1. Introduction

1.1. Document Scope and Assumptions

This document provides an overview and introduction to the use of the IBM Power9 (SCOUT) located at the ARL DSRC, along with a description of the specific computing environment on SCOUT. The intent of this guide is to provide information that will enable the average user to perform computational tasks on the system. To receive the most benefit from the information provided here, you should be proficient in the following areas:

1.2. Policies to Review

Users are expected to be aware of the following policies for working on SCOUT.

1.2.1. Login Node Abuse Policy

Memory or CPU intensive programs running on the login nodes can significantly affect all users of the system. Therefore, only small applications requiring a minimal amount of runtime and memory are allowed on the login nodes. Any job running on the login nodes that affects their overall interactive performance may be unilaterally terminated.

1.2.2. Workspace Purge Policy

The /work1 directory is subject to a 21-day purge policy. A system "scrubber" monitors scratch space utilization, and if available space becomes low, files not accessed within 21 days are subject to removal, although files may remain longer if the space permits. There are no exceptions to this policy.

Note! If it is determined as part of the normal purge cycle that files in your $WORKDIR directory must be deleted, you WILL NOT be notified prior to deletion. You are responsible to monitor your workspace to prevent data loss.

1.3. Obtaining an Account

The process of getting an account on the HPC systems at any of the DSRCs begins with getting an account on the HPCMP Portal to the Information Environment, commonly called a "pIE User Account." If you do not yet have a pIE User Account, please visit HPC Centers: Obtaining An Account and follow the instructions there. Once you have an active pIE User Account, visit the ARL accounts page for instructions on how to request accounts on the ARL DSRC HPC systems. If you need assistance with any part of this process, please contact the HPC Help Desk at accounts@helpdesk.hpc.mil.

1.4. Requesting Assistance

The HPC Help Desk is available to help users with unclassified problems, issues, or questions. Analysts are on duty 8:00 a.m. - 8:00 p.m. Eastern, Monday - Friday (excluding Federal holidays).

You can contact the ARL DSRC directly in any of the following ways for support services not provided by the HPC Help Desk:

For more detailed contact information, please see our Contact Page.

2. System Configuration

2.1. System Summary

SCOUT is an IBM Power9 system. Each login node is populated with two IBM Power9 processors. SCOUT uses the Expanded Data Rate InfiniBand interconnect in a Non-Blocking Fat Tree configuration as its high-speed network for MPI messages and IO traffic. SCOUT has 22 training nodes each with 2 Power9 processors, 512 GB of memory, and 6 NVIDIA V100 GPUs; 128 inference nodes each with 2 Power9 processors, 256 GB of memory, and 4 NVIDIA T4 GPUs; and 2 visualization nodes each with 2 Power9 processors, 512 GB of memory, and 2 NVIDIA V100 GPUs (SRD not yet available).

SCOUT is intended as a batch-scheduled HPC system. Its login nodes are not to be used for large computational (memory, IO, long executions) work. All executions that require large amounts of system resources must be sent to the training or inference nodes by batch job submission.

2.2. Processors

SCOUT uses 2.6-GHz Power9 processors on its nodes. There are 2 processors per node, each with 20 cores, for a total of 40 cores per node. In addition, these processors have a level 3 cache of 120 MB.

2.3. Memory

SCOUT uses both shared and distributed memory models. Memory is shared among all the cores on a node, but is not shared among the nodes across the cluster.

Each login node contains 512 GB of main memory. All memory and cores on the node are shared among all users who are logged in. Therefore, users should not use excessive amounts of memory at any one time.

Each of the 22 training compute nodes has 6 NVIDIA V100 GPUs with 32 GB memory and 512 GB of user-accessible shared memory. Each of the 128 inference nodes has 4 NVIDIA T4 GPUs with 16 GB memory and 256 GB of user-accessible shared memory. Each of the 2 visualization nodes has 2 NVIDIA V100 GPU with 32 GB of Memory and contains 512 GB of user-accessible shared memory.

2.4. Operating System

The operating system on SCOUT is RedHat Linux.

2.5. File Systems

SCOUT has the following file systems available for user storage:

2.5.1. /p/home

This file system is locally mounted from SCOUT's GPFS file system. It has a formatted capacity of 155 TB. All users have a home directory located on this file system which can be referenced by the environment variable $HOME.

2.5.2. /p/scratch1

SCOUT has on-node temporary storage space (/p/scratch1) available on each of the nodes. The capacities for each node type are as follows: Login nodes: 1.5 TB, Training nodes: 12 TB, and Inference and Visualization nodes: 3.3 TB. All users have the ability to access this space, and it can be referenced by the environment variable $LSCRATCH. This space should not be used for anything other than temporary storage, as it will be cleared as needed by the system.

2.5.3. /p/work1

This directory comprises SCOUT's user scratch file area and is a locally mounted GPFS file system. /p/work1 has a formatted capacity of 1.045 PB. All users have a work directory located on /p/work1 which can be referenced by the environment variable $WORKDIR.

2.5.4. /p/app

All center-managed COTS packages are stored in /p/app. This file system is locally mounted from SCOUT's GPFS file system. It has a formatted capacity of 90 TB and can be referenced by the environment variable $CSI_HOME. In addition, users may request space in this area under /p/app/unsupported to store user-managed software packages that they wish to make available to other owner-designated users. This area can be referenced by the environment variable $PROJECTS_HOME. To have space allocated in /p/app/unsupported, submit a request to the ARL DSRC Help Desk. Send e-mail to dsrchelp@arl.army.mil or call 1-800-ARL-1552 (1-800-275-1552) or (410) 278-1700.

2.5.5. /archive

This NFS-mounted file system is accessible from the login nodes on SCOUT. Files in this file system are subject to migration to tape and access may be slower due to the overhead of retrieving files from tape. It has a formatted capacity of 16 TB with a petascale archival tape storage system. The disk portion of the file system is automatically backed up. Users should migrate all large input and output files to this area for long-term storage. Users should also migrate all important smaller files from their home directory in /p/home to this directory for long-term storage. All users have a directory located on this file system which can be referenced by the environment variable $ARCHIVE_HOME.

2.5.6. /tmp or /var/tmp

Never use /tmp or /var/tmp for temporary storage! These directories are not intended for temporary storage of user data, and abuse of these directories could adversely affect the entire system.

2.5.7. /p/cwfs

This path is directed to the Center-Wide File System (CWFS) which is meant for short-term storage (no longer than 120 days). All users have a directory defined in this file system. The environment variable for this is $CENTER. This is accessible from the unclassified HPC system login nodes. The CWFS has a formatted capacity of 3.3 PB and is managed by IBM's Spectrum Scale (formerly GPFS).

2.6. Peak Performance

SCOUT is rated at 1.2 peak PFLOPS.

3. Accessing the System

3.1. Kerberos

A Kerberos client kit must be installed on your desktop system to enable you to get a Kerberos ticket. Kerberos is a network authentication tool that provides secure communication by using secret cryptographic keys. Only users with a valid HPCMP Kerberos authentication can gain access to SCOUT. More information about installing Kerberos clients on your desktop can be found at HPC Centers: Kerberos & Authentication.

3.2. Logging In

The system host name for SCOUT is scout.arl.hpc.mil, which will redirect the user to one of four login nodes. Hostnames and IP addresses to these nodes are available upon request from the HPC Help Desk.

The preferred way to login to SCOUT is via ssh, as follows:

3.3. File Transfers

File transfers to ARL DSRC systems (except for those to the local archive server) must be performed using Kerberized versions of the following tools: scp, mpscp, ftp, sftp, or scampi.

The command below uses secure copy (scp) to copy a single local file into a destination directory on a SCOUT login node. The mpscp command is similar to the scp command, but has a different underlying means of data transfer, and may enable greater transfer rates. The mpscp command has the same syntax as scp.

Both scp and mpscp can be used to send multiple files. This command transfers all files with the .txt extension to the same destination directory.

The example below uses the secure file transfer protocol (sftp) to connect to SCOUT, then uses the sftp "cd" and "put" commands to change to the destination directory and copy a local file there. The sftp "quit" command ends the sftp session. Use the sftp "help" command to see a list of all sftp commands.

Windows users may use a graphical file transfer protocol (ftp) client such as FileZilla.

4. User Environment

4.1. User Directories

4.1.1. Home Directory

When you log on to SCOUT, you will be placed in your home directory, /p/home/username. The environment variable $HOME is automatically set for you and refers to this directory. $HOME is visible to both the login and compute nodes, and may be used to store small user files. However, it has limited capacity and is not backed up on a daily basis and therefore, should not be used for long-term storage.

4.1.2. Work Directory

The path for your working directory on SCOUT's scratch file system is /p/work1/username. The environment variable $WORKDIR is automatically set for you and refers to this directory. $WORKDIR is visible to both the login and compute nodes, and should be used for temporary storage of active data related to your batch jobs.

Note: Although the $WORKDIR environment variable is automatically set for you, the directory itself may not be created. If not, you can create your $WORKDIR directory as follows:

mkdir $WORKDIR

The scratch file system provides 1.2 PB of formatted disk space. This space is not backed up, however, and is subject to a purge policy.

REMEMBER: This file system is considered volatile working space. You are responsible for archiving any data you wish to preserve. To prevent your data from being "scrubbed," you should copy files that you want to keep into your /archive directory (see below) for long-term storage.

4.1.3. Archive Directory

In addition to $HOME and $WORKDIR, each user is also given a directory on the /archive file system. This file system is visible to the login nodes (not the compute nodes) and is the preferred location for long-term file storage. All users have an area defined in /archive for their use, which can be accessed using the $ARCHIVE_HOME environment variable. We recommend that you keep large computational files and more frequently accessed files in the $ARCHIVE_HOME directory. We also recommend that any important files located in $HOME should be copied into $ARCHIVE_HOME as well.

Because the compute nodes are unable to see $ARCHIVE_HOME, you will need to pre-stage your input files to your $WORKDIR from a login node before submitting jobs. After jobs complete, you will need to transfer output files from $WORKDIR to $ARCHIVE_HOME from a login node. This may be done manually or through the transfer queue, which executes serial jobs on login nodes.

4.1.4. Center-Wide File System Directory

The Center-Wide File System (CWFS) provides file storage that is accessible from SCOUT's login nodes and from the HPC Portal. The CWFS allows for file transfers and other file and directory operations from SCOUT using standard Linux commands. Each user has their own directory in the CWFS. The name of your CWFS directory may vary between machines and between centers, but the environment variable $CENTER will always refer to this directory.

The example below shows how to copy a file from your work directory on SCOUT to the CWFS ($CENTER).

While logged into SCOUT, copy your file from your work directory to the CWFS.

% cp $WORKDIR/filename $CENTER

4.2. Shells

The following shells are available on SCOUT: csh, bash, ksh, tcsh, zsh, and sh. To change your default shell, go to pIE (https://ieapp.hpc.mil). Select OpenID Login. Select ether CAC Login or Yubikey. After logging in, select the User Information Environment tab. Then click in "View/Modify personal account information", mid-way down the page you can change your preferred shell via a drop down menu. After selecting a preferred shell, be sure to click on Save Changes, at the bottom of the information section. Your preferred shell will become your default shell on SCOUT and all other clusters where you have an account within 24 hours.

4.3. Environment Variables

A number of environment variables are provided by default on all HPCMP HPC systems. We encourage you to use these variables in your scripts where possible. Doing so will help to simplify your scripts and reduce portability issues if you ever need to run those scripts on other systems. The following environment variables are common to both the login and batch environments:

4.4. Modules

Software modules are a very convenient way to set needed environment variables and include necessary directories in your path so commands for particular applications can be found. We strongly encourage you to use modules. For more information on using modules, see the Modules User Guide.

4.5. Archive Usage

Archive storage is provided through the $ARCHIVE_HOME NFS-mounted file system. All users are automatically provided a directory under this file system. However, it is only accessible from the login nodes. Since space in a user's login home area in /p/home is limited, all large data files requiring permanent storage should be placed in $ARCHIVE_HOME. Also, it is recommended that all important smaller files in /p/home for which a user requires long-term access be copied to $ARCHIVE_HOME as well. For more information on using the archive system, see the Archive System User Guide.

4.6. Login Files

When an account is created on SCOUT, a default .cshrc, and/or .profile file is placed into your home directory. This file contains the default modules setup to configure modules, LSF and other system defaults. We suggest you customize the following: .cshrc.pers or .profile.pers for your shell with any paths, aliases, or libraries you may need to load. The files should be sourced at the end of your .cshrc and/or .profile file as necessary. For example:

5. Program Development

5.1. Programming Models

SCOUT supports two programming models: Message Passing Interface (MPI) and Open Multi-Processing (OpenMP). A hybrid (MPI/OpenMP) programming model is also supported. MPI is an example of a message- or data-passing model. OpenMP only uses shared memory on a node by spawning threads. And, the hybrid model combines both models.

5.1.1. Message Passing Interface (MPI)

SCOUT has two MPI-3.0 standard library suites: IBM Spectrum and OpenMPI. The modules for these MPI libraries are mpi/spectrum/10.03 and mpi/openmpi/latest.

5.1.2. Open Multi-Processing (OpenMP)

SCOUT supports OpenMP through all of its programming environments. OpenMP is a portable, scalable model that gives programmers a simple and flexible interface for developing parallel applications. It supports shared-memory multiprocessing programming in C, C++, and Fortran, and consists of a set of compiler directives, library routines, and environment variables that influence compilation and run-time behavior.

5.1.3. Hybrid Processing (MPI/OpenMP)

In hybrid processing, all intranode parallelization is accomplished using OpenMP, while all internode parallelization is accomplished using MPI. Typically, there is one MPI task assigned per node, with the number of OpenMP threads assigned to each node set at the number of cores available on the node.

5.2. Available Compilers

SCOUT has two compiler suites:

All versions of MPI share a common base set of compilers that are available on both the login and compute nodes.

IBM MPT codes are built using the above compiler commands with addition of "-lmpi" option on the link line. The following additional compiler wrapper scripts are used for building MPI codes:

To select one of these compilers for use, load its associated module. See Relevant Modules (below) for more details.

5.2.1. PGI C, C++, and Fortran Compiler

The latest versions of the PGI compiler suite is also available to provide compatibility and portability of codes from other systems.

Several optimizations and tuning options are available for code developed with all PGI compilers. The table below shows some compiler options that may help with optimization.

The following tables contain examples of serial, MPI, and OpenMP compile commands for C, C++, and Fortran.

5.2.2. GNU Compiler

The default GNU compilers are good for compiling utility programs, but are probably not appropriate for computationally intensive applications. It is available without loading a separate module. The primary selling point of using GNU compilers is the compatibility between different architectures. They can be executed using the commands in the table above. For GNU compilers, the "-O" flag is the basic optimization setting.

More GNU compiler information can be found in the GNU gcc 4.8.5 manual.

5.3. Relevant Modules

If you compile your own codes, you will need to select which compiler and MPI version you want to use. For example:

module load compiler/pgi/x.x mpi/openmpi/x.x.x

These same module commands should be executed in your batch script before executing your program.

SCOUT provides individual modules for each compiler and MPI version. To see the list of currently available modules use the "module avail" command. You can use any of the available MPI versions with each compiler by pairing them together when you load the modules.

The table below shows the naming convention used for various modules.

For more information on using modules, see the Modules User Guide.

5.4. Libraries

5.4.1. BLAS

The Basic Linear Algebra Subprogram (BLAS) library is a set of high quality routines for performing basic vector and matrix operations. There are three levels of BLAS operations:

More information on the BLAS library can be found at http://www.netlib.org/blas.

5.4.2. Additional Math Libraries

There is also an extensive set of Math libraries available in the /opt/ibmmath/essl/6.2 directory on SCOUT.

5.5. Debuggers

5.5.1. gdb

The GNU Project Debugger (gdb) works similarly to dbx and can be invoked either with a program for execution or a running process id. To use gdb to debug a program during execution, use:

gdb a.out corefile

To debug a process that is currently executing on this node, use:

gdb a.out pid

For more information, the GDB manual can be found at http://sourceware.org/gdb/current/onlinedocs/gdb.

5.6. Code Profiling and Optimization

Profiling is the process of analyzing the execution flow and characteristics of your program to identify sections of code that are likely candidates for optimization, which increases the performance of a program by modifying certain aspects for increased efficiency.

We provide the profiling tool, gprof, to assist you in the profiling process. A basic overview of optimization methods with information about how they may improve the performance of your code can be found in Performance Optimization Methods (below).

5.6.1. gprof

The GNU Project Profiler (gprof) is a profiler that shows how your program is spending its time and which functions calls are made. To profile code using gprof, use the "-pg" option during compilation. For more information, the gprof manual can be found at http://sourceware.org/binutils/docs/gprof/index.html.

5.6.2. Program Development Reminders

If an application is not programmed for distributed memory, then only the cores on a single node can be used. This is limited to 16 cores on SCOUT.

Check the utilization of the nodes your application is running on to see if it is taking advantage of all the resources available to it. This can be done by finding the nodes assigned to your job by executing "bstatus <JOB_ID>", logging into one of the nodes using the ssh command, and then executing the top command to see how many copies of your executable are being executed on the node.

Keep the system architecture in mind during code development. For instance, if your program requires more memory than is available on a single node, then you will need to parallelize your code so that it can function across multiple nodes.

5.6.3. Performance Optimization Methods

Optimization generally increases compilation time and executable size, and may make debugging difficult. However, it usually produces code that runs significantly faster. The optimizations that you can use will vary depending on your code and the system on which you are running.

Note: Before considering optimization, you should always ensure that your code runs correctly and produces valid output.

In general, there are five main categories of optimization:

Global Optimization

A technique that looks at the program as a whole and may perform any of the following actions:

Loop Optimization

A technique that focuses on loops (for, while, etc.) in your code and looks for ways to reduce loop iterations or parallelize the loop operations. The following types of actions may be performed:

Interprocedural Analysis and Optimization (IPA)

A technique that allows the use of information across function call boundaries to perform optimizations that would otherwise be unavailable.

Function Inlining

A technique that seeks to reduce function call and return overhead.

Profile-Guided Optimizations

Profile-Guided optimizations are available which allow the compiler to make data driven decisions during compilation on branch predictions, increased parallelism, block ordering, register allocation, function ordering, and more. The build for this option takes about three steps though and uses a representative data set to come up with the optimizations.

For example:

6. Batch Scheduling

6.1. Scheduler

The Load Sharing Facility (LSF) is currently running on SCOUT. It schedules jobs and manages resources and job queues, and can be accessed through the interactive batch environment or by submitting a batch request. LSF is able to manage both single-processor and multiprocessor jobs. The LSF module is automatically loaded by the Master module on SCOUT at login.

6.2. Queue Information

The following table describes the LSF queues available on SCOUT:

Queue Descriptions and Limits on SCOUT

Priority	Queue Name	Max Wall Clock Time	Max Cores Per Job	Description
Highest	transfer	48 Hours	N/A	Data transfer for user jobs. See the ARL DSRC Archive Guide, section 5.2.
	urgent	96 Hours	N/A	Jobs belonging to DoD HPCMP Urgent Projects
	debug	1 Hour	N/A	Time/resource-limited for user testing and debug purposes
	high	168 Hours	N/A	Jobs belonging to DoD HPCMP High Priority Projects
	frontier	168 Hours	N/A	Jobs belonging to DoD HPCMP Frontier Projects
	HIE	24 Hours	N/A	Rapid response for interactive work. For more information see the HPC Interactive Environment (HIE) User Guide.
	interactive	12 Hours	N/A	Interactive jobs
	standard	168 Hours	N/A	Standard jobs
Lowest	background	24 Hours	N/A	User jobs that are not charged against the project allocation

6.3. Interactive Logins

When you log in to SCOUT, you will be running in an interactive shell on a login node. The login nodes provide login access for SCOUT and support such activities as compiling, editing, and general interactive use by all users. Please note the Login Node Abuse policy. The preferred method to run resource intensive executions is to use an interactive batch session.

6.4. Interactive Batch Sessions

An interactive session on a compute node is possible using a proper LSF command line syntax from a login node. Once LSF has scheduled your request on the compute pool, you will be directly logged into a compute node, and this session can last as long as your requested wall time.

To submit an interactive batch job, use the following submission format:

Your batch shell request will be placed in the interactive queue and scheduled for execution. This may take a few minutes or a long time depending on the system load. Once your shell starts, you will be logged into the first compute node of the compute nodes that were assigned to your interactive batch job. At this point, you can run or debug applications interactively, execute job scripts, or start executions on the compute nodes you were assigned. The "-X" option enables X-Windows access, so it may be omitted if that functionality is not required for the interactive job.

6.5. Batch Request Submission

LSF batch jobs are submitted via the bsub command. The format of this command is:

bsub < [ options ] batch_script_file

bsub options may be specified on the command line or embedded in the batch script file by lines beginning with "#BSUB".

6.6. Launch Commands

There are different commands for launching MPI executables from within a batch job depending on which MPI implementation your script uses.

To launch an IBM Spectrum executable, mpiexec command as follows:

mpiexec -n #_of_MPI_tasks ./mpijob.exe

To launch an OpenMPI executable, use the openmpi_wrapper command as follows:

openmpi_wrapper -n #_of_MPI_tasks ./mpijob.exe

For OpenMP executables, no launch command is needed.

6.7. Sample Script

The following script is a basic example. More thorough examples are available in the Sample Code Repository ($SAMPLES_HOME) on SCOUT.

Note: By default, GPU support is turned off. To turn it on, use the mpirun -gpu flag: mpirun -gpu
Using the -gpu option causes additional runtime checking of every buffer that is passed to MPI. The -gpu flag is only required for applications that pass pointers to GPU buffers to MPI API calls. Applications that use GPUs, but do not pass pointers that refer to memory that is managed by the GPU, are not required to pass the -gpu option.

#!/bin/csh
#  Specify job name.
#BSUB -J myjob

#  Specify queue name.
#BSUB -q standard


#BSUB -n 40

#  Specify how MPI processes should be distributed across nodes.
#BSUB -R "span[ptile=20]"

#  Specify maximum wall clock time.
#BSUB -W 24:00:00

#  Specify Project ID to use. ID may have the form ARLAP96090RAY.
#BSUB -P XXXXXXXXXXXXX

#  Specify that environment variables should be passed to master MPI process.
#BSUB -V

set JOBID=`echo $LSF_JOBID | cut -f1 d.`

#  Create a temporary working directory within $WORKDIR for this job run.
set TMPD=${WORKDIR}/${JOBID}
mkdir -p $TMPD

# Change directory to submit directory
# and copy executable and input file to scratch space
cd $LSF_O_WORKDIR
cp mpicode.x $TMPD
cp input.dat $TMPD

cd $TMPD

# The following line provides an example of running a code built
#  with the gcc compiler and IBM Spectrum MPI.
module load compiler/gcc/9.1.1  mpi/spectrum/10.03
mpiexec -n 48 ./mpicode.x > out.dat

cp out.dat $LSF_O_WORKDIR

exit
############ MPI+CUDA Hybrid Example ############

#BSUB -m inf[001-128]
#BSUB -n 4
#BSUB -gpu  "num=4:mode=shared:j_exclusive=yes"
#BSUB -P ARLAP96090RAY
#BSUB -J mpi_cuda_job
#BSUB -o ./%J_hw.out
#BSUB -e ./%J_hw.err
#BSUB -x

module unload compiler
module unload mpi
module unload cuda

module load compiler/gcc/8.3.1
module load mpi/spectrum/10.03
module load cuda/10.2

nvidia-smi
mkdir $WORKDIR/$JOBID && cd $WORKDIR/$JOBID
mpirun -gpu -n 4 ./a.out >& output.dat

6.8. LSF Commands

The following commands provide the basic functionality for using the LSF batch system:

bsub: Used to submit jobs for batch processing.
bsub [ options ] my_job_script

bjobs: Used to check the status of submitted jobs.
bjobs $LSF_JOBID ## check one job bjobs -u my_user_name ## check all of user's jobs bjobs -u all -a ## check all jobs of all users

bhosts: Used to Display hosts and their static and dynamic resources.
bhosts -a ## returns host name, host status, job state statistics, and ## job slot limits for all hosts.

bqueues: Displays information about queues.
bqueues QUEUE_NAME PRIO STATUS MAX JL/U JL/P JL/H NJOBS PEND RUN SUSP transfer 110 Open:Active - - - - 0 0 0 0 urgent 100 Open:Active - - - - 0 0 0 0 debug 99 Open:Active - - - - 0 0 0 0 high 90 Open:Active - - - - 0 0 0 0 frontier 80 Open:Active - - - - 0 0 0 0 HIE 60 Open:Active - - - - 0 0 0 0 interactive 60 Open:Active - - - - 0 0 0 0 staff 50 Open:Active - - - - 0 0 0 0 standard 50 Open:Active - - - - 8709 4080 4629 0 background 1 Open:Active 1200 - - - 0 0 0 0

bkill: Used to kill queued or running jobs.
bkill $LSF_JOBID

7. Software Resources

7.1. Application Software

All Commercial Off The Shelf (COTS) software packages can be found in the $CSI_HOME (/p/app) directory. A complete listing of software on SCOUT with installed versions can be found on our software page. The general rule for all COTS software packages is that the two latest versions will be maintained on our systems. For convenience, modules are also available for most COTS software packages.

7.2. Useful Utilities

The following utilities are available on SCOUT. For command-line syntax and examples of usage, please see each utility's online man page.

7.3. Sample Code Repository

The Sample Code Repository is a directory that contains examples for COTS batch scripts, building and using serial and parallel programs, data management, and accessing and using serial and parallel math libraries. The $SAMPLES_HOME environment variable contains the path to this area, and is automatically defined in your login environment. Below is a listing of the examples provided in the Sample Code Repository on SCOUT.

8. Links to Vendor Documentation

8.1. IBM Links

IBM Home: http://www.ibm.com
IBM Power9: https://www.ibm.com/it-infrastructure/power
IBM IC922 Inference Nodes: https://www.ibm.com/products/power-system-ic922
IBM AC922 Training Nodes: https://www.ibm.com/products/power-systems-ac922

8.2. RedHat Links

RedHat Home: http://www.redhat.com

8.3. GNU Links

GNU Home: http://www.gnu.org
GNU Compiler: http://gcc.gnu.org

8.4. PGI Links

PGI Home: http://www.pgroup.com
PGI Compiler Documentation: http://www.pgroup.com/resources/docs.php