Niagara Quickstart

System information

Hardware characteristics of the Niagara supercomputer can be found on this page.

Logging in

Access to Niagara is via SSH (secure shell) only.

To access Niagara, first 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 as the compute nodes.

The optional -Y in the commands above 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 to the scheduler.

Migration to Niagara

Migration for existing GPC users

Niagara replaces SciNet clusters

• TCS (Tightly Coupled Cluster) decommissioned last fall and
• GPC (General Purpose Cluster) whose compute nodes will be decommissioned on April 21, 2018 and storage space on May 9, 2018.

Active GPC Users have access to Niagara since April 9, 2018.

The home and project folders were last copied from GPC to Niagara on April 5th, 2018, except for files with names starting with a period and located in home directories (these files were never synced).

It is the user's responsibility to copy to Niagara any 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 and SCINETUSERNAME will be the same. Make sure you use the backslash (\) before the first $SCRATCH; it causes 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 backslash in front of the last occurrence of $SCRATCH.

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

Non-GPC users

Those who are new to SciNet, but have 2018 RAC allocations on Niagara, will have their accounts created and ready for them 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

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

$HOME=/home/g/groupname/myccusername

$SCRATCH=/scratch/g/groupname/myccusername

For example:

nia-login07:~$ pwd
/home/s/scinet/rzon

nia-login07:~$ cd $SCRATCH

nia-login07:rzon$ pwd
/scratch/s/scinet/rzon

Project

Users from groups with a RAC allocation will also have a project directory on Niagara.

$PROJECT=/project/g/groupname/myccusername

IMPORTANT: Future-proof your scripts

Use the environment variables (HOME, SCRATCH, PROJECT) instead of the actual paths since these may change in the future.

Storage

location	quota	block size	expiration time	backed up	on login nodes	on compute nodes
$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, which will be, but is not yet, attached to Niagara.
• Backup means a recent snapshot, not an achive of all data that ever was.

• $BBUFFER stands for the Burst Buffer, a functionality that is still being set up. This parallel storage tier for temporary data will be the fastest

Moving data

Use the scp or rsync commands to move data to either niagara.scinet.utoronto.ca or niagara.computecanada.ca. The transfer method depends on the size of the data you need to move.

• To move less than 10GB, use login nodes, which are the only ones visible from outside Niagara. Transfers done in this way will time out if data is larger than about 10GB.

• To move more than 10GB, use datamover nodes, which are not reachable from the outside. To do so, from a Niagara login node, first ssh into nia-dm1 or nia-dm2 and initiate transfer from the datamovers. The other side of the transfer (e.g. your machine) must be reachable from the outside.

If you often move data, consider using Globus, a web-based tool for data transfer.

You may also want to move data to HPSS/Archive/Nearline, but this functionality will be implemented at a later date. 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 as those loaded on Cedar and Graham, also run 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 on Niagara. This can lead to very confusing behaviour under certain circumstances. Instead, load modules by hand when needed, or by sourcing a separate script, and 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.

There are some handy abbreviations of the module command:

        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-advise 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
------------------------------------------------------------------------------------------------------
  openmpi:
------------------------------------------------------------------------------------------------------
     Versions:
        openmpi/2.1.3
        openmpi/3.0.1
        openmpi/3.1.0rc3

------------------------------------------------------------------------------------------------------
  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 details 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
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

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

Running commercial software

• You may have to provide your own license.
• 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, 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).
• The GSL requires a cblas implementation, which 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.

Testing

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 for users with an allocation, and 12 hours for users that do not have an allocation.

• 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 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.

• You should try to use all the cores on the nodes allocated to your job. Since there are 40 cores per node, your job should use N x 40 cores. If this is not the case, we will be contacted you to help you optimize your workflow.

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 once, 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 (Your Mileage May Vary).

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).

Example submission script (OpenMP)

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

./appl_openmp_ex

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.

Example submission script (MPI)

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).

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.

For more information, check out the wiki page devoted to Running jobs.

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.
• Burst buffer (to come) is better for i/o heavy jobs and to speed up checkpoints.

Resource Allocation Competition

Intel Math Kernel Library, a software library of optimized math routines

Rapid Access Service

Message Passing Interface