Difference between revisions of "Niagara Quickstart"

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  sbatch --job-name=$i.$j.run --output=$i.$j.out --export=i=$i,j=$j jobscript.sbatch
  sbatch --job-name=$i.$j.run --output=$i.$j.out --export=i=$i,j=$j jobscript.sbatch
=== Command line arguments ===
Command line arguments can also be used in the same way as command line argument for shell scripts. The only important detail is that they are considered after the script name, ie. it is better to place all your sbatch flags before the script name, ie.
<source lang="bash">
sbatch  -p debug  jobscript.sbatch  FirstArgument SecondArgument ...
== Email Notification ==
Email notification works, but you need to add the email address and type of notification you may want to receive in your submission script, eg.
<source lang="bash">
#SBATCH --mail-user=YOUR.email.ADDRESS
#SBATCH --mail-type=ALL   

Revision as of 21:01, 10 May 2018

Installed Jan 2018
Operating System CentOS 7.4
Number of Nodes 1500 nodes (60,000 cores)
Interconnect Mellanox Dragonfly+
Ram/Node 188 GiB / 202 GB
Cores/Node 40 (80 hyperthreads)
Login/Devel Node niagara.scinet.utoronto.ca
Vendor Compilers icc (C) ifort (fortran) icpc (C++)
Queue Submission Slurm


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 (would've been #42 on the TOP500 in Nov 2017). Each node 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.

Using Niagara: Logging in

As with all SciNet and CC (Compute Canada) compute systems, access to Niagara is via ssh (secure shell) only.

To access SciNet systems, first open a terminal window (e.g. MobaXTerm on Windows).

Then ssh into the Niagara login nodes with your CC credentials:

$ ssh -Y MYCCUSERNAME@niagara.scinet.utoronto.ca


$ 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.

Migration to Niagara

Migration for Existing Users of the GPC

Niagara is replacing the General Purpose Cluster (GPC) and the Tightly Coupled Cluster (TCS) at SciNet. The TCS was decommissioned last fall, and GPC will be decommissioned very soon: the compute nodes of the GPC will be decommissioned on April 21, 2018, while the storage attached to the GPC will be decommissioned on May 9, 2018.

Active GPC Users got access to the new system, Niagara, on April 9, 2018.

Users' home and project folder were last copied over from the GPC to Niagara on April 5th, 2018, except for files whose name start with a period that were in their home directories (these files were never synced).

It is the user's responsibility to copy over data generated on the GPC after April 5th, 2018.

Data stored in scratch has also not been transfered automatically. Users are to clean up their scratch space on the GPC as much as possible (remember it's temporary data!). Then they can transfer what they need using datamover nodes.

To enable this transfer, there will be a short period during which you can have access to Niagara as well as to the GPC storage resources. This period will end on May 9, 2018.

To copy substantial amounts of data (i.e.,more than 10 GB), please use the datamovers of both the GPC (called gpc-logindm01 and gpc-logindm02) and the Niagara datamovers (called nia-dm1 and nia-dm2). For instance, to copy a directory abc from your GPC scratch to your Niagara scratch directory, you can do the following:

$ ssh CCUSERNAME@niagara.computecanada.ca
$ ssh nia-dm1
$ scp -r SCINETUSERNAME@gpc-logindm01:\$SCRATCH/abc $SCRATCH/abc

For many of you, CCUSERNAME amd SCINETUSERNAME will be the same. Make sure you use the slash (\) before the first $SCRATCH; it cause the value of scratch on the remote node (i.e., here, gpc-logindm01) to be used. Note that the gpc-logindm01 will ask for your SciNet password.

You can also go the other way:

$ ssh SCINETUSERNAME@login.scinet.utoronto.ca
$ ssh gpc-logindm01
$ scp -r $SCRATCH/abc CCUSERNAME@nia-dm1:\$SCRATCH/abc

Again, pay attention to the slash in front of the last occurrence of $SCRATCH.

If you are using rsync, we advice to refrain from using the -a flags, and if using cp, refrain from using the -a and -p flags.

For Non-GPC Users

Those of you new to SciNet, but with 2018 RAC allocations on Niagara, will have your accounts created and ready for you to login.

New, non-RAC users: we are still working out the procedure to get access. If you can't wait, for now, you can follow the old route of requesting a SciNet Consortium Account on the CCDB site.

Locating your directories

home and scratch

You have a home and scratch directory on the system, whose locations will be given by



For example:

nia-login07:~$ pwd

nia-login07:~$ cd $SCRATCH

nia-login07:rzon$ pwd

project and archive

Users from groups with RAC storage allocation will also have a project and/or archive directory.



NOTE: Currently archive space is available only via HPSS

IMPORTANT: Future-proof your scripts

Use the environment variables (HOME, SCRATCH, PROJECT, ARCHIVE) instead of the actual paths! The paths may change in the future.


location quota block size expiration time backed up on login on compute
$HOME 100 GB 1 MB yes yes read-only
$SCRATCH 25 TB 16 MB 2 months no yes yes
$PROJECT by group allocation 16 MB yes yes yes
$ARCHIVE by group allocation dual-copy no no
$BBUFFER ? 1 MB very short no ? ?
  • Compute nodes do not have local storage.
  • Archive space is on HPSS.
  • Backup means a recent snapshot, not an achive of all data that ever was.
  • $BBUFFER stands for the Burst Buffer, a faster parallel storage tier for temporary data.

Moving data

Move amounts less than 10GB through the login nodes.

  • Only Niagara login nodes visible from outside SciNet.
  • Use scp or rsync to niagara.scinet.utoronto.ca or niagara.computecanada.ca (no difference).
  • This will time out for amounts larger than about 10GB.

Move amounts larger than 10GB through the datamover nodes.

  • From a Niagara login node, ssh to nia-datamover1 or nia-datamover2.
  • Transfers must originate from this datamover.
  • The other side (e.g. your machine) must be reachable from the outside.
  • If you do this often, consider using Globus, a web-based tool for data transfer.

Moving data to HPSS/Archive/Nearline using the scheduler.

  • HPSS is a tape-based storage solution, and is SciNet's nearline a.k.a. archive facility.
  • Storage space on HPSS is allocated through the annual Compute Canada RAC allocation.

Loading Software Modules

Other than essentials, all installed software is made available using module commands. These modules set environment variables (PATH, etc.) This allows multiple, conflicting versions of a given package to be available. module spider shows the available software.

For example:

nia-login07:~$ module spider
The following is a list of the modules currently av
  CCEnv: CCEnv

  NiaEnv: NiaEnv/2018a

  anaconda2: anaconda2/5.1.0

  anaconda3: anaconda3/5.1.0

  autotools: autotools/2017
    autoconf, automake, and libtool 

  boost: boost/1.66.0

  cfitsio: cfitsio/3.430

  cmake: cmake/3.10.2 cmake/3.10.3


Common module subcommands are:

  • module load <module-name>

    use particular software

  • module purge

    remove currently loaded modules

  • module spider

    (or module spider <module-name>)

    list available software packages

  • module avail

    list loadable software packages

  • module list

    list loaded modules

On Niagara, there are really two software stacks:

  1. 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
  2. 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

    If you want the same default modules loaded as on Cedar and Graham, then afterwards also module load StdEnv.

Note: the *Env modules are sticky; remove them by --force.

Tips for loading software

  • We advise against loading modules in your .bashrc.

    This could lead to very confusing behaviour under certain circumstances.

  • 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. intelintel/2018.2.

    It is usually better to be explicit about the versions, for future reproducibility.

  • Handy abbreviations:

        ml → module list
        ml NAME → module load NAME  # if NAME is an existing module
        ml X → module X
  • Modules sometimes require other modules to be loaded first.

Solve these dependencies by using module spider.

Module spider

Oddly named, the module subcommand spider is the search-and-advice facility for modules.

Suppose one wanted to load the openmpi module. Upon trying to load the module, one may get the following message:

nia-login07:~$ module load openmpi
Lmod has detected the error:  These module(s) exist but cannot be loaded as requested: "openmpi"
   Try: "module spider openmpi" to see how to load the module(s).

So while that fails, following the advice that the command outputs, the next command would be:

nia-login07:~$ module spider openmpi

  For detailed information about a specific "openmpi" module (including how to load the modules) use
  the module s full name.
  For example:

     $ module spider openmpi/3.1.0rc3

So this gives just more detailed suggestions on using the spider command. Following the advice again, one would type:

nia-login07:~$ module spider openmpi/3.1.0rc3
  openmpi: openmpi/3.1.0rc3
    You will need to load all module(s) on any one of the lines below before the "openmpi/3.1.0rc3"
    module is available to load.

      NiaEnv/2018a  gcc/7.3.0
      NiaEnv/2018a  intel/2018.2

These are concrete instructions on how to load this particular openmpi module. Following these leads to a successful loading of the module.

nia-login07:~$ module load NiaEnv/2018a  intel/2018.2   # note: NiaEnv is usually already loaded
nia-login07:~$ module load openmpi/3.1.0rc3
nia-login07:~$ module list
Currently Loaded Modules:
  1) NiaEnv/2018a (S)   2) intel/2018.2   3) openmpi/3.1.0.rc3

   S:  Module is Sticky, requires --force to unload or purge

Running Commercial Software

  • Possibly, but you have to bring your own license for it.
  • 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, 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.

Compiling on Niagara: Example

Suppose one want to compile an application from two c source files, appl.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)
   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


  • 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).
  • The GSL requires a cblas implementation, for is contained in the Intel Math Kernel Library (MKL). 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.


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: couple of minutes, taking at most about 1-2GB of memory, 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 salloc command

    nia-login07:~$ salloc -pdebug --nodes N --time=1:00:00

    where N is the number of nodes. The duration of your interactive debug session can be at most one hour, can use at most 4 nodes, and each user can only have one such session at a time.

    Alternatively, on Niagara, you can use the 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 give you 30 minutes.

Submitting jobs

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.

  • Maximum walltime is 24 hours.

  • Jobs must write to your scratch or project directory (home is read-only on compute nodes).

  • Compute nodes have no internet access.

    Download data you need beforehand on a login node.

Scheduling by Node

  • All job resource requests on Niagara are scheduled as a multiple of nodes.

  • The nodes that your jobs run on are exclusively yours.
    • 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.

  • Memory requests to the scheduler are of no use.

    Your job gets N x 202GB of RAM if N is the number of nodes.

  • You should use all 40 cores on each of the nodes that your job uses.

    You will be contacted if you don't, and we will help you get more science done.

Hyperthreading: Logical CPUs vs. cores

  • Hyperthreading, a technology that leverages more of the physical hardware by pretending there are twice as many logical cores than real ones, is enabled on Niagara.
  • So the OS and scheduler see 80 logical cores.
  • 80 logical cores vs. 40 real cores typically gives about a 5-10% speedup (YMMV).

Because Niagara is scheduled by node, hyperthreading is actually fairly easy to use:

  • Ask for a certain number of nodes N for your jobs.

  • You know that you get 40xN cores, so you will use (at least) a total of 40xN mpi processes or threads.

    (mpirun, srun, and the OS will automaticallly spread these over the real cores)

  • But you should also test if running 80xN mpi processes or threads gives you any speedup.

  • Regardless, your usage will be counted as 40xNx(walltime in years).


There are limits to the size and durection 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 Resarch 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 50 200 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 10 10 N/A N/A 15 minutes 72 hours
Inspecting archived data, small archival actions in HPSS archiveshort 10 10 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.

Passing Variables to Job's submission scripts

It is possible to pass values through environment variables into your SLURM submission scripts. For doing so with already defined variables in your shell, just add the following directive in the submission script,

#SBATCH --export=ALL

and you will have access to any predefined environment variable.

A better way is to specify explicitly which variables you want to pass into the submision script,

 sbatch --export=i=15,j='test' jobscript.sbatch

You can even set the job name and output files using environment variables, eg.

 sbatch --job-name=$i.$j.run --output=$i.$j.out --export=i=$i,j=$j jobscript.sbatch

Command line arguments

Command line arguments can also be used in the same way as command line argument for shell scripts. The only important detail is that they are considered after the script name, ie. it is better to place all your sbatch flags before the script name, ie.

 sbatch  -p debug  jobscript.sbatch  FirstArgument SecondArgument ...

Email Notification

Email notification works, but you need to add the email address and type of notification you may want to receive in your submission script, eg.

#SBATCH --mail-user=YOUR.email.ADDRESS
#SBATCH --mail-type=ALL    

Example submission script (OpenMP)

#SBATCH --nodes=1
#SBATCH --cpus-per-task=40
#SBATCH --time=1:00:00
#SBATCH --job-name openmp_job
#SBATCH --output=openmp_output_%j.txt


module load intel/2018.2


# or "srun ./openmp_example".

Submit this script with the command:

nia-login07:~$ sbatch openmp_job.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_job) .
  • 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;
    • Sets an environment variable;
    • Runs the openmp_example application.
  • To use hyperthreading, just change --cpus-per-task=40 to --cpus-per-task=80.

Example submission script (MPI)

#SBATCH --nodes=8
#SBATCH --ntasks=320
#SBATCH --time=1:00:00
#SBATCH --job-name mpi_job
#SBATCH --output=mpi_output_%j.txt


module load intel/2018.2
module load openmpi/3.1.0rc3

mpirun ./mpi_example
# or "srun ./mpi_example"

Submit this script with the command:

nia-login07:~$ sbatch mpi_job.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_job)

  • 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 mpi_example application.
  • 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).

Monitoring queued jobs

Once the job is incorporated into the queue, there are some command you can use to monitor its progress.

  • squeue or qsum to show the job queue (squeue -u $USER for just your jobs);

  • squeue -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.

  • More utilities like those that were available on the GPC are under development.

Data Management and I/O Tips

  • $HOME, $SCRATCH, and $PROJECT all use the parallel file system called GPFS.
  • Your files can be seen on all Niagara login and compute nodes.
  • GPFS is a high-performance file system which provides rapid reads and writes to large data sets in parallel from many nodes.
  • But accessing data sets which consist of many, small files leads to poor performance.
  • Avoid reading and writing lots of small amounts of data to disk.
  • Many small files on the system would waste space and would be slower to access, read and write.
  • Write data out in binary. Faster and takes less space.
  • The Burst Buffer is better for i/o heavy jobs and to speed up checkpoints.


Information about how to use visualization tools on Niagara is available on Visualization page.

Further information

Useful sites


  • support@scinet.utoronto.ca
  • niagara@computecanada.ca