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* To use hyperthreading, just change <tt>--cpus-per-task=40</tt> to <tt>--cpus-per-task=80</tt>. | * To use hyperthreading, just change <tt>--cpus-per-task=40</tt> to <tt>--cpus-per-task=80</tt>. | ||
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Further instructions for monitoring your jobs can be found on the [[Slurm#Monitoring_jobs | Slurm page]]. The [https://my.scinet.utoronto.ca my.SciNet] site is also a very useful tool for monitoring your current and past usage. | |||
= Visualization = <!--T:203--> | = Visualization = <!--T:203--> |
Revision as of 18:12, 27 September 2018
Specifications[edit]
The Niagara cluster is a large cluster of 1500 Lenovo SD350 servers each with 40 Intel "Skylake" cores at 2.4 GHz. The peak performance of the cluster is 3.02 PFlops delivered / 4.6 PFlops theoretical. It was ranked 53rd fastest supercomputer on the TOP500 list of June 2018.
Each node of the cluster has 188 GiB / 202 GB RAM per node (at least 4 GiB/core for user jobs). Being designed for large parallel workloads, it has a fast interconnect consisting of EDR InfiniBand in a Dragonfly+ topology with Adaptive Routing. The compute nodes are accessed through a queueing system that allows jobs with a minimum of 15 minutes and a maximum of 12 or 24 hours and favours large jobs.
See the "Intro to Niagara" recording
More detailed hardware characteristics of the Niagara supercomputer can be found on this page.
Getting started on Niagara[edit]
Those of you new to SciNet and belonging to a group whose primary PI does not have an allocation, as granted in the annual Compute Canada RAC, must first follow the old route of requesting a SciNet Consortium Account on the CCDB site to gain access to Niagara.
Please read this document carefully. The FAQ is also a useful resource. If at any time you require assistance, or if something is unclear, please do not hesitate to contact us
Logging in[edit]
Niagara runs CentOS 7, which is a type of Linux. You will need to be familiar with Linux systems to function on Niagara. If you are not it will be worth your time to review our Introduction to Linux Shell class.
As with all SciNet and CC (Compute Canada) compute systems, access to Niagara is done via ssh (secure shell) only. Open a terminal window (e.g. PuTTY on Windows or MobaXTerm), then ssh into the Niagara login nodes with your CC credentials:
$ ssh -Y MYCCUSERNAME@niagara.scinet.utoronto.ca
or
$ ssh -Y MYCCUSERNAME@niagara.computecanada.ca
The Niagara login nodes are where you develop, edit, compile, prepare and submit jobs.
These login nodes are not part of the Niagara compute cluster, but have the same architecture, operating system, and software stack.
The optional -Y
is needed to open windows from the Niagara command-line onto your local X server.
To run on Niagara's compute nodes, you must submit a batch job.
If you cannot log in, be sure first to check the System Status on this site's front page.
Your various directories[edit]
By virtue of your access to Niagara you are granted storage space on the system. There are several directories available to you, each indicated by an associated environment variable
home and scratch[edit]
You have a home and scratch directory on the system, whose locations are of the form
$HOME=/home/g/groupname/myccusername
$SCRATCH=/scratch/g/groupname/myccusername
where groupname is the name of your PI's group, and myccusername is your CC username. For example:
nia-login07:~$ pwd
/home/s/scinet/rzon
nia-login07:~$ cd $SCRATCH
nia-login07:rzon$ pwd
/scratch/s/scinet/rzon
NOTE: home is read-only on compute nodes.
project and archive[edit]
Users from groups with RAC storage allocation will also have a project and/or archive directory.
$PROJECT=/project/g/groupname/myccusername
$ARCHIVE=/archive/g/groupname/myccusername
NOTE: Currently archive space is available only via HPSS
IMPORTANT: Future-proof your scripts
When writing your scripts, use the environment variables ($HOME, $SCRATCH, $PROJECT, $ARCHIVE) instead of the actual paths! The paths may change in the future.
Storage and quotas[edit]
You should familiarize yourself with the various file systems, what purpose they serve, and how to properly use them. This table summarizes the various file systems. See the Data Management page for more details.
location | quota | block size | expiration time | backed up | on login nodes | on compute nodes | |
---|---|---|---|---|---|---|---|
$HOME | 100 GB per user | 1 MB | yes | yes | read-only | ||
$SCRATCH | 25 TB per user | 16 MB | 2 months | no | yes | yes | |
50-500TB per group | depending on group size | ||||||
$PROJECT | by group allocation | 16 MB | yes | yes | yes | ||
$ARCHIVE | by group allocation | dual-copy | no | no | |||
$BBUFFER | 10 TB per user | 1 MB | very short | no | yes | yes |
Moving data to Niagara[edit]
If you need to move data to Niagara for analysis, or when you need to move data off of Niagara, use the following guidelines:
- If your data is less than 10GB, move the data using the login nodes.
- If your data is greater than 10GB, move the data using the datamover nodes nia-datamover1.scinet.utoronto.ca and nia-datamover2.scinet.utoronto.ca .
Details of how to use the datamover nodes can be found on the Data Management page.
Loading software modules[edit]
You have two options for running code on Niagara: use existing software, or compile your own. This section focuses on the former.
Other than essentials, all installed software is made available using module commands. These modules set environment variables (PATH, etc.), allowing multiple, conflicting versions of a given package to be available. A detailed explanation of the module system can be found on the modules page.
Common module subcommands are:
module load <module-name>
: use particular softwaremodule purge
: remove currently loaded modulesmodule spider
(or module spider <module-name>
): list available software packagesmodule avail
: list loadable software packagesmodule list
: list loaded modules
Along with modifying common environment variables, such as PATH, and LD_LIBRARY_PATH, these modules also create a SCINET_MODULENAME_ROOT environment variable, which can be used to access commonly needed software directories, such as /include and /lib.
There are handy abbreviations for the module commands. ml
is the same as module list
, and ml <module-name>
is the same as module load <module-name>
.
Software stacks: NiaEnv and CCEnv[edit]
On Niagara, there are two available software stacks:
A Niagara software stack tuned and compiled for this machine. This stack is available by default, but if not, can be reloaded with
module load NiaEnv
The same software stack available on Compute Canada's General Purpose clusters Graham and Cedar, compiled (for now) for a previous generation of CPUs:
module load CCEnv
Or, if you want the same default modules loaded as on Cedar and Graham, then do
module load CCEnv
module load StdEnv
Tips for loading software[edit]
We advise against loading modules in your .bashrc.
This could lead to very confusing behaviour under certain circumstances.Our guidelines for .bashrc files can be found here
Instead, load modules by hand when needed, or by sourcing a separate script.
Load run-specific modules inside your job submission script.
Short names give default versions; e.g.
intel
→intel/2018.2
. It is usually better to be explicit about the versions, for future reproducibility.Modules sometimes require other modules to be loaded first.
Solve these dependencies by using
module spider
.Available compilers and interpreters[edit]
- For most compiled software, one should use the Intel compilers (icc for C, icpc for C++, and ifort for Fortran). Loading an intel module makes these available.
- The GNU compiler suite (gcc, g++, gfortran) is also available, if you load one of the gcc modules.
- Open source interpreted, interactive software is also available:
Please visit the Python or R page for details on using these tools. For information on running MATLAB applications on Niagara, visit this page.
Running commercial software[edit]
May I use commercial software on Niagara?
- Possibly, but you have to bring your own license for it. You can connect to an external license server using ssh tunneling.
- SciNet and Compute Canada have an extremely large and broad user base of thousands of users, so we cannot provide licenses for everyone's favorite software.
- Thus, the only commercial software installed on Niagara is software that can benefit everyone: compilers, math libraries and debuggers.
- That means no MATLAB, Gaussian, IDL,
- Open source alternatives like Octave, Python, and R are available.
- We are happy to help you to install commercial software for which you have a license.
- In some cases, if you have a license, you can use software in the Compute Canada stack.
The list of commercial software which is installed on Niagara, for which you will need a license to use, can be found on the commercial software page.
Compiling on Niagara: Example[edit]
Suppose one want to compile an application from two c source files, main.c and module.c, which use the Gnu Scientific Library (GSL). This is an example of how this would be done:
nia-login07:~$ module list Currently Loaded Modules: 1) NiaEnv/2018a (S) Where: S: Module is Sticky, requires --force to unload or purge nia-login07:~$ module load intel/2018.2 gsl/2.4 nia-login07:~$ ls appl.c module.c nia-login07:~$ icc -c -O3 -xHost -o appl.o appl.c nia-login07:~$ icc -c -O3 -xHost -o module.o module.c nia-login07:~$ icc -o appl module.o appl.o -lgsl -mkl nia-login07:~$ ./appl
Note:
- The optimization flags -O3 -xHost allow the Intel compiler to use instructions specific to the architecture CPU that is present (instead of for more generic x86_64 CPUs).
- Linking with this library is easy when using the intel compiler, it just requires the -mkl flags.
- If compiling with gcc, the optimization flags would be -O3 -march=native. For the way to link with the MKL, it is suggested to use the MKL link line advisor.
Testing[edit]
You really should test your code before you submit it to the cluster to know if your code is correct and what kind of resources you need.
Small test jobs can be run on the login nodes.
Rule of thumb: tests should run no more than a couple of minutes, taking at most about 1-2GB of memory, and use no more than a couple of cores.
You can run the the ddt debugger on the login nodes after
module load ddt
.Short tests that do not fit on a login node, or for which you need a dedicated node, request an interactive debug job with the debug command:
nia-login07:~$ debugjob N
where N is the number of nodes, If N=1, this gives an interactive session one 1 hour, when N=4 (the maximum), it gives you 30 minutes. Finally, if your debugjob process takes more than 1 hour, you can request an interactive job from the regular queue using the salloc command. Note, however, that this may take some time to run, since it will be part of the regular queue, and will be run when the scheduler decides.
nia-login07:~$ salloc --nodes N --time=M:00:00
here N is again the number of nodes, and M is the number of hours you wish the job to run. If you need to use graphics while testing your code through salloc, e.g. when using a debugger such as DDT or DDD, you have the following options, please visit the Testing with graphics page.
Submitting jobs[edit]
Niagara uses SLURM as its job scheduler.
You submit jobs from a login node by passing a script to the sbatch command:
nia-login07:~$ sbatch jobscript.sh
This puts the job in the queue. It will run on the compute nodes in due course.
Jobs will run under their group's RRG allocation, or, if the group has none, under a RAS allocation (previously called `default' allocation).
Keep in mind:
Scheduling is by node, so in multiples of 40-cores.
f your group has an allocation, your job's maximum walltime is 24 hours. If your group is without an allocation, your job's maximum walltime is 12 hours.
Jobs must write to your scratch or project directory (home is read-only on compute nodes).
Compute nodes have no internet access.
Move your data to Niagara before you submit your job.
Scheduling by node[edit]
On many systems that use SLURM, the scheduler will deduce from the specifications of the number of tasks and the number of cpus-per-node what resources should be allocated. On Niagara things are a bit different.
All job resource requests on Niagara are scheduled as a multiple of nodes.
- The nodes that your jobs run on are exclusively yours, for as long as the job is running on them.
- No other users are running anything on them.
- You can ssh into them to see how things are going.
Whatever your requests to the scheduler, it will always be translated into a multiple of nodes allocated to your job.
Memory requests to the scheduler are of no use. Your job always gets N x 202GB of RAM, where N is the number of nodes and 202GB is the amount of memory on the node.
If you run serial jobs you must still use all 40 cores on the node. Visit the serial jobs page for examples of how to do this.
Since there are 40 cores per node, your job should use N x 40 cores. If you do not, we will contact you to help you optimize your workflow. Or you can contact us to get assistance.
Limits[edit]
There are limits to the size and duration of your jobs, the number of jobs you can run and the number of jobs you can have queued. It matters whether a user is part of a group with a Resources for Research Group allocation or not. It also matters in which 'partition' the jobs runs. 'Partitions' are SLURM-speak for use cases. You specify the partition with the -p parameter to sbatch or salloc, but if you do not specify one, your job will run in the compute partition, which is the most common case.
Usage Partition Running jobs Submitted jobs (incl. running) Min. size of jobs Max. size of jobs Min. walltime Max. walltime Compute jobs with an allocation compute 50 1000 1 node (40 cores) 1000 nodes (40000 cores) 15 minutes 24 hours Compute jobs without allocation ("default") compute 50 200 1 node (40 cores) 20 nodes (800 cores) 15 minutes 12 hours Testing or troubleshooting debug 1 1 1 node (40 cores) 4 nodes (160 cores) N/A 1 hour Archiving or retrieving data in HPSS archivelong 2 per user (max 5 total) 10 per user N/A N/A 15 minutes 72 hours Inspecting archived data, small archival actions in HPSS archiveshort 2 per user 10 per user N/A N/A 15 minutes 1 hour Within these limits, jobs will still have to wait in the queue. The waiting time depends on many factors such as the allocation amount, how much allocation was used in the recent past, the number of nodes and the walltime, and how many other jobs are waiting in the queue.
File Input/Output Tips[edit]
It is important to understand the file systems, so as to perform your file I/O (Input/Output) responsibly. Refer to the Data Management page for details about the file systems.
- Your files can be seen on all Niagara login and compute nodes.
- $HOME, $SCRATCH, and $PROJECT all use the parallel file system called GPFS.
- GPFS is a high-performance file system which provides rapid reads and writes to large data sets in parallel from many nodes.
- Accessing data sets which consist of many, small files leads to poor performance on GPFS.
- Avoid reading and writing lots of small amounts of data to disk. Many small files on the system waste space and are slower to access, read and write. If you must write many small files, use ramdisk.
- Write data out in a binary format. This is faster and takes less space.
- The Burst Buffer is better for i/o heavy jobs and to speed up checkpoints.
Example submission script (MPI)[edit]
Suppose you want to run an MPI application called appl_mpi_ex with 320 processes. The job script could look as follows:
#!/bin/bash #SBATCH --nodes=8 #SBATCH --ntasks=320 #SBATCH --time=1:00:00 #SBATCH --job-name mpi_ex #SBATCH --output=mpi_ex_%j.txt cd $SLURM_SUBMIT_DIR module load intel/2018.2 module load openmpi/3.1.0rc3 mpirun ./appl_mpi_ex
Submit this script (if it is called mpi_ex.sh) with the command:
nia-login07:~$ sbatch mpi_ex.sh
First line indicates that this is a bash script.
Lines starting with
#SBATCH
go to SLURM.sbatch reads these lines as a job request (which it gives the name
mpi_ex
)In this case, SLURM looks for 8 nodes with 40 cores on which to run 320 tasks, for 1 hour.
Once it found such a node, it runs the script:
- Change to the submission directory;
- Loads modules;
- Runs the
appl_mpi_ex
application with mpirun (srun should work too).
- To use hyperthreading, just change --ntasks=320 to --ntasks=640, and add --bind-to none to the mpirun command (the latter is necessary for OpenMPI only, not when using IntelMPI).
Example submission script (OpenMP)[edit]
Suppose you want to run a single-node, multi-threaded application called appl_openmp_ex that uses OpenMP. The job script could look as follows:
#!/bin/bash #SBATCH --nodes=1 #SBATCH --cpus-per-task=40 #SBATCH --time=1:00:00 #SBATCH --job-name openmp_ex #SBATCH --output=openmp_ex_%j.txt cd $SLURM_SUBMIT_DIR module load intel/2018.2 export OMP_NUM_THREADS=$SLURM_CPUS_PER_TASK ./openmp_example # or "srun ./openmp_example".
Submit this script (if it is called openmp_ex.sh) with the command:
nia-login07:~$ sbatch openmp_ex.sh
- First line indicates that this is a bash script.
- Lines starting with
#SBATCH
go to SLURM. - sbatch reads these lines as a job request (which it gives the name
openmp_ex
) . - In this case, SLURM looks for one node with 40 cores to be run inside one task, for 1 hour.
- Once it found such a node, it runs the script:
- Change to the submission directory;
- Loads modules (must be done again in the submission script on Niagara);
- Sets an environment variable to set the number of threads to 40 (no hyperthreading in this example);
- Runs the
appl_openmp_ex
application.
- To use hyperthreading, just change --cpus-per-task=40 to --cpus-per-task=80.
Monitoring queued jobs[edit]
Once the job is incorporated into the queue, there are some command you can use to monitor its progress.
squeue
orsqc
(a caching version of squeue) to show the job queue (squeue -u $USER
for just your jobs);qsum
shows a summary of qudue by usersqueue -j JOBID
to get information on a specific job(alternatively,
scontrol show job JOBID
, which is more verbose).squeue --start -j JOBID
to get an estimate for when a job will run; these tend not to be very accurate predictions.scancel -i JOBID
to cancel the job.sinfo -pcompute
to look at available nodes.jobperf JOBID
to get an instantaneous view of the cpu and memory usage of the nodes of the job while it is running.sacct
to get information on your recent jobs.
Further instructions for monitoring your jobs can be found on the Slurm page. The my.SciNet site is also a very useful tool for monitoring your current and past usage.
Visualization[edit]
Information about how to use visualization tools on Niagara is available on Visualization page.
Further information[edit]
Useful sites
- SciNet: https://www.scinet.utoronto.ca
- Niagara: Niagara wiki page
- System Status: https://docs.scinet.utoronto.ca/index.php/Main_Page
- Training: https://support.scinet.utoronto.ca/education
Support
- support@scinet.utoronto.ca
- niagara@computecanada.ca