Jump to content Logo Back to Release Notes for SUSE products ? Release Notes Show Contents: Release Notes Top 1. 1 About the Release Notes 2. 2 SUSE Linux Enterprise for High-Performance Computing 3. 3 Technology Previews 4. 4 Installation and Upgrade 5. 5 Functionality 6. 6 HPC Libraries 7. 7 Updated Packages 8. 8 Obtaining Source Code 9. 9 Legal Notices SUSE Linux Enterprise for High-Performance Computing 15 SP1 Release Notes # SUSE Linux Enterprise for High-Performance Computing is a highly scalable, high performance open-source operating system designed to utilize the power of parallel computing. This document provides an overview of high-level general features, capabilities, and limitations of SUSE Linux Enterprise for High-Performance Computing 15 SP1 and important product updates. This product will be released in June 2019. The latest version of these release notes is always available at https://www.suse.com/releasenotes. Drafts of the general documentation can be found at http://susedoc.github.io/. Publication Date: 2019-03-29, Version: 15.100000000.20190329 1 About the Release Notes 2 SUSE Linux Enterprise for High-Performance Computing 2.1 Hardware Platform Support 2.2 Important Sections of This Document 2.3 Support and Life Cycle 2.4 Support Statement for SUSE Linux Enterprise for High-Performance Computing 2.5 Documentation and Other Information 3 Technology Previews 4 Installation and Upgrade 4.1 System Roles for SUSE Linux Enterprise for High-Performance Computing 15 SP1 4.2 Installation 4.3 Upgrade-Related Notes 5 Functionality 5.1 cpuid ? x86 CPU Identification Tool 5.2 ConMan ? The Console Manager 5.3 Ganglia ? System Monitoring 5.4 Genders ? Static Cluster Configuration Database 5.5 GNU Compiler Collection for HPC 5.6 hwloc ? Portable Abstraction of Hierarchical Architectures for High-Performance Computing 5.7 Lmod ? Lua-based Environment Modules 5.8 ohpc ? OpenHPC Compatibility Macros 5.9 pdsh ? Parallel Remote Shell Program 5.10 PowerMan ? Centralized Power Control for Clusters 5.11 rasdaemon ? Utility to Log RAS Error Tracings 5.12 Slurm ? Utility for HPC Workload Management 5.13 Enabling the pam_slurm_adopt Module 5.14 memkind ? Heap Manager for Heterogeneous Memory Platforms and Mixed Memory Policies 5.15 munge Authentication 5.16 mrsh/mrlogin ? Remote Login Using munge Authentication 6 HPC Libraries 6.1 FFTW HPC Library ? Discrete Fourier Transforms 6.2 HDF5 HPC Library ? Model, Library, File Format for Storing and Managing Data 6.3 NetCDF HPC Library ? Implementation of Self-Describing Data Formats 6.4 NumPy Python Library 6.5 OpenBLAS Library ? Optimized BLAS Library 6.6 PAPI HPC Library ? Consistent Interface for Hardware Performance Counters 6.7 PETSc HPC Library ? Solver for Partial Differential Equations 6.8 ScaLAPACK HPC Library ? LAPACK Routines 7 Updated Packages 7.1 Slurm Has Been Updated From version 17 to version 18 8 Obtaining Source Code 9 Legal Notices 1 About the Release Notes # The most recent version of the Release Notes is available online at https:// www.suse.com/releasenotes. Entries can be listed multiple times if they are important and belong to multiple sections. Release notes only list changes that happened between two subsequent releases. Always review all release notes documents that apply in your upgrade scenario. 2 SUSE Linux Enterprise for High-Performance Computing # SUSE Linux Enterprise for High-Performance Computing is a highly scalable, high performance open-source operating system designed to utilize the power of parallel computing for modeling, simulation and advanced analytics workloads. SUSE Linux Enterprise for High-Performance Computing 15 SP1 provides tools and libraries related to High Performance Computing. This includes: * Workload manager * Remote and parallel shells * Performance monitoring and measuring tools * Serial console monitoring tool * Cluster power management tool * A tool for discovering the machine hardware topology * System monitoring * A tool for monitoring memory errors * A tool for determining the CPU model and its capabilities (x86-64 only) * User-extensible heap manager capable of distinguishing between different kinds of memory (x86-64 only) * Serial and parallel computational libraries providing the common standards BLAS, LAPACK, ... * Various MPI implementations * Serial and parallel libraries for the HDF5 file format 2.1 Hardware Platform Support # SUSE Linux Enterprise for High-Performance Computing 15 SP1 is available for the Intel 64/AMD64 (x86-64) and AArch64 platforms. 2.2 Important Sections of This Document # If you are upgrading from a previous SUSE Linux Enterprise for High-Performance Computing release, you should review at least the following sections: * Section 2.4, ?Support Statement for SUSE Linux Enterprise for High-Performance Computing? * Section 4.3, ?Upgrade-Related Notes? 2.3 Support and Life Cycle # SUSE Linux Enterprise for High-Performance Computing is backed by award-winning support from SUSE, an established technology leader with a proven history of delivering enterprise-quality support services. SUSE Linux Enterprise for High-Performance Computing 15 has a 13-year life cycle, with 10 years of General Support and 3 years of Extended Support. The current version (SP1) will be fully maintained and supported until 6 months after the release of SUSE Linux Enterprise for High-Performance Computing 15 SP2. Any release package is fully maintained and supported until the availability of the next release. Extended Service Pack Overlay Support (ESPOS) and Long Term Service Pack Support (LTSS) are also available for this product. If you need additional time to design, validate and test your upgrade plans, Long Term Service Pack Support (LTSS) can extend the support you get by an additional 12 to 36 months in 12-month increments, providing a total of 3 to 5 years of support on any given Service Pack. For more information, see: * The support policy at https://www.suse.com/support/policy.html * Long Term Service Pack Support page at https://www.suse.com/support/ programs/long-term-service-pack-support.html 2.4 Support Statement for SUSE Linux Enterprise for High-Performance Computing # To receive support, you need an appropriate subscription with SUSE. For more information, see https://www.suse.com/support/programs/subscriptions/. The following definitions apply: L1 Problem determination, which means technical support designed to provide compatibility information, usage support, ongoing maintenance, information gathering and basic troubleshooting using available documentation. L2 Problem isolation, which means technical support designed to analyze data, reproduce customer problems, isolate problem area and provide a resolution for problems not resolved by Level 1 or prepare for Level 3. L3 Problem resolution, which means technical support designed to resolve problems by engaging engineering to resolve product defects which have been identified by Level 2 Support. For contracted customers and partners, SUSE Linux Enterprise for High-Performance Computing 15 SP1 is delivered with L3 support for all packages, except for the following: * Technology Previews, see Section 3, ?Technology Previews? * Sound, graphics, fonts and artwork * Packages that require an additional customer contract SUSE will only support the usage of original packages. That is, packages that are unchanged and not recompiled. 2.5 Documentation and Other Information # 2.5.1 On the Product Medium # * For general product information, see the file README and the file README.BETA in the top level of the product medium. * For a chronological log of all changes made to updated packages, see the file ChangeLog in the top level of the product medium. * Detailed change log information about a particular package is available using RPM: rpm --changelog -qp FILE_NAME.rpm (Replace FILE_NAME.rpm with the name of the RPM.) * For more information, see the directory docu of the product medium of SUSE Linux Enterprise for High-Performance Computing 15 SP1. 2.5.2 Externally Provided Documentation # * Find a collection of White Papers in the SUSE Linux Enterprise for High-Performance Computing Resource Library at https://www.suse.com/ products/server/hpc#resources. 3 Technology Previews # Technology previews are packages, stacks, or features delivered by SUSE which are not supported. They may be functionally incomplete, unstable or in other ways not suitable for production use. They are included for your convenience and give you a chance to test new technologies within an enterprise environment. Whether a technology preview becomes a fully supported technology later depends on customer and market feedback. Technology previews can be dropped at any time and SUSE does not commit to providing a supported version of such technologies in the future. Give your SUSE representative feedback about technology previews, including your experience and use case. 4 Installation and Upgrade # SUSE Linux Enterprise for High-Performance Computing comes with a number of preconfigured system roles for HPC. These roles provide a set of preselected packages typical for the specific role, as well as an installation workflow that will configure the system to make the best use of system resource based on a typical role use case. 4.1 System Roles for SUSE Linux Enterprise for High-Performance Computing 15 SP1 # With SUSE Linux Enterprise for High-Performance Computing 15 SP1, 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: HPC Management Server (Head Node) This role includes the following features: + Uses XFS as the default root file system + Includes HPC-enabled libraries + Disables firewall and Kdump services + Installs controller for the Slurm Workload Manager + Mounts a large scratch partition to /var/tmp HPC Compute Node This role includes the following features: + Uses XFS as the default root file system + Includes HPC-enabled libraries + Disables firewall and Kdump services + Based from minimal setup configuration + Installs client for the Slurm Workload Manager + Does not create a separate home partition + Mounts a large scratch partition to /var/tmp HPC Development Node This role includes the following features: + Includes HPC-enabled libraries + Adds compilers and development toolchain 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 5.7, ?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 5.16, ?mrsh/mrlogin ? Remote Login Using munge Authentication? and Section 5.15, ?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 5.3, ?Ganglia ? System Monitoring?. The system roles are only available for new installations of SUSE Linux Enterprise for High-Performance Computing. 4.2 Installation # This section includes information related to the initial installation of the SUSE Linux Enterprise for High-Performance Computing 15 SP1. 4.3 Upgrade-Related Notes # This section includes upgrade-related information for the SUSE Linux Enterprise for High-Performance Computing 15 SP1. You can upgrade to SUSE Linux Enterprise for High-Performance Computing 15 SP1 from SLES 12 SP3 or SUSE Linux Enterprise for High-Performance Computing 12 SP3. When upgrading from SLES 12 SP3, the upgrade will only be performed if the SUSE Linux Enterprise for High-Performance Computing 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 SUSE Linux Enterprise for High-Performance Computing 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 for High-Performance Computing 15 SP1, 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). 5 Functionality # This section comprises information about packages and their functionality, as well as additions, updates, removals and changes to the package layout of software. 5.1 cpuid ? x86 CPU Identification Tool # 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. 5.2 ConMan ? The Console Manager # ConMan is a serial console management program designed to support a large number of console devices and simultaneous users. It supports: * local serial devices * remote terminal servers (via the telnet protocol) * IPMI Serial-Over-LAN (via FreeIPMI) * Unix domain sockets * external processes (for example, using 'expect' scripts for telnet, ssh, or ipmi-sol connections) ConMan can be used for monitoring, logging and optionally timestamping console device output. To install ConMan, run zypper in conman. Important 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: * ConMan comes with a number of expect-scripts: check /usr/lib/conman/exec. * Input to conman is not echoed in interactive mode. This can be changed by entering the escape sequence &E. * When pressing Enter in interactive mode, no line feed is generated. To generate a line feed, press Ctrl?L. For more information about options, see the man page of ConMan. 5.3 Ganglia ? System Monitoring # 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. 5.4 Genders ? Static Cluster Configuration Database # 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: * genders * genders-base * genders-devel * python-genders * genders-perl-compat * libgenders0 * libgendersplusplus2 5.5 GNU Compiler Collection for HPC # 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 5.7, ?Lmod ? Lua-based Environment Modules?. 5.6 hwloc ? Portable Abstraction of Hierarchical Architectures for High-Performance Computing # 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. 5.7 Lmod ? Lua-based Environment Modules # 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. Installation and Basic Usage# 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//init/bash /usr/share/lmod//init/ksh /usr/share/lmod//init/tcsh /usr/share/lmod//init/zsh /usr/share/lmod//init/sh Pick the one appropriate for your shell. Then add the following to the init file of your shell: . /usr/share/lmod//init/ To obtain , run: rpm -q lua-lmod | sed "s/.*-\([^-]\+\)-.*/\1/" The init script adds the command module. Listing Available Modules# 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. Listing Loaded Modules# 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. Gathering Information About a Module# 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. Loading Modules# 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. Environment Variables# 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# For more information on Lmod, see https://lmod.readthedocs.org. 5.8 ohpc ? OpenHPC Compatibility Macros # ohpc contains compatibility macros to build OpenHPC packages on SUSE Linux Enterprise. To install ohpc, run: zypper in ohpc. 5.9 pdsh ? Parallel Remote Shell Program # 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 5.16, ?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. 5.10 PowerMan ? Centralized Power Control for Clusters # PowerMan allows manipulating remote power control devices (RPC) from a central location. It can control: * local devices connected to a serial port * RPCs listening on a TCP socket * RPCs which are accessed through an external program 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, do: 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 Important: Unencrypted Transfer Data is transferred unencrypted, therefore this is not recommended unless the network is appropriately secured. 5.11 rasdaemon ? Utility to Log RAS Error Tracings # 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 5.12 Slurm ? Utility for HPC Workload Management # 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: 1. Before installing Slurm, create a user and a group called slurm. Important Important: Make Sure of Consistent UIDs and GIDs for Slurm's Accounts For security reasons, Slurm does not run as the user root but under its own user. It is important that the user slurm has the same UID/GID across all nodes of the cluster. If this user/group does not exist, the package slurm creates this user and group when it is installed. However, this does not guarantee that the generated UIDs/GIDs will be identical on all systems. Therefore, we strongly advise you to create the user/group slurm before installing slurm. If you are using a network directory service such as LDAP for user and group management, you can use it to provide the slurm user/ group as well. 2. Install slurm-munge on the control and compute nodes: zypper in slurm-munge 3. Configure, enable and start "munge" on the control and compute nodes as described in Section 5.16, ?mrsh/mrlogin ? Remote Login Using munge Authentication?. 4. On the compute node, edit /etc/slurm/slurm.conf: a. Configure the parameter ControlMachine=CONTROL_MACHINE with the host name of the control node. To find out the correct host name, run hostname -s on the control node. b. Additionally add: NodeName=NODE_LIST Sockets=SOCKETS \ CoresPerSocket=CORES_PER_SOCKET \ ThreadsPerCore=THREADS_PER_CORE \ State=UNKNOWN and PartitionName=normal Nodes=NODE_LIST \ Default=YES MaxTime=24:00:00 State=UP where NODE_LIST is the list of compute nodes (that is, the output of hostname -s run on each compute node (either comma-separated or as ranges: foo[1-100]). Additionally, SOCKETS denotes the number of sockets, CORES_PER_SOCKET the number of cores per socket, THREADS_PER_CORE the number of threads for CPUs which can execute more than one thread at a time. (Make sure that SOCKETS * CORES_PER_SOCKET * THREADS_PER_CORE does not exceed the number of system cores on the compute node). c. On the control node, copy /etc/slurm/slurm.conf to all compute nodes: scp /etc/slurm/slurm.conf COMPUTE_NODE:/etc/slurm/ d. On the control node, start slurmctld: systemctl start slurmctld.service Also enable it so that it starts on every boot: systemctl enable slurmctld.service e. On the compute nodes, start and enable slurmd: systemctl start slurmd.service systemctl enable slurmd.service The last line causes slurmd to be started on every boot automatically. 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). 5.13 Enabling the pam_slurm_adopt Module # The pam_slurm_adopt module allows restricting access to compute nodes to those users that have jobs running on them. It can also take care of run-away processes from user's jobs and end these processes when the job has finished. pam_slurm_adopt works by binding the login process of a user and all its child processes to the cgroup of a running job. It can be enabled with following steps: 1. In the configuration file slurm.conf, set the option PrologFlags=contain. Make sure the option ProctrackType=proctrack/cgroup is also set. 2. Restart the services slurmctld and slurmd. For this change to take effect, it is not sufficient to issue the command scontrol reconfigure. 3. Decide whether to limit resources: + If resources are not limited, user processes can continue running on a node even after the job to which they were bound has finished. + If resources are limited using a cgroup, user processes will be killed when the job finishes, and the controlling cgroup is deactivated. To activate resource limits via a cgroup, in the file /etc/slurm/ cgroup.conf, set the option ConstrainCores=yes. Due to the complexity of accurately determining RAM requirements of jobs, limiting the RAM space is not recommended. 4. Install the package slurm-pam_slurm: zypper install slurm-pam_slurm 5. (Optional) You can disallow logins by users who have no running job in the machine: * Disabling SSH Logins Only: In the file /etc/pam.d/ssh, add the option: account required pam_slurm_adopt.so * Disabling All Types of Logins: In the file /etc/pam.d/common-account, add the option: account required pam_slurm_adopt.so 5.14 memkind ? Heap Manager for Heterogeneous Memory Platforms and Mixed Memory Policies # 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: * the man pages memkind and hbwallow * https://github.com/memkind/memkind * https://memkind.github.io/memkind/ Note This tool is only available for x86-64. 5.15 munge Authentication # 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: systemctl enable munge.service systemctl start munge.service If several nodes are installed, one key must be selected and synchronized to all the other nodes in the cluster. This key file should belong to the munge user and must have the access rights 0400. 5.16 mrsh/mrlogin ? Remote Login Using munge Authentication # 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: * If only the mrsh client is required (without allowing remote login to this machine), use: zypper in mrsh. * To allow logging in to a machine, the server needs to be installed: zypper in mrsh-server. * To get a drop-in replacement for rsh and rlogin, run: zypper in mrsh-rsh-server-compat or zypper in mrsh-rsh-compat. 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 5.15, ?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 6 HPC Libraries # Library packages which support environment modules follow a distinctive naming scheme: all packages have the compiler suite and, if built with MPI support, the MPI flavor in their name: *-[MPI_FLAVOR]-COMPILER-hpc*. To support a parallel installation of multiple versions of a library package, the package name contains the version number (with dots . replaced by underscores _). To simplify the installation of a library, master -packages are supplied which will ensure that the latest version of a package is installed. When these master packages are updated, the latest version of the respective library packages will be installed while leaving previous versions installed. Library packages are split between runtime and compile time packages. The compile time packages typically supply include files and .so-files for shared libraries. Compile time package names end with -devel. For some libraries static (.a) libraries are supplied as well, package names for these end with -devel-static. As an example: Package names of the ScaLAPACK library version 2.0.2 built with GCC for Open MPI v1: * library package: libscalapack2_2_0_2-gnu-openmpi1-hpc * library master package: libscalapack2-gnu-openmpi1-hpc * development package: libscalapack2_2_0_2-gnu-openmpi1-hpc-devel * development master package: libscalapack2-gnu-openmpi1-hpc-devel * static library package: libscalapack2_2_0_2-gnu-openmpi1-hpc-devel-static (Note that the digit 2 appended to the library name denotes the .so version of the library). To install a library packages run zypper in LIBRARY-MASTER-PACKAGE. To install a development file, run zypper in LIBRARY-DEVEL-MASTER-PACKAGE. Presently, the GNU compiler collection version 4.8 as provided with SUSE Linux Enterprise 15 and the MPI flavors Open MPI v.2 and MVAPICH2 are supported. 6.1 FFTW HPC Library ? Discrete Fourier Transforms # 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: * libfftw3-gnu-hpc * fftw3-gnu-hpc-devel * libfftw3-gnu-openmpi1-hpc * fftw3-gnu-openmpi1-hpc-devel * libfftw3-gnu-mvapich2-hpc * fftw3-gnu-mvapich2-hpc-devel For general information about Lmod and modules, see Section 5.7, ?Lmod ? Lua-based Environment Modules?. 6.2 HDF5 HPC Library ? Model, Library, File Format for Storing and Managing Data # 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: * hdf5-examples * hdf5-gnu-hpc-devel * libhdf5-gnu-hpc * libhdf5_cpp-gnu-hpc * libhdf5_fortran-gnu-hpc * libhdf5_hl_cpp-gnu-hpc * libhdf5_hl_fortran-gnu-hpc * hdf5-gnu-openmpi1-hpc-devel * libhdf5-gnu-openmpi1-hpc * libhdf5_fortran-gnu-openmpi1-hpc * libhdf5_hl_fortran-gnu-openmpi1-hpc * hdf5-gnu-mvapich2-hpc-devel * libhdf5-gnu-mvapich2-hpc * libhdf5_fortran-gnu-mvapich2-hpc * libhdf5_hl_fortran-gnu-mvapich2-hpc For general information about Lmod and modules, see Section 5.7, ?Lmod ? Lua-based Environment Modules?. 6.3 NetCDF HPC Library ? Implementation of Self-Describing Data Formats # 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. netcdf Packages# 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-gnu-hpc * netcdf-gnu-hpc-devel * netcdf-gnu-hpc * netcdf-gnu-hpc-devel * netcdf-gnu-openmpi1-hpc * netcdf-gnu-openmpi1-hpc-devel * netcdf-gnu-mvapich2-hpc * netcdf-gnu-mvapich2-hpc-devel netcdf-cxx 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: * libnetcdf-cxx4-gnu-hpc * libnetcdf-cxx4-gnu-hpc-devel * netcdf-cxx4-gnu-hpc-tools netcdf-fortran Packages# The netcdf-fortran packages provide FORTRAN bindings for the NetCDF API, with and without MPI support. For More Information# For general information about Lmod and modules, see Section 5.7, ?Lmod ? Lua-based Environment Modules?. 6.4 NumPy Python Library # 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: * for Python 2: module load python2-numpy * for Python 3: module load python3-numpy List of master packages: * python2-numpy-gnu-hpc * python2-numpy-gnu-hpc-devel * python3-numpy-gnu-hpc * python3-numpy-gnu-hpc-devel 6.5 OpenBLAS Library ? Optimized BLAS Library # 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. OpenMP-Enabled Variant# The OpenMP variant covers all use cases: * Programs using OpenMP. This requires the OpenMP-enabled library version to function correctly. * Programs using pthreads. This requires an OpenBLAS library without pthread support. This can be achieved with the OpenMP-version. We recommend limiting the number of threads that are used to 1 by setting the environment variable OMP_NUM_THREADS=1. * Programs without pthreads and without OpenMP. Such programs can still take advantage of the OpenMP optimization in the library by linking against the OpenMP variant of the library. When linking statically, ensure that libgomp.a is included by adding the linker flag -lgomp. pthreads Variant# 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. Installation and Usage# This module requires loading a compiler toolchain beforehand. To select the latest version of this module provided, run: * OpenMP version: module load openblas-pthreads * pthreads version: module load openblas List of master package for: * libopenblas-gnu-hpc * libopenblas-gnu-hpc-devel * libopenblas-pthreads-gnu-hpc * libopenblas-pthreads-gnu-hpc-devel For general information about Lmod and modules, see Section 5.7, ?Lmod ? Lua-based Environment Modules?. 6.6 PAPI HPC Library ? Consistent Interface for Hardware Performance Counters # 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: * papi-hpc * papi-hpc-devel For general information about Lmod and modules, see Section 5.7, ?Lmod ? Lua-based Environment Modules?. 6.7 PETSc HPC Library ? Solver for Partial Differential Equations # 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: * libpetsc-gnu-openmpi1-hpc * petsc-gnu-openmpi1-hpc-devel * libpetsc-gnu-mvapich2-hpc * petsc-gnu-mvapich2-hpc-devel For general information about Lmod and modules, see Section 5.7, ?Lmod ? Lua-based Environment Modules?. 6.8 ScaLAPACK HPC Library ? LAPACK Routines # 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: * libblacs2-gnu-openmpi1-hpc * libblacs2-gnu-openmpi1-hpc-devel * libscalapack2-gnu-openmpi1-hpc * libscalapack2-gnu-openmpi1-hpc-devel * libblacs2-gnu-mvapich2-hpc * libblacs2-gnu-mvapich2-hpc-devel * libscalapack2-gnu-mvapich2-hpc * libscalapack2-gnu-mvapich2-hpc-devel For general information about Lmod and modules, see Section 5.7, ?Lmod ? Lua-based Environment Modules?. 7 Updated Packages # 7.1 Slurm Has Been Updated From version 17 to version 18 # 7.1.1 Configuration Changes in slurm.conf # When updating from Slurm 17 to 18, make sure to review the following important changes to the configuration file /etc/slurm/slurm.conf: * The epilog script epilog-clean.sh was removed because of its inconsistent behavior when a job finished. To limit the access to compute nodes to users who have jobs running on them, use the PAM module pam_slurm_adopt. For more information, see Section 5.13, ?Enabling the pam_slurm_adopt Module?. * The options ControlMachine, ControlAddr, BackupController, or BackupAddr are deprecated and may be removed in the future. Replace these options by an ordered list of SlurmCtldHost records. * The PreemptType=preempt/job_prio has been removed, use PreemptType=preempt/ qos instead. 7.1.2 Updating # To update slurm from version 17 to version 18, proceed as follows: 1. Stop all Slurm-related services: + slurmctld + slurmd + slurmdbd (if running) 2. Create a backup of the configuration files in /etc/slurm, the Saved State directory (defined in StateSaveLocation), /var/lib/slurm and also the munge key /etc/munge/munge.key. 3. (Optional) If you are using an accounting database, back up, update, and restart the database server: a. Create a backup of the accounting database, as the update irreversibly converts the database. b. Update the package slurm-slurmdbd with the command: zypper update slurm-slurmdbd c. The conversion begins automatically when slurmdbd is started the next time. However, when starting slurmdbd as a systemd service, the conversion process will likely take so long that the command would run into a systemd timeout. Therefore, trigger the database conversion by manually start the daemon slurmdbd with: slurmdbd -D Monitor the process until the database conversion is complete. When the conversion succeeds, the message Conversion done: success! will be shown. d. Restart the service slurmdbd: systemctl start slurmdbd 4. Update the package slurm-slurmctld and other Slurm-related packages: zypper update slurm slurm-slurmctld slurm-node 5. Restart the service slurmctld: systemctl start slurmctld 6. Finally, restart the service slurmd: systemctl start slurmd 8 Obtaining Source Code # This SUSE product includes materials licensed to SUSE under the GNU General Public License (GPL). The GPL requires SUSE to provide the source code that corresponds to the GPL-licensed material. The source code is available for download at http://www.suse.com/download-linux/source-code.html. Also, for up to three years after distribution of the SUSE product, upon request, SUSE will mail a copy of the source code. Requests should be sent by e-mail to mailto:sle_source_request@suse.com or as otherwise instructed at http:// www.suse.com/download-linux/source-code.html. SUSE may charge a reasonable fee to recover distribution costs. 9 Legal Notices # SUSE makes no representations or warranties with regard to the contents or use of this documentation, and specifically disclaims any express or implied warranties of merchantability or fitness for any particular purpose. Further, SUSE reserves the right to revise this publication and to make changes to its content, at any time, without the obligation to notify any person or entity of such revisions or changes. Further, SUSE makes no representations or warranties with regard to any software, and specifically disclaims any express or implied warranties of merchantability or fitness for any particular purpose. Further, SUSE reserves the right to make changes to any and all parts of SUSE software, at any time, without any obligation to notify any person or entity of such changes. Any products or technical information provided under this Agreement may be subject to U.S. export controls and the trade laws of other countries. You agree to comply with all export control regulations and to obtain any required licenses or classifications to export, re-export, or import deliverables. You agree not to export or re-export to entities on the current U.S. export exclusion lists or to any embargoed or terrorist countries as specified in U.S. export laws. You agree to not use deliverables for prohibited nuclear, missile, or chemical/biological weaponry end uses. Refer to https://www.suse.com/company /legal/ for more information on exporting SUSE software. SUSE assumes no responsibility for your failure to obtain any necessary export approvals. Copyright ? 2010-2019 SUSE LLC. This release notes document is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License (CC-BY-ND-4.0). You should have received a copy of the license along with this document. If not, see https://creativecommons.org/licenses/by-nd/4.0/. SUSE has intellectual property rights relating to technology embodied in the product that is described in this document. In particular, and without limitation, these intellectual property rights may include one or more of the U.S. patents listed at https://www.suse.com/company/legal/ and one or more additional patents or pending patent applications in the U.S. and other countries. For SUSE trademarks, see SUSE Trademark and Service Mark list (https:// www.suse.com/company/legal/). All third-party trademarks are the property of their respective owners. Share this page: Facebook ? Google+ ? Twitter ? E-Mail Print this page ? 2019 SUSE * Careers * Legal * About * Contact Us