes are skipped in this process if their maximum slot count is exhausted. If the maximum slot count is exhausted on all nodes while there are still processes to be scheduled, Open MPI will abort without launching any processes.

If :OVERSUBSCRIBE is not specified and an oversubscription condition occurs, Open MPI will abort without launching any processes.


11.4.21. Can I oversubscribe nodes (run more processes than processors)?

Yes. But it very much matters how you do it.

Specifically: it is critical that Open MPI knows that you are oversubscribing the node, or severe performance degradation can result.

Important

Here is a good general rule to follow: never specify a number of slots that is more than the available number of processors.

For example, if you want to run 4 processes on a host with 2 processor cores, then indicate that you only have 2 slots but want to run 4 processes. For example:

# In a hostfile, the number of slots will default to the number of
# processor cores on the host
shell$ cat my-hostfile
localhost
shell$ mpirun -n 4 --hostfile my-hostfile a.out

Specifically: we strongly suggest that you do NOT have a hostfile that contains slots=4 (because there are only two available processor cores).

That being said, the above command will fail, because you are trying to run 4 processes but there are only 2 slots available. You must specifically tell Open MPI that it is ok to oversubscribe via --map-by :OVERSUBSCRIBE:

shell$ cat my-hostfile
# For the purposes of this example, explicitly tell Open MPI
# that we have 2 slots on the host.
localhost slots=2
shell$ mpirun -n 4 --hostfile my-hostfile --map-by :OVERSUBSCRIBE a.out

The reason you should tell Open MPI whether you’re oversubscribing or not (i.e., never specify a slots value more than the number of processor cores available) is because Open MPI basically runs its message passing progression engine in two modes: aggressive and degraded.

  1. Degraded: When Open MPI thinks that it is in an oversubscribed mode (i.e., more processes are running than there are processor cores available), MPI processes will automatically run in degraded mode and frequently yield the processor to its peers, thereby allowing all processes to make progress.

    Note

    Be sure to see this FAQ entry that describes how degraded mode affects processor and memory affinity.

  2. Aggressive: When Open MPI thinks that it is in an exactly- or under-subscribed mode (i.e., the number of running processes is equal to or less than the number of available processor cores), MPI processes will automatically run in aggressive mode, meaning that they will never voluntarily give up the processor to other processes. With some network transports, this means that Open MPI will spin in tight loops attempting to make message passing progress, effectively causing other processes to not get any CPU cycles (and therefore never make any progress).

For example, on a node with a two processor cores:

shell$ cat my-hostfile
localhost slots=4
shell$ mpirun -n 4 --hostfile my-hostfile a.out

This would cause all 4 MPI processes to run in aggressive mode because Open MPI thinks that there are 4 available processor cores to use. This is actually a lie (there are only 2 processor core — not 4), and can cause extremely bad performance.


11.4.22. Can I force Aggressive or Degraded performance modes?

Yes.

The MCA parameter mpi_yield_when_idle controls whether an MPI process runs in Aggressive or Degraded performance mode. Setting it to 0 forces Aggressive mode; setting it to 1 forces Degraded mode (see this FAQ entry to see how to set MCA parameters).

Note that this value only affects the behavior of MPI processes when they are blocking in MPI library calls. It does not affect behavior of non-MPI processes, nor does it affect the behavior of a process that is not inside an MPI library call.

Open MPI normally sets this parameter automatically (see this FAQ entry for details). Users are cautioned against setting this parameter unless you are really, absolutely, positively sure of what you are doing.


11.4.23. How do I run with the TotalView parallel debugger?

This has changed with different releases of TotalView and Open MPI; it is best to consult TotalView’s documentation for how you should debug Open MPI applications with TotalView.


11.4.24. How do I run with the DDT parallel debugger?

This has changed with different releases of DDT and Open MPI; it is best to consult DDT’s documentation for how you should debug Open MPI applications with DDT.


11.4.25. How do I dynamically load libmpi at runtime?

If you want to load a the shared library libmpi explicitly at runtime either by using dlopen() from C/C ++ or something like the ctypes package from Python, some extra care is required. The default configuration of Open MPI uses dlopen() internally to load its support components. These components rely on symbols available in libmpi. In order to make the symbols in libmpi available to the components loaded by Open MPI at runtime, libmpi must be loaded with the RTLD_GLOBAL option.

In C/C++, this option is specified as the second parameter to the POSIX dlopen(3) function.

When using ctypes with Python, this can be done with the second (optional) parameter to CDLL(). For example (shown below in Mac OS X, where Open MPI’s shared library name ends in .dylib; other operating systems use other suffixes, such as .so):

from ctypes import *

mpi = CDLL('libmpi.0.dylib', RTLD_GLOBAL)

f = pythonapi.Py_GetArgcArgv
argc = c_int()
argv = POINTER(c_char_p)()
f(byref(argc), byref(argv))
mpi.MPI_Init(byref(argc), byref(argv))

# Your MPI program here

mpi.MPI_Finalize()

Other scripting languages should have similar options when dynamically loading shared libraries.


11.4.26. What MPI environment variables exist?

Open MPI provides the following environment variables that will be defined on every MPI process:

  • OMPI_COMM_WORLD_SIZE: the number of processes in this process’s MPI_COMM_WORLD

  • OMPI_COMM_WORLD_RANK: the MPI rank of this process in MPI_COMM_WORLD

  • OMPI_COMM_WORLD_LOCAL_SIZE: the number of ranks from this job that are running on this node.

  • OMPI_COMM_WORLD_LOCAL_RANK: the relative rank of this process on this node within its job. For example, if four processes in a job share a node, they will each be given a local rank ranging from 0 to 3.

  • OMPI_UNIVERSE_SIZE: the number of process slots allocated to this job. Note that this may be different than the number of processes in the job.

  • OMPI_COMM_WORLD_NODE_RANK: the relative rank of this process on this node looking across all jobs.