▶ Table of Contents
Deep Bayou, the latest addtion to LSU HPC's pool of resources, is a 13-node GPU cluster funded by the NSF CC* award #2020446. Each Deep Bayou compute node is equipped with at least two NVIDIA V100S GPUs and a 1.5 TB NVMe solid state drive. Two of the compute nodes are equipped with four NVIDIA V100S GPUs connected by NVLink, which boosts the data exchange performance between GPUs. These features make Deep Bayou a powerful platform for deep learning and AI workloads.
The compute time on Deep Bayou is allocated separately from Super Mike 2 and SuperMIC. Given its limited number of nodes and hardware features, when requesting an allocation on Deep Bayou, PIs should describe how their intended workloads will use the GPU devices.
Deep Bayou went into general production in March 2021 and is available to all LSU HPC users.
- Common Features
- RedHat Enterprise Linux 7 Operating System
- 100 Gb/sec (HDR100) InfiniBand
- 11 GPU Compute Nodes, each with:
- Two 24-core Intel Cascade Lake (Intel® Xeon® Gold 6248R Processor) CPUs.
- 192 GB memory
- Two NVIDIA V100S GPUs (each with 32 GB memory)
- 1.5TB NVMe SSD drive
- 2 GPU NVLink Compute Nodes, each with:
- Two 24-core Intel Cascade Lake (Intel® Xeon® Gold 6240R Processor) CPUs.
- 384 GB memory
- Four NVIDIA V100S GPUs (each with 32 GB memory, SXM2 with NVLINK)
- 1.5TB NVMe SSD drive
- 1 Login Nodes, with:
- Two 24-core Intel Cascade Lake (Intel® Xeon® Gold 6226R Processor) CPUs.
- 192 GB Ram
- Cluster Storage
- 840 TB Lustre file system (shared with the SuperMIC cluster)
1. System Access to Deep Bayou
To access Deep Bayou, users must connect using an Secure Shell (SSH) client.
Linux and Mac Users - SSH client is already installed and can be accessed from the command prompt using the ssh command. One would issue a command similar to the following:
$ ssh -X email@example.com
The user would then be prompted for his password. The -X flags allow for X11 Forwarding to be set up automatically.
Windows Users - You will need to download and install a SSH client such as the PuTTY utility. If users need access to login with X11 Forwarding, a X-Server needs to be installed and running on your local Windows machine. Xming X Server is recommended, advanced users may also install Cygwin which also provides a command line ssh client similar to that available for Linux and Mac Users.
If you have forgotten your password, or you wish to reset it, see here(click "Forgot your password?").
To report a problem please run the ssh or gsissh command with the "-vvv" option and include the verbose information in the ticket.
2. File Transfer
Using scp is the easiest method to use when transferring single files.
Local File to Remote Host
% scp localfile user@remotehost:/destination/dir/or/filename
Remote Host to Local File
% scp user@remotehost:/remote/filename localfile
One may find this mode very similar to the interactive interface offered. A login session may look similar to the following:
% sftp user@remotehost (enter in password) ... sftp>
The commands are similar to those offered by the outmoded ftp client programs: get, put, cd, pwd, lcd, etc. For more information on the available set of commands, one should consult sftp the man page.
% man sftp
One may use sftp interactively in two cases.
Case 1: Pull a remote file to the local host.
% sftp user@remotehost:/remote/filename localfilename
Case 2: Creating a special sftp batch file containing the set of commands one wishes to execute with out any interaction.
% sftp -b batchfile user@remotehost
Additional information on constructing a batch file is available in the sftp man page.
2.3. rsync Over SSH (preferred)
rsync is an extremely powerful program; it can synchronize entire directory trees, only sending data about files that have changed. That said, it is rather picky about the way it is used. The rsync man page has a great deal of useful information, but the basics are explained below.
Single File Synchronization
To synchronize a single file via rsync, use the following:
To send a file:
% rsync --rsh=ssh --archive --stats --progress localfile \ username@remotehost:/destination/dir/or/filename
To receive a file:
% rsync --rsh=ssh --archive --stats --progress \ username@remotehost:/remote/filename localfilename
Note that --rsh=ssh is not necessary with newer versions of rsync, but older installs will default to using rsh (which is not generally enabled on modern OSes).
To synchronize an entire directory, use the following:
To send a directory:
% rsync --rsh=ssh --archive --stats --progress localdir/ \ username@remotehost:/destination/dir/
% rsync --rsh=ssh --archive --stats --progress localdir \ username@remotehost:/destination
To receive a directory:
% rsync --rsh=ssh --archive --stats --progress \ username@remotehost:/remote/directory/ /some/localdirectory/
% rsync --rsh=ssh --archive --stats --progress \ username@remotehost:/remote/directory /some/
Note the difference with the slashes. The second command will place the files in the directory /destination/localdir; the fourth will place them in the directory /some/directory. rsync is very particular about the placement of slashes. Before running any significant rsync command, add --dry-run to the parameters. This will let rsync show you what it plans on doing without actually transferring the files.
Synchronization with Deletion
This is very dangerous; a single mistyped character may blow away all of your data. Do not synchronize with deletion if you aren't absolutely certain you know what you're doing.
To have directory synchronization delete files on the destination system that don't exist on the source system:
% rsync --rsh=ssh --archive --stats --dry-run --progress \ --delete localdir/ username@remotehost:/destination/dir/
Note that the above command will not actually delete (or transfer) anything; the --dry-run must be removed from the list of parameters to actually have it work.
Using BBCP to transfer large data files without encryption.
% bbcp [opt] user@source:/path/to/data user@destination:/path/to/store/data
Possible options include:
- -P 2
- Give a progress report every 2 seconds
- - w 2M
- TCP window size of 2MBytes
- -s 16
- Set the number of streams to 16 (default is 4)
Other options may be necessary if bbcp is not installed in a regular location on either end of the transfer. This can lead to rather complex command lines:
$ bbcp -z -T \ "ssh -x -a -oFallBackToRsh=no %I -l %U %H /home/user/Custom/bin/bbcp" \ foobar-5.4.14.tbz "firstname.lastname@example.org:foo.tbz"
2.5 Client Software
scp and sftp
The command-line scp and sftp tools come with any modern distribution of OpenSSH; this is generally installed by default on modern Linux, UNIX, and Mac OS X installs.
Windows clients include:
(puTTY-related command line utilities), and
- scp, sftp, & rsync as provided by Cygwin.
*** VERY IMPORTANT ***: if you use Filezilla, please use the Site Manager feature (under "File") to manage the profile of the cluster you use. In the "Transfer Settings" tab, make sure that the "Limit number of simultaneous comments" box is checked and the "Maximum number of connections" is set to 1. Failing to do so may result in Filezilla creating excessive ssh connections, which could lead the suspension of your user account.
3. Computing Environment.
Deep Bayou's default shell is
bash. Other shells are available:
sh, csh, tcsh, and
ksh. Users may change their default shell by logging into their HPC Profile page at https://accounts.hpc.lsu.edu.
The following is a guide to managing your software environment with modules.
The Environment Modules package provides for dynamic modification of your shell environment. Module commands set, change, or delete environment variables, typically in support of a particular application. They also let the user choose between different versions of the same software or different combinations of related codes. Complete documentation is available in the module(1) and modulefile(4) manpages.
3.2.1. Default Environment
The default environment is defined in the .modules file under each user's home directory. Edit this file if you would like to change the default environment.
3.2.2. Useful Module Commands
|module list||List the modules that are currently loaded|
|module avail||List the modules that are available|
|module display <module name>||Show the environment variables used by <module name> and how they are affected|
|module unload <module name>||Remove <module name> from the environment|
|module load <module name>||Load <module name> into the environment|
|module swap <module one> <module two>||Replace <module one> with <module two> in the environment|
3.2.3. Loading and unloading modules
You must remove some modules before loading others. Some modules depend on others, so they may be loaded or unloaded as a consequence of another module command. For example, if intel and mvapich are both loaded, running the command module unload intel will automatically unload mvapich. Subsequently issuing the module load intel command does not automatically reload mvapich.
4. File Systems
|File system name||Access point||Type of file system||Quota||Time until purged||Best for|
|Home||/home/<your user name>||NFS||10 GB||Never||Code in development, compiled executables|
|Work (scratch)||/work/<your user name>||Lustre||Unlimited||60 days||Job input/output|
|Project||/project/<your user name>||Lustre||Varies||12 months, can be longer upon renewal||Storage space for a specific project (NOT meant for archival purposes)|
User-owned storage on the Deep Bayou system is available in two directories: home (/home/<your user name>) and work (/work/<your user name>). These directories are on separate file systems, and accessible from any node in the system. The work directory is created automatically within an hour of first login. If your work directory does not exist when you login, please wait at least an hour before contacting the HPC helpdesk.
4.1. Home Directory
The /home file system quota on Deep Bayou is 10 GB. Files can be stored on /home permanently, which makes it an ideal place for your source code and executables. The /home file system is meant for interactive use such as editing and active code development. Do not use /home for batch job I/O.
4.2. Work (Scratch) Directory
The /work (/scratch) directories are created automatically once an hour after first login. The /work volume is meant for the input and output of executing batch jobs and not for long term storage. We expect files to be moved off to other locations or deleted in a timely manner, usually within 30-120 days. For performance reasons, our policy on all volumes is to limit the number of files per directory to around 10,000 and total number files to about 500,000.
The /work file system quota on Deep Bayou is unlimited. If it becomes over utilized we will enforce a purge policy, which means that we will begin deleting files starting with the oldest last accessed date, and largest files, and continue until the volume has been reduced below 80%. An email message will be sent out weekly to users who may have files subject to purge informing them of their /work utilization. If diskspace should become critically low, more drastic measures may be required to keep the system stable.
Please do not attempt to circumvent the removal process by manually changing file dates. The /work volume capacity is not unlimited, and attempts to circumvent the purge process may adversely affect others and lead to access restrictions to the /work volume or even the cluster.
5. Application Development
The Intel, GNU and Portland Group (PGI) C, C++ and Fortran compilers are installed on Deep Bayou and they can be used to create OpenMP, MPI, hybrid and serial programs. The commands you should use to create each of these types of programs are shown in the table below.
Intel compilers are loaded by default, codes can be compiled according to the following chart:
|Serial Codes||MPI Codes||OpenMP Codes||Hybrid Codes|
|Fortran||ifort||mpiifort||ifort -openmp||mpiifort -openmp|
|C||icc||mpiicc||icc -openmp||mpiicc -openmp|
|C++||icpc||mpiicpc||icpc -openmp||mpiicpc -openmp|
|Serial Codes||MPI Codes||OpenMP Codes||Hybrid Codes|
|Fortran||gfortran||mpif90||gfortran -fopenmp||mpif90 -fopenmp|
|C||gcc||mpicc||gcc -fopenmp||mpicc -fopenmp|
|C++||g++||mpiCC||g++ -fopenmp||mpiCC -fopenmp|
|Serial Codes||MPI Codes||OpenMP Codes||Hybrid Codes|
|Fortran||pgf90||mpif90||pgf90 -mp||mpif90 -mp|
|C||pgcc||mpicc||pgcc -mp||mpicc -mp|
|C++||pgCC||mpiCC||pgCC -mp||mpiCC -omp|
Default MPI: mvapich 1.1 compiled with Intel compiler version 11.1
To compile a serial program, the syntax is: <your choice of compiler> <compiler flags> <source file name> . For example, the command below compiles the source file mysource.f90 and generate the executble myexec.
$ ifort -o myexec mysource.f90
To compile a MPI program, the syntax is the same, except that one needs to replace the serial compiler with an MPI one listed in the table above:
$ mpif90 -o myexec_par my_parallel_source.f90
5.1. GPU Programming
NVIDIA's CUDA compiler and libraries are accessed by loading the CUDA module:
module load cuda
Use the nvcc compiler on the head node to compile code, and run executables on nodes with GPUs - there are no GPUs on the head nodes. Deep Bayou K20's GPUs are compute capability 2.0 devices. When compiling your code, make sure to specify this level of capability with:
nvcc -arch=compute_20 -code=sm_20 ...
GPU nodes are accessible through the gpu queue for production work.
OpenACC is the name of an application program interface (API) that uses a collection of compiler directives to accelerate applications that run on multicore and GPU systems. The OpenACC compiler directives specify regions of code that can be offloaded from a CPU to an attached accelerator. A quick reference guide is available here.
Currently, only the Portland Group compilers installed on Deep Bayou can be used to compile C and Fortran code annotated with OpenACC directives.
To load the PGI compilers:
module load pgi
To compile a C code annotated with OpenACC directives:
pgcc -acc -ta=nvidia -Minfo=accel code.c -o code.exe
6. Running Applications
Deep Bayou uses SLURM to manage user jobs. Whether you run in batch mode or interactively, you will access the compute nodes using the SLURM command as described below. Remember that computationally intensive jobs should be run only on the compute nodes and not the login nodes. More details on submitting jobs and SLURM commands can be found here.
6.1. Available Partitions (Queues) on Deep Bayou
Below are the possible job queues to choose from:
- single - Used for jobs that will only execute on a single node, i.e. nodes=1:ppn<=48.
- checkpt - Used for jobs that will use at least one node. Jobs in the checkpt queue can be preempted if needed.
|Queue Name||Max Walltime||Max Nodes (per job)||Allowed ppn|
|single||72||1||1 to 48|
The available queues and actual limit settings can be verified by running the command:
6.2. Job Submission
SLURM (Simple Linux Utility for Resource Management) is an open source, highly scalable cluster management and job scheduling system. It is used for managing job scheduling on new HPC and LONI clusters. It was originally created at the Livermore Computing Center, and has grown into a full-fledge open-source software backed up by a large community, commercially supported by the original developers, and installed in many of the Top-500 supercomputers.
Information about the following topics can be found here:
- Submitting batch script (single node)
- Submitting batch script (multiple nodes)
- Submitting interactive jobs
- Commonly used SLURM Commands
Submitting batch script (single node)
To create a batch SLURM script, use your favorite editor (e.g. vi or emacs) to create a text file with both SLURM instructions and commands how to run your job. All SLURM directives (special instructions) are prefaced by the #SBATCH. Below is an example of a SLURM batch job script:
#!/bin/bash #SBATCH -N 1 # request one node #SBATCH -t 2:00:00 # request two hours #SBATCH -p single # in single partition (queue) #SBATCH -A your_allocation_name #SBATCH -o slurm-%j.out-%N # optional, name of the stdout, using the job number (%j) and the hostname of the node (%N) #SBATCH -e slurm-%j.err-%N # optional, name of the stderr, using job and hostname values # below are job commands date # Set some handy environment variables. export HOME_DIR=/home/$USER/myjob export WORK_DIR=/work/$USER/myjob # Make sure the WORK_DIR exists: mkdir -p $WORK_DIR # Copy files, jump to WORK_DIR, and execute a program called "mydemo" cp $HOME_DIR/mydemo $WORK_DIR cd $WORK_DIR ./mydemo # Mark the time it finishes. date # exit the job exit 0
To submit the above job to the scheduler, save the above script as a text file, e.g., singlenode.sh, then use the below command to submit:
$ sbatch singlenode.sh
List of useful SLURM directives and their meaning:
- #SBATCH -A allocationname: short for --account, charge jobs to your allocation named allocationname.
- #SBATCH -J: short for --jobname, name of the job.
- #SBATCH -n : short for --ntasks, number of tasks (CPU cores) to run job on. The memory limit for jobs is 4 GB of MEM per CPU core requested.
- #SBATCH -N : short for --nodes, number of nodes on which to run.
- #SBATCH -c : short for --ncpus-per-task, number of threads per process.
- #SBATCH -p partition: short for --partition, submit job to the partition queue.
- Allowed values for partition: single, checkpt, workq, gpu, bigmem.
- Depending on cluster, addition partitions can be found via the sinfo command.
- #SBATCH -t hh:mm:ss: short for --time, request resources to run job for hh hours, mm minutes and ss seconds.
- #SBATCH -o filename.out: short for --output, write standard output to file filename.out.
- #SBATCH -e filename.err: short for --error, write standard error to file filename.err.
- Note that by default, SLURM will merge stardard error and standard output to one file if no "-o" or "-e" flag is set.
- #SBATCH --mail-user email@example.com: Address to send email to when the --mail-type directive below is trigerred.
- #SBATCH --mail-type type: Send an email after job status typeoccurs. Common values for type include BEGIN, END, FAIL or ALL. The arguments can be combined, for e.g. BEGIN, END will send email when job begins and ends
List of common useful SLURM environmental variables and their meaning:
- SLURM_JOBID: Job ID number given to this job
- SLURM_JOB_NODELIST: List of nodes allocated to the job
- SLURM_SUBMIT_DIR: Directory where the sbatch command was executed
- SLURM_NNODES: Total number of nodes in the job's resource allocation.
- SLURM_NTASKS: Total number of CPU cores requested in a job.
Submitting batch script (multiple nodes)
Creating multiple-node job script is very similar to the single node job script, with the difference of using multiple nodes. Below is an example of a multiple-node batch job script:
#!/bin/bash #SBATCH -N 2 # request two nodes #SBATCH -n 16 # specify 16 MPI processes (8 per node) #SBATCH -c 6 # specify 6 threads per process #SBATCH -t 2:00:00 #SBATCH -p checkpt #SBATCH -A your_allocation_name #SBATCH -o slurm-%j.out-%N # optional, name of the stdout, using the job number (%j) and the first node (%N) #SBATCH -e slurm-%j.err-%N # optional, name of the stderr, using job and first node values # below are job commands date # Set some handy environment variables. export HOME_DIR=/home/$USER/myjob export WORK_DIR=/work/$USER/myjob # load appropriate modules, in this case Intel compilers, MPICH module load mpich/3.1.4/INTEL-15.0.3 # Make sure the WORK_DIR exists: mkdir -p $WORK_DIR # Copy files, jump to WORK_DIR, and execute a program called "my_mpi_demo" cp $HOME_DIR/mydemo $WORK_DIR cd $WORK_DIR srun -N2 -n8 -c6 /my_mpi_demo # Launch the MPI application with two nodes, 8 MPI processes each node, and 6 threads per MPI process. # Mark the time it finishes. date # exit the job exit 0
Note: in the examples above, the srun command is used to launch the MPI application. This will be the default behavior.
The syntax for the srun command is:
srun <flags> <name of the MPI executable>
Some useful flags are:
- -N: number of nodes
- -n: total number of MPI processes
- -c: number of threads per MPI process
- -u: turn on unbuffered output (the output from MPI processes will be flushed to stdout as soon as it's generate); without this flag, Slurm will buffer and rearrange the output according to the MPI ranks.
Submitting interactive jobs
To start an interactive job, use the srun command similar to the example below:
srun -t 1:00:00 -n8 -N1 -A your_allocation_name -p single --pty /bin/bash
Similar to the batch job script, the -n denotes 8 tasks (cores), the -N denotes 1 compute node. Note the important --pty flag denoting an interactive terminal, which is required and has to be at the end of the commnad. This flag can be changed to desired shell, e.g., /bin/csh, /bin/tcsh or /bin/ksh, etc. The complete form of the above command can be:
srun --time=1:00:00 --ntasks=8 --nodes=1 --account=your_allocation_name --partition=single --pty /bin/bash
With Slurm, the simplest command to start an interactive job can be:
srun --pty /bin/bash
This command will start an interactive job using default values: --time=1:00:00 --ntasks=1 --nodes=1 --account=your_default_allocation --partition=single.
- If an interactive job session is submitted to a partition other than single, the -n or --ntasks flag will be ignored and one or more entire nodes will be allocated to the job.
- It is suggested to specify your allocation name (-A your_allocation_name) to the srun command so a proper allocation can be used by the scueduler. Note that the "-A allocation_name" must be appear before the last command to be run by the scheduler, in this case, the "/bin/bash", therefore below command will work:
srun -t 1:00:00 -n8 -N1 -p single --pty -A your_allocation_name /bin/bashHowever below command might fail if you did not specify a *valid* default allocation in allocation balance page from LONI or HPC user portal:
srun -t 1:00:00 -n8 -N1 -p single --pty /bin/bash -A your_allocation_nameBecause the entire string after --pty, i.e., "/bin/bash -A your_allocation_name" is considered a command to be run by the srun command, and then the allocation information is not passed to the Slurm scheduler.
Commonly used SLURM Commands
squeue is used to show the partition (queue) status. Useful options:
- -l ("l" for "long"): gives more verbose information
- -u someusername: limit output to jobs by username --state=pending: limit output to pending (i.e. queued) jobs --state=running: limit output to running jobs
Below is an example to query all jobs submitted by current user (fchen14)
[fchen14@db2 ~]$ squeue -u $USER JOBID PARTITION NAME USER ST TIME NODES NODELIST(REASON) 340 checkpt bash fchen14 R 1:06:59 1 db002 339 checkpt bash fchen14 R 1:07:09 1 db001
sinfo is used to view information about SLURM nodes and partitions. Typical usage:
[fchen14@db001 test]$ sinfo PARTITION AVAIL TIMELIMIT NODES STATE NODELIST debug up infinite 3 idle db[026-027,032] checkpt* up 3-00:00:00 2 alloc db[001-002] checkpt* up 3-00:00:00 23 idle db[003-025] single up 7-00:00:00 2 alloc db[001-002] single up 7-00:00:00 23 idle db[003-025] bigmem up 7-00:00:00 2 idle db[033-034]
scancel is used to signal or cancel jobs. Typical usage with squeue:
[fchen14@db1 ~]$ squeue -u fchen14 JOBID PARTITION NAME USER ST TIME NODES NODELIST(REASON) 341 checkpt bash fchen14 R 0:13 1 db001 340 checkpt bash fchen14 R 1:50:57 1 db002 # cancel (delete) job with JOBID 340 [fchen14@db1 ~]$ scancel 340 # job status might display a temporary "CG" ("CompletinG") status immediately after scancel [fchen14@db1 ~]$ squeue -u fchen14 JOBID PARTITION NAME USER ST TIME NODES NODELIST(REASON) 340 checkpt bash fchen14 CG 1:51:08 1 db002 341 checkpt bash fchen14 R 0:41 1 db001 [fchen14@db1 ~]$ squeue -u fchen14 JOBID PARTITION NAME USER ST TIME NODES NODELIST(REASON) 341 checkpt bash fchen14 R 1:08 1 db001
scontrol is used to view or modify SLURM configuration and state. Typical usage for the user is to check job status:
[fchen14@db1 ~]$ squeue -u fchen14 # show all jobs JOBID PARTITION NAME USER ST TIME NODES NODELIST(REASON) 341 checkpt bash fchen14 R 1:29:20 1 db001 [fchen14@db1 ~]$ scontrol show job 341 JobId=341 JobName=bash UserId=fchen14(32584) GroupId=Admins(10000) MCS_label=N/A Priority=1 Nice=0 Account=hpc_hpcadmin6 QOS=normal JobState=RUNNING Reason=None Dependency=(null) Requeue=1 Restarts=0 BatchFlag=0 Reboot=0 ExitCode=0:0 RunTime=01:29:31 TimeLimit=12:00:00 TimeMin=N/A SubmitTime=2020-05-07T10:47:52 EligibleTime=2020-05-07T10:47:52 AccrueTime=Unknown StartTime=2020-05-07T10:47:52 EndTime=2020-05-07T22:47:57 Deadline=N/A SuspendTime=None SecsPreSuspend=0 LastSchedEval=2020-05-07T10:47:52 Partition=checkpt AllocNode:Sid=db1:28374 ReqNodeList=(null) ExcNodeList=(null) NodeList=db001 BatchHost=db001 NumNodes=1 NumCPUs=8 NumTasks=1 CPUs/Task=1 ReqB:S:C:T=0:0:*:* TRES=cpu=8,mem=22332M,node=1,billing=8 Socks/Node=* NtasksPerN:B:S:C=0:0:*:* CoreSpec=* MinCPUsNode=1 MinMemoryNode=22332M MinTmpDiskNode=0 Features=(null) DelayBoot=00:00:00 OverSubscribe=NO Contiguous=0 Licenses=(null) Network=(null) Command=/bin/bash WorkDir=/home/fchen14/test Power=
More detailed information on the SLURM commands to schedule and monitor jobs can be found at Slurm on-line documentation.