Release Notes #

With SUSE Linux Enterprise High Performance Computing 15 GA, it is possible to choose specific roles for the system based on modules selected during the installation process. When the HPC Module is enabled, these three roles are available:

The scratch partition /var/tmp/ will only be created if there is sufficient space available on the installation medium (minimum 32 GB).

The Environment Module Lmod will be installed for all roles. It is required at build time and run time of the system. For more information, see Section 8.7, “Lmod — Lua-based Environment Modules”.

All libraries specifically build for HPC will be installed under /usr/lib/hpc. They are not part of the standard search path, thus the Lmod environment module system is required.

Munge authentication is installed for all roles. This requires to copy the same generated munge keys to all nodes of a cluster. For more information, see Section 8.15, “mrsh/mrlogin — Remote Login Using munge Authentication” and Section 8.14, “munge Authentication”.

From the Ganglia monitoring system, the data collector ganglia-gmod is installed for every role, while the data aggregator ganglia-gmetad needs to be installed manually on the system which is expected to collect the data. For more information, see Section 8.3, “Ganglia — System Monitoring”.

The system roles are only available for new installations of SUSE Linux Enterprise High Performance Computing.

This section includes information related to the initial installation of the SUSE Linux Enterprise High Performance Computing 15 GA.

This section includes upgrade-related information for the SUSE Linux Enterprise High Performance Computing 15 GA.

You can upgrade to SUSE Linux Enterprise High Performance Computing 15 GA from SLES 12 SP3 or SLE HPC 12 SP3. When upgrading from SLES 12 SP3, the upgrade will only be performed if the SLE HPC module has been registered prior to upgrading. Otherwise, the system will instead be upgraded to SLES 15.

To upgrade from SLES 12 to SLES 15, make sure to unregister the SLE HPC module prior to upgrading. To do so, open a root shell and execute:

SUSEConnect -d -p sle-module-hpc/12/ARCH

Replace ARCH with the architecture used (x86_64, aarch64).

When migrating to SUSE Linux Enterprise High Performance Computing 15 GA, all modules not supported by the migration target need to be deregistered. This can be done by executing:

SUSEConnect -d -p sle-module-MODULE_NAME/12/ARCH

Replace MODULE_NAME by the name of the module and ARCH with the architecture used (x86_64, aarch64).

cpuid executes the x86 CPUID instruction and decodes and prints the results to stdout. Its knowledge of Intel, AMD and Cyrix CPUs is fairly complete. It also supports Intel Knights Mill CPUs (x86-64).

To install cpuid, run: zypper in cpuid.

For information about runtime options for cpuid, see the man page cpuid(1).

Note that this tool is only available for x86-64.

ConMan is a serial console management program designed to support a large number of console devices and simultaneous users. It supports:

ConMan can be used for monitoring, logging and optionally timestamping console device output.

To install ConMan, run zypper in conman.

Important: conmand Sends Unencrypted Data

The daemon conmand sends unencrypted data over the network and its connections are not authenticated. Therefore, it should be used locally only: Listening to the port localhost. However, the IPMI console does offer encryption. This makes conman a good tool for monitoring a large number of such consoles.

Usage:

For more information about options, see the man page of ConMan.

Ganglia is a scalable distributed monitoring system for high-performance computing systems, such as clusters and grids. It is based on a hierarchical design targeted at federations of clusters.

To use Ganglia, make sure to install ganglia-gmetad on the management serve then start the Ganglia meta-daemon: rcgmead start. To make sure the service is started after a reboot, run: systemctl enable gmetad. On each cluster node which you want to monitor, install ganglia-gmond, start the service rcgmond start and make sure it is enabled to be started automatically after a reboot: systemctl enable gmond. To test whether the gmond daemon has connected to the meta-daemon, run gstat -a and check that each node to be monitored is present in the output.

When using the Btrfs file system, the monitoring data will be lost after a rollback and the service gmetad. To be able to start it again, either install the package ganglia-gmetad-skip-bcheck or create the file /etc/ganglia/no_btrfs_check.

To use the Ganglia Web interface, it is required to add the "Web and Scripting Module" first. This can be done by running SUSEConnect -p sle-module-web-scripting/15/x86_64. Install ganglia-web on the management server. Depending on which PHP version is used (default is PHP 5), enable it in Apache2: a2enmod php5 or a2enmod php7. Then start Apache2 on this machine: rcapache2 start and make sure it is started automatically after a reboot: systemctl enable apache2. The Ganglia Web interface should be accessible from http://MANAGEMENT_SERVER/ganglia.

Support for Genders has been added to the HPC module.

Genders is a static cluster configuration database used for configuration management. It allows grouping and addressing sets of hosts by attributes and is used by a variety of tools. The Genders database is a text file which is usually replicated on each node in a cluster.

Perl, Python, C, and C++ bindings are supplied with Genders, the respective packages provide man pages or other documentation describing the APIs.

To create the Genders database, follow the instructions and examples in /etc/genders and check /usr/share/doc/packages/genders-base/TUTORIAL. Testing a configuration can be done with nodeattr (for more information, see man 1 nodeattr).

List of packages:

gnu-compilers-hpc installs the base version of the GNU compiler suite and provides environment files for Lmod to select this compiler suite and provides environment module files for them. This version of the compiler suite is required to enable linking against HPC libraries enabled for environment modules.

This package requires lua-lmod to supply environment module support.

To install gnu-compilers-hpc, run:

zypper in gnu-compilers-hpc

To set up the environment appropriately and select the GNU toolchain, run:

module load gnu

If you have more than one version of this compiler suite installed, add the version number of the compiler suite. For more information, see Section 8.7, “Lmod — Lua-based Environment Modules”.

hwloc provides command-line tools and a C API to obtain the hierarchical map of key computing elements, such as: NUMA memory nodes, shared caches, processor packages, processor cores, processing units (logical processors or "threads") and even I/O devices. hwloc also gathers various attributes such as cache and memory information, and is portable across a variety of different operating systems and platforms. Additionally it may assemble the topologies of multiple machines into a single one, to let applications consult the topology of an entire fabric or cluster at once.

In graphical mode (X11), hwloc can display the topology in a human-readable format. Alternatively, it can export to one of several formats, including plain text, PDF, PNG, and FIG. For more information, see the man pages provided by hwloc.

It also features full support for import and export of XML-formatted topology files via the libxml2 library.

The package hwloc-devel offers a library that can be directly included into external programs. This requires that the libxml2 development library (package libxml2-devel) is available when compiling hwloc.

Lmod is an advanced environment module system which allows the installation of multiple versions of a program or shared library, and helps configure the system environment for the use of a specific version. It supports hierarchical library dependencies and makes sure that the correct version of dependent libraries are selected. Environment Modules-enabled library packages supplied with the HPC module support parallel installation of different versions and flavors of the same library or binary and are supplied with appropriate lmod module files.

To install Lmod, run: zypper in lua-lmod.

Before Lmod can be used, an init file needs to be sourced from the initialization file of your interactive shell. The following init files are available:

/usr/share/lmod/<lmod_version>/init/bash
/usr/share/lmod/<lmod_version>/init/ksh
/usr/share/lmod/<lmod_version>/init/tcsh
/usr/share/lmod/<lmod_version>/init/zsh
/usr/share/lmod/<lmod_version>/init/sh

Pick the one appropriate for your shell. Then add the following to the init file of your shell:

. /usr/share/lmod/<LMOD_VERSION>/init/<INIT-FILE>

To obtain <lmod_version>, run:

rpm -q lua-lmod | sed "s/.*-\([^-]\+\)-.*/\1/"

The init script adds the command module.

To list the available all available modules, run: module spider. To show all modules which can be loaded with the currently loaded modules, run: module avail. A module name consists of a name and a version string separated by a / character. If more than one version is available for a certain module name, the default version (marked by *) or (if this is not set) the one with the highest version number is loaded. To refer to a specific module version, the full string NAME/VERSION may be used.

module list shows all currently loaded modules. Refer to module help for a short help on the module command and module help MODULE-NAME for a help on the particular module. Note that the module command is available only when you log in after installing lua-lmod.

To get information about a particular module, run: module whatis MODULE-NAME To load a module, run: module load MODULE-NAME. This will ensure that your environment is modified (that is, the PATH and LD_LIBRARY_PATH and other environment variables are prepended) such that binaries and libraries provided by the respective modules are found. To run a program compiled against this library, the appropriate module load commands must be issued beforehand.

The module load MODULE command needs to be run in the shell from which the module is to be used. Some modules require a compiler toolchain or MPI flavor module to be loaded before they are available for loading.

If the respective development packages are installed, build time environment variables like LIBRARY_PATH, CPATH, C_INCLUDE_PATH and CPLUS_INCLUDE_PATH will be set up to include the directories containing the appropriate header and library files. However, some compiler and linker commands may not honor these. In this case, use the appropriate options together with the environment variables -I PACKAGE_NAME_INC and -L PACKAGE_NAME_LIB to add the include and library paths to the command lines of the compiler and linker.

For more information on Lmod, see https://lmod.readthedocs.org.

ohpc contains compatibility macros to build OpenHPC packages on SUSE Linux Enterprise.

To install ohpc, run: zypper in ohpc.

pdsh is a parallel remote shell which can be used with multiple back-ends for remote connections. It can run a command on multiple machines in parallel.

To install pdsh, run zypper in pdsh.

On SLES 12, the back-ends ssh, mrsh, and exec are supported. The ssh back-end is the default. Non-default login methods can be used by either setting the PDSH_RCMD_TYPE environment variable or by using the -R command argument.

When using the ssh back-end, it is important that a non-interactive (that is, passwordless) login method is used.

The mrsh back-end requires the mrshd to be running on the client. The mrsh back-end does not require the use of reserved sockets. Therefore, it does not suffer from port exhaustion when executing commands on many machines in parallel. For information about setting up the system to use this back-end, see Section 8.15, “mrsh/mrlogin — Remote Login Using munge Authentication”.

Remote machines can either be specified on the command line or pdsh can use a machines file (/etc/pdsh/machines), dsh (Dancer's shell) style groups or netgroups. Also, it can target nodes based on the currently running Slurm jobs.

The different ways to select target hosts are realized by modules. Some of these modules provide identical options to pdsh. The module loaded first will win and consume the option. Therefore, we recommend limiting yourself to a single method and specifying this with the -M option.

The machines file lists all target hosts one per line. The appropriate netgroup can be selected with the -g command line option.

The following host-list plugins for pdsh are supported: machines, slurm, netgroup and dshgroup. Each host-list plugin is provided in a separate package. This avoids conflicts between command line options for different plugins which happen to be identical and helps to keep installations small and free of unneeded dependencies. Package dependencies have been set to prevent installing plugins with conflicting command options. To install one of the plugins, run:

zypper in pdsh-PLUGIN_NAME

For more information, see the man page pdsh.

PowerMan allows manipulating remote power control devices (RPC) from a central location. It can control:

The communication to RPCs is controlled by “expect”-like scripts. For a list of currently supported devices, see the configuration file /etc/powerman/powerman.conf.

To install PowerMan, run zypper in powerman.

To configure it, include the appropriate device file for your RPC (/etc/powerman/*.dev) in /etc/powerman/powerman.conf and add devices and nodes. The device “type” needs to match the “specification” name in one of the included device files. The list of “plugs” used for nodes need to match an entry in the “plug name” list.

After configuring PowerMan, start its service by:

systemctl start powerman.service

To start PowerMan automatically after every boot, run:

systemctl enable powerman.service

Optionally, PowerMan can connect to a remote PowerMan instance. To enable this, add the option listen to /etc/powerman/powerman.conf.

Important: Unencrypted Transfer

When connecting to a remote PowerMan instance, data is transferred unencrypted. Therefore, use this feature only if the network is appropriately secured.

rasdaemon is a RAS (Reliability, Availability and Serviceability) logging tool. It records memory errors using the EDAC tracing events. EDAC drivers in the Linux kernel handle detection of ECC errors from memory controllers.

rasdaemon can be used on large memory systems to track, record and localize memory errors and how they evolve over time to detect hardware degradation. Furthermore, it can be used to localize a faulty DIMM on the board.

To check whether the EDAC drivers are loaded, execute:

ras-mc-ctl --status

The command should return ras-mc-ctl: drivers are loaded. If it indicates that the drivers are not loaded, EDAC may not be supported on your board.

To start rasdaemon, run systemctl start rasdaemon.service. To start rasdaemon automatically at boot time, execute systemctl enable rasdaemon.service. The daemon will log information to /var/log/messages and to an internal database. A summary of the stored errors can be obtained with:

ras-mc-ctl --summary

The errors stored in the database can be viewed with

ras-mc-ctl --errors

Optionally, you can load the DIMM labels silk-screened on the system board to more easily identify the faulty DIMM. To do so, before starting rasdaemon, run:

systemctl start ras-mc-ctl start

For this to work, you need to set up a layout description for the board. There are no descriptions supplied by default. To add a layout description, create a file with an arbitrary name in the directory /etc/ras/dimm_labels.d/. The format is:

Vendor: VENDOR-NAME
  Model: MODEL-NAME
    LABEL: MC.TOP.MID.LOW

Slurm is an open-source, fault-tolerant, and highly scalable cluster management and job scheduling system for Linux clusters containing up to 65,536 nodes. Components include machine status, partition management, job management, scheduling and accounting modules.

For a minimal setup to run Slurm with munge support on one compute node and multiple control nodes, follow these instructions:

Note: Epilog Script

The standard epilog script will kill all remaining processes of a user on a node. If this behavior is not wanted, disable the standard epilog script.

For further documentation, see the Quick Start Administrator Guide (https://slurm.schedmd.com/quickstart_admin.html) and Quick Start User Guide (https://slurm.schedmd.com/quickstart.html). There is further in-depth documentation on the Slurm documentation page (https://slurm.schedmd.com/documentation.html).

The memkind library is a user-extensible heap manager built on top of jemalloc which enables control of memory characteristics and a partitioning of the heap between kinds of memory. The kinds of memory are defined by operating system memory policies that have been applied to virtual address ranges. Memory characteristics supported by memkind without user extension include control of NUMA and page size features.

For more information, see:

This tool is only available for x86-64.

munge allows users to connect as the same user from a machine to any other machine which shares the same secret key. This can be used to set up a cluster of machines between which the user can connect and execute commands without any additional authentication.

The munge authentication is based on a single shared key. This key is located under /etc/munge/munge.key. At the installation time of the munge package an individual munge key is created from the random source /dev/urandom. This key has to be the same on all systems that should allow login to each other: To set up munge authentication on these machines copy the munge key from one machine (ideally a head node of the cluster) to the other machines within this cluster:

scp /etc/munge/munge.key root@NODE_N:/etc/munge/munge.key

Then enable and start the service munge on each machine that users are expected to log in to:

systemctl enable munge.service
systemctl start munge.service

If several nodes are installed, you must select and synchronize one key to all other nodes in the cluster. This key file should belong to the munge user and must have the access rights 0400.

mrsh is a set of remote shell programs using the munge authentication system instead of reserved ports for security.

It can be used as a drop-in replacement for rsh and rlogin.

To install mrsh, do the following:

To set up a cluster of machines allowing remote login from each other, first follow the instructions for setting up and starting munge authentication in Section 8.14, “munge Authentication”. After munge has been successfully started, enable and start mrlogin on each machine on which the user will log in:

systemctl enable mrlogind.socket mrshd.socket
systemctl start mrlogind.socket mrshd.socket

To start mrsh support at boot, run:

systemctl enable munge.service
systemctl enable mrlogin.service

We do not recommend using mrsh when logged in as the user root. This is disabled by default. To enable it anyway, run:

echo "mrsh" >> /etc/securetty
echo "mrlogin" >> /etc/securetty

FFTW is a C subroutine library for computing the Discrete Fourier Transform (DFT) in one or more dimensions, of both real and complex data, and of arbitrary input size.

This library is available as both a serial and an MPI-enabled variant. This module requires a compiler toolchain module loaded. To select an MPI variant, the respective MPI module needs to be loaded beforehand. To load this module, run:

module load fftw3

List of master packages:

For general information about Lmod and modules, see Section 8.7, “Lmod — Lua-based Environment Modules”.

HDF5 is a data model, library, and file format for storing and managing data. It supports an unlimited variety of data types, and is designed for flexible and efficient I/O and for high volume and complex data. HDF5 is portable and extensible, allowing applications to evolve in their use of HDF5.

There are serial and MPI variants of this library available. All flavors require loading a compiler toolchain module beforehand. The MPI variants also require loading the correct MPI flavor module.

To load the highest available serial version of this module run:

module load hdf5

When an MPI flavor is loaded, the MPI version of this module can be loaded by:

module load phpdf5

List of master packages:

For general information about Lmod and modules, see Section 8.7, “Lmod — Lua-based Environment Modules”.

The NetCDF software libraries for C, C++, FORTRAN, and Perl are a set of software libraries and self-describing, machine-independent data formats that support the creation, access, and sharing of array-oriented scientific data.

The packages with names starting with netcdf provide C bindings for the NetCDF API. These are available with and without MPI support.

There are serial and MPI variants of this library available. All flavors require loading a compiler toolchain module beforehand. The MPI variants also require loading the correct MPI flavor module.

The MPI variant becomes available when the MPI module is loaded. Both variants require loading a compiler toolchain module beforehand. To load the highest version of the non-MPI netcdf module, run:

module load netcdf

To load the highest available MPI version of this module, run:

module load pnetcdf

List of master packages:

netcdf-cxx4 provides a C++ binding for the NetCDF API.

This module requires loading a compiler toolchain module beforehand. To load this module, run:

module load netcdf-cxx4

List of master packages:

The netcdf-fortran packages provide FORTRAN bindings for the NetCDF API, with and without MPI support.

For general information about Lmod and modules, see Section 8.7, “Lmod — Lua-based Environment Modules”.

NumPy is a general-purpose array-processing package designed to efficiently manipulate large multi-dimensional arrays of arbitrary records without sacrificing too much speed for small multi-dimensional arrays.

NumPy is built on the Numeric code base and adds features introduced by numarray as well as an extended C API and the ability to create arrays of arbitrary type which also makes NumPy suitable for interfacing with general-purpose data-base applications.

There are also basic facilities for discrete Fourier transform, basic linear algebra and random number generation.

This package is available both for Python 2 and Python 3. The specific compiler toolchain and MPI library flavor modules must be loaded for this library. The correct library module for the Python version used needs to be specified when loading this module. To load this module, run:

List of master packages:

OpenBLAS is an optimized BLAS (Basic Linear Algebra Subprograms) library based on GotoBLAS2 1.3, BSD version. It provides the BLAS API. It is shipped as a package enabled for environment modules and thus requires using Lmod to select a version. There are two variants of this library, an OpenMP-enabled variant and a pthreads variant.

The OpenMP variant covers all use cases:

When linking statically, ensure that libgomp.a is included by adding the linker flag -lgomp.

The pthreads variant of the OpenBLAS library can improve the performance of single-threaded programs. The number of threads used can be controlled with the environment variable OPENBLAS_NUM_THREADS.

This module requires loading a compiler toolchain beforehand. To select the latest version of this module provided, run:

List of master package for:

For general information about Lmod and modules, see Section 8.7, “Lmod — Lua-based Environment Modules”.

PAPI (package papi) provides a tool with a consistent interface and methodology for use of the performance counter hardware found in most major microprocessors.

This package serves all compiler toolchains and does not require a compiler toolchain to be selected. The latest version provided can be selected by running:

module load papi

List of master packages:

For general information about Lmod and modules, see Section 8.7, “Lmod — Lua-based Environment Modules”.

PETSc is a suite of data structures and routines for the scalable (parallel) solution of scientific applications modeled by partial differential equations.

This module requires loading a compiler toolchain as well as an MPI library flavor beforehand. To load this module, run:

module load petsc

List of master packages:

For general information about Lmod and modules, see Section 8.7, “Lmod — Lua-based Environment Modules”.

The library ScaLAPACK (short for "Scalable LAPACK") includes a subset of LAPACK routines designed for distributed memory MIMD-parallel computers.

This library requires loading both a compiler toolchain and an MPI library flavor beforehand. To load this library, run:

module load scalapack

List of master packages:

For general information about Lmod and modules, see Section 8.7, “Lmod — Lua-based Environment Modules”.