Niagara Quickstart: Difference between revisions

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The Niagara cluster is a large cluster of 1500 Lenovo SD350 servers each with 40 Intel "Skylake" cores at 2.4 GHz.  
The Niagara cluster is a large cluster of 1548 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 [https://www.top500.org/list/2018/06/?page=1 TOP500 list of June 2018].  
The peak performance of the cluster is 3.02 PFlops delivered / 4.75 PFlops theoretical.  It is the 53rd fastest supercomputer on the [https://www.top500.org/list/2018/06/?page=1 TOP500 list of June 2018].  


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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.
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 24 hours and favours large jobs.


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See the [https://support.scinet.utoronto.ca/education/go.php/370/content.php/cid/1383/ "Intro to Niagara"] recording
See the [https://support.scinet.utoronto.ca/education/go.php/370/content.php/cid/1383/ Intro to Niagara] recording


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More detailed hardware characteristics of the Niagara supercomputer can be found [[Niagara|on this page]].
More detailed hardware characteristics of the Niagara supercomputer can be found [[Niagara|on this page]].


= Getting started on Niagara =
= Getting started on Niagara = <!--T:209-->


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Those of you new to SciNet and belonging to a group whose primary PI does not have an allocation, as granted in the annual [https://www.computecanada.ca/research-portal/accessing-resources/resource-allocation-competitions Compute Canada RAC], must first follow the old route of [https://www.scinethpc.ca/getting-a-scinet-account/ requesting a SciNet Consortium Account on the CCDB site] to gain access to Niagara.
Access to Niagara is not enabled automatically for everyone with an Alliance account, but anyone with an active Alliance account can get their access enabled.
If you have an active Alliance account but you do not have access to Niagara yet (e.g. because you are a new user and belong to a group whose primary PI does not have an allocation as granted in the annual [https://www.computecanada.ca/research-portal/accessing-resources/resource-allocation-competitions Alliance RAC]), go to the [https://ccdb.computecanada.ca/services/opt_in opt-in page on the CCDB site].  After clicking the "Join" button on that page, it usually takes only one or two business days for access to be granted.


Please read this document carefully.  The [https://docs.scinet.utoronto.ca/index.php/FAQ FAQ] is also a useful resource.  If at any time you require assistance, or if something is unclear, please do not hesitate to [mailto:support@scinet.utoronto.ca contact us]
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Please read this document carefully.  The [https://docs.scinet.utoronto.ca/index.php/FAQ FAQ] is also a useful resource.  If at any time you require assistance, or if something is unclear, please do not hesitate to [mailto:niagara@computecanada.ca contact us].


== Logging in == <!--T:3-->
== Logging in == <!--T:3-->
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 [https://support.scinet.utoronto.ca/education/browse.php?category=-1&search=scmp101&include=all&filter=Filter Introduction to Linux Shell] class.
Niagara runs CentOS 7, which is a type of Linux.  You will need to be familiar with Linux systems to work on Niagara.  If you are not it will be worth your time to review  
the [[Linux introduction]] or to attend a local "Linux Shell" workshop.  


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As with all SciNet and CC (Compute Canada) compute systems, access to Niagara is done via ssh (secure shell) only.
As with all SciNet and Alliance compute systems, access to Niagara is done via ssh (secure shell) only. As of January 22 2022, authentication is only allowed via SSH keys. Please refer to [[SSH_Keys|this page]] to generate your SSH key pair and make sure you use them securely.
 
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Open a terminal window (e.g. [[Connecting with PuTTY|PuTTY]] on Windows or [[Connecting with MobaXTerm|MobaXTerm]]), then ssh into the Niagara login nodes with your CC credentials:
Open a terminal window (e.g. [[Connecting with PuTTY|PuTTY]] on Windows or [[Connecting with MobaXTerm|MobaXTerm]]), then ssh into the Niagara login nodes with your CC credentials:


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<source lang="bash">
<source lang="bash">
$ ssh -Y MYCCUSERNAME@niagara.scinet.utoronto.ca</source>
$ ssh -i /path/to/ssh_private_key -Y MYCCUSERNAME@niagara.scinet.utoronto.ca</source>


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<source lang="bash">$ ssh -Y MYCCUSERNAME@niagara.computecanada.ca</source>
<source lang="bash">$ ssh -i /path/to/ssh_private_key -Y MYCCUSERNAME@niagara.computecanada.ca</source>


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<translate>
<translate>


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NOTE: home is read-only on compute nodes.
NOTE: home is read-only on compute nodes.


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Users from groups with [https://www.computecanada.ca/research-portal/accessing-resources/resource-allocation-competitions RAC storage allocation] will also have a project and/or archive directory.
Users from groups with [https://www.computecanada.ca/research-portal/accessing-resources/resource-allocation-competitions RAC storage allocation] will also have a project and possibly an archive directory.


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NOTE: Currently archive space is available only via [https://docs.scinet.utoronto.ca/index.php/HPSS HPSS]
NOTE: Currently archive space is available only via [https://docs.scinet.utoronto.ca/index.php/HPSS HPSS], and is not accessible on the Niagara login, compute, or datamover nodes.


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=== Storage and quotas === <!--T:39-->
=== Storage and quotas === <!--T:39-->


You should familiarize yourself with the [[Data_Management#Purpose_of_each_file_system | various file systems]], what purpose they serve, and how to properly use them.  This table summarizes the various file systems.  See the [[Data_Management | Data Management]] page for more details.
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You should familiarize yourself with the [[Data_management_at_Niagara#Purpose_of_each_file_system | various file systems]], what purpose they serve, and how to properly use them.  This table summarizes the various file systems.  See the [[Data_management_at_Niagara | Data management at Niagara]] page for more details.


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|-
|-
|align="right"|50-500TB per group
|align="right"|50-500TB per group
|align="right"|[[Data_Management#Quotas_and_purging | depending on group size]]
|align="right"|[[Data_management#Quotas_and_purging | depending on group size]]
|-
|-
| $PROJECT
| $PROJECT
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|}
|}


=== Moving data to Niagara ===
=== Moving data to Niagara === <!--T:213-->


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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 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 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 .
* 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#Moving_data | Data Management ]] page.
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Details of how to use the datamover nodes can be found on the [[Data_management_at_Niagara#Moving_data | Data management at Niagara]] page.


= Loading software modules = <!--T:48-->
= Loading software modules = <!--T:48-->
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You have two options for running code on Niagara: use existing software, or [[Niagara_Quickstart#Compiling_on_Niagara:_Example | compile your own]].  This section focuses on the former.


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Other than essentials, all installed software is made available [[Using modules|using module commands]]. These modules set environment variables (<code>PATH</code>, etc.) This allows multiple, conflicting versions of a given package to be available. <tt> module spider</tt> shows the available software.
Other than essentials, all installed software is made available [[Using_modules | 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 [[Using_modules | found on the modules page]].
 
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For example:
</translate>
<source lang="bash">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
<!--T:217-->
    autoconf, automake, and libtool
 
  boost: boost/1.66.0
 
  cfitsio: cfitsio/3.430
 
  cmake: cmake/3.10.2 cmake/3.10.3
 
  ...</source>
<translate>
<!--T:52-->
<ul>
Common module subcommands are:
Common module subcommands are:
<li><code>module load &lt;module-name&gt;</code>: use particular software</li>
<li><code>module load &lt;module-name&gt;</code>: use particular software</li>
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<li><code>module spider</code> (or <code>module spider &lt;module-name&gt;</code>): list available software packages</li>
<li><code>module spider</code> (or <code>module spider &lt;module-name&gt;</code>): list available software packages</li>
<li><code>module avail</code>: list loadable software packages</li>
<li><code>module avail</code>: list loadable software packages</li>
<li><code>module list</code>: list loaded modules</li></ul>
<li><code>module list</code>: list loaded modules</li>
 
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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.
 
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There are handy abbreviations for the module commands. <code>ml</code> is the same as <code>module list</code>, and <code>ml <module-name></code> is the same as <code>module load <module-name></code>.
 
== Software stacks: NiaEnv and CCEnv == <!--T:220-->


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On Niagara, there are really two software stacks:
On Niagara, there are two available software stacks:


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<!--T:54-->
<ol style="list-style-type: decimal;">
<ol style="list-style-type: decimal;">
<li><p>A [[Modules specific to Niagara|Niagara software stack]] tuned and compiled for this machine. This stack is available by default, but if not, can be reloaded with</p>
<li><p>A [[Modules_specific_to_Niagara | Niagara software stack]] tuned and compiled for this machine. This stack is available by default, but if not, can be reloaded with</p>
<source lang="bash">module load NiaEnv</source></li>
<code>module load NiaEnv</code></li>
<li><p>The same [[Modules|software stack available on Compute Canada's General Purpose clusters]] [https://docs.computecanada.ca/wiki/Graham Graham] and [https://docs.computecanada.ca/wiki/Cedar Cedar], compiled (for now) for a previous generation of CPUs:</p>
<li><p>The standard [[Available software|Alliance software stack]] which is available on Alliance's other clusters (including [[Graham]], [[Cedar]], [[Narval]], and [[Beluga]]):</p>
<source lang="bash">module load CCEnv</source>
<code>module load CCEnv arch/avx512</code>
<p>If you want the same default modules as those loaded on Cedar and Graham, also run <code>module load StdEnv</code>.</p></li></ol>
<br>(without the <tt>arch/avx512</tt> module, you'd get the modules for a previous generation of CPUs)
 
<p>Or, if you want the same default modules loaded as on Cedar, Graham, and Beluga, then do
<!--T:55-->
</p><p>
Note: the <code>*Env</code> modules are '''''sticky'''''; remove them by <code>--force</code>.
<code>module load CCEnv arch/avx512 StdEnv/2018.3</code>
</p>
</li></ol>


== Tips for loading software == <!--T:56-->
== Tips for loading software == <!--T:56-->
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The default .bashrc and .bash_profile files on Niagara can be found [https://docs.scinet.utoronto.ca/index.php/Bashrc_guidelines here]
Our guidelines for .bashrc files can be found [https://docs.scinet.utoronto.ca/index.php/Bashrc_guidelines here]


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Short names give default versions; e.g. <code>intel</code> → <code>intel/2018.2</code>.  It is usually better to be explicit about the versions, for future reproducibility.
Short names give default versions; e.g. <code>intel</code> → <code>intel/2018.2</code>.  It is usually better to be explicit about the versions, for future reproducibility.
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Handy abbreviations:
<!--T:60-->
<pre class="sh">
        ml → module list
        ml NAME → module load NAME  # if NAME is an existing module
        ml X → module X
</pre>


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Solve these dependencies by using <code>module spider</code>.
Solve these dependencies by using <code>module spider</code>.


== Module spider == <!--T:63-->
= Available compilers and interpreters = <!--T:221-->
 
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Oddly named, the module subcommand spider is the search-and-advise facility for modules.


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Suppose one wanted to load the openmpi module.  Upon trying to load the module, one may get the following message:
* For most compiled software, one should use the Intel compilers (<tt>icc</tt> for C, <tt>icpc</tt> for C++, and <tt>ifort</tt> for Fortran). Loading an <tt>intel</tt> module makes these available.
<source lang="bash">nia-login07:~$ module load openmpi
* The GNU compiler suite (<tt>gcc, g++, gfortran</tt>) is also available, if you load one of the <tt>gcc</tt> modules.
Lmod has detected the error:  These module(s) exist but cannot be loaded as requested: "openmpi"
* Open source interpreted, interactive software is also available:
  Try: "module spider openmpi" to see how to load the module(s).</source>
** [[Python]]
So while that fails, following the advice that the command outputs, the next command would be:
** [[R]]
</translate>
** Julia
<source lang="bash">nia-login07:~$ module spider openmpi
** Octave
------------------------------------------------------------------------------------------------------
 
  openmpi:
Please visit the [[Python]] or [[R]] page for details on using these tools. For information on running MATLAB applications on Niagara, visit [[MATLAB| this page]].
------------------------------------------------------------------------------------------------------
    Versions:
        openmpi/2.1.3
        openmpi/3.0.1
        openmpi/3.1.0rc3


------------------------------------------------------------------------------------------------------
= Using Commercial Software = <!--T:67-->
  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
<!--T:223-->
------------------------------------------------------------------------------------------------------</source>
May I use commercial software on Niagara?
<translate>
<!--T:98-->
So this gives just more details suggestions on using the <tt>spider</tt> command. Following the advice again, one would type:
</translate>
<source lang="bash">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
</source>
<translate>
<!--T:66-->
These are concrete instructions on how to load this particular openmpi module. Following these leads to a successful loading of the module.
</translate>
<source lang="bash">
nia-login07:~$ module load NiaEnv/2018a  intel/2018.2
nia-login07:~$ module load openmpi/3.1.0rc3
</source>
<source lang="bash">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</source>
 
<translate>
= Running commercial software = <!--T:67-->


<!--T:68-->
<!--T:68-->
* You may have to provide your own license.
* Possibly, but you have to bring your own license for it.  You can connect to an external license server using [https://docs.scinet.utoronto.ca/index.php/SSH_Tunneling 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.
* SciNet and Alliance 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.
* 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,  
* That means no [[MATLAB]], Gaussian, IDL,  
* Open source alternatives like Octave, Python, R are available.
* 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.
* 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.
* In some cases, if you have a license, you can use software in the Alliance 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 [https://docs.scinet.utoronto.ca/index.php/Commercial_software commercial software page].


= Compiling on Niagara: Example = <!--T:69-->
= Compiling on Niagara: Example = <!--T:69-->
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Note:
Note:
* The optimization flags <tt>-O3 -xHost</tt> allow the Intel compiler to use instructions specific to the architecture CPU that is present (instead of for more generic x86_64 CPUs).
* The optimization flags <tt>-O3 -xHost</tt> 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 <tt>-mkl</tt> flags.
* Linking with this library is easy when using the intel compiler, it just requires the <tt>-mkl</tt> flags.
* If compiling with gcc, the optimization flags would be <tt>-O3 -march=native</tt>.  For the way to link with the MKL, it is suggested to use the [https://software.intel.com/en-us/articles/intel-mkl-link-line-advisor MKL link line advisor].
* If compiling with gcc, the optimization flags would be <tt>-O3 -march=native</tt>.  For the way to link with the MKL, it is suggested to use the [https://software.intel.com/en-us/articles/intel-mkl-link-line-advisor MKL link line advisor].


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<ul>
<ul>
<li><p>Small test jobs can be run on the login nodes.</p>
<li>Small test jobs can be run on the login nodes.
<p>Rule of thumb: couple of minutes, taking at most about 1-2GB of memory, couple of cores.</p></li>
<p>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.</p>
<li><p>You can run the the ddt debugger on the login nodes after <code>module load ddt</code>.</p></li>
</li>
<li><p>Short tests that do not fit on a login node, or for which you need a dedicated node, request an<br />
<li>
interactive debug job with the salloc command</p>
<p>You can run the ddt debugger on the login nodes after <code>module load ddt</code>.</p>
<source lang="bash">nia-login07:~$ salloc -pdebug --nodes N --time=1:00:00</source>
</li>
<p>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.</p>
<li>
Alternatively, on Niagara, you can use the command
<p>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:</p>
<source lang="bash">nia-login07:~$ debugjob N</source>
<source lang="bash">nia-login07:~$ debugjob N</source>
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.
<p>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.</p><p> 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.</p>
</li></ul>
<source lang="bash">nia-login07:~$ salloc --nodes N --time=M:00:00</source>
 
<p>here N is again the number of nodes, and M is the number of hours you wish the job to run.</p>
== Testing with Graphics: X-forwarding == <!--T:158-->
<p>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
If you need to use graphics while testing your code, e.g. when using a debugger such as DDT or DDD, you have the following options:
[[Testing_With_Graphics | Testing with graphics]] page.</p>
 
</li>
<!--T:159-->
<ul>
<li> You can use the <code>debugjob</code> command which automatically provides X-forwarding support.
<source lang="bash">
$ ssh niagara.scinet.utoronto.ca -X
 
<!--T:160-->
USER@nia-login07:~$ debugjob
debugjob: Requesting 1 nodes for 60 minutes
xalloc: Granted job allocation 189857
xalloc: Waiting for resource configuration
xalloc: Nodes nia0030 are ready for job
 
<!--T:161-->
[USER@nia1265 ~]$
</source>
 
<!--T:162-->
<li> If <code>debugjob</code> is not suitable for your case due to the limitations either on time or resources (see above [[#Testing]]), then you have to follow these steps:
 
<!--T:163-->
You will need two terminals in order to achieve this:
<ol>
<li>In the 1st terminal
<ul>
<li> ssh to <code>niagara.scinet.utoronto.ca</code> and issue your <code>salloc</code> command
<li> wait until your resources are allocated and you are assigned the nodes
<li> take note of the node where you are logged to, ie. the head node, let's say <code>niaWXYZ</code>
</ul>
<source lang="bash">
$ ssh  niagara.scinet.utoronto.ca
USER@nia-login07:~$ salloc --nodes 5 --time=2:00:00
 
<!--T:164-->
.salloc: Granted job allocation 141862
.salloc: Waiting for resource configuration
.salloc: Nodes nia1265 are ready for job
 
<!--T:165-->
[USER@nia1265 ~]$
</source>
 
<!--T:166-->
<li> On the second terminal:
<ul>
<li> ssh into <code>niagara.scinet.utoronto.ca</code> now using the <code>-X</code> flag in the ssh command
 
<!--T:167-->
<li> after that <code>ssh -X niaWXYZ</code>, ie. you will ssh carrying on the '-X' flag into the head node of the job
 
<!--T:168-->
<li> in the <code>niaWXYZ</code> you should be able to use graphics and should be redirected by x-forwarding to your local terminal
</ul>
 
<!--T:169-->
<source lang="bash">
ssh niagara.scinet.utoronto.ca -X
USER@nia-login07:~$ ssh -X nia1265
[USER@nia1265 ~]$ xclock  ## just an example to test the graphics, a clock should pop up, close it to exit
[USER@nia1265 ~]$ module load ddt  ## load corresponding modules, eg. for DDT
[USER@nia1265 ~]$ ddt  ## launch DDT, the GUI should appear in your screen
</source>
 
<!--T:170-->
</ol>
</ul>
 
 
<!--T:171-->
Observations:
<ul>
<li> If you are using ssh from a Windows machine, you need to have an X-server, a good option is to use MobaXterm, that already brings an X-server included.
<li> If you are in Mac OS, substitute -X by -Y
<li> Instead of using two terminals, you could just use <code>screen</code> to request the resources and then detach the session and ssh into the head node directly.
</ul>
</ul>


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<li><p>Niagara uses SLURM as its job scheduler.</p></li>
<li><p>Niagara uses SLURM as its job scheduler.</p></li>
<li><p>You submit jobs from a login node by passing a script to the sbatch command:</p>
<li><p>You submit jobs from a login node by passing a script to the sbatch command:</p>
<source lang="bash">nia-login07:~$ sbatch jobscript.sh</source></li>
<source lang="bash">nia-login07:scratch$ sbatch jobscript.sh</source></li>
<li><p>This puts the job in the queue. It will run on the compute nodes in due course.</p></li>
<li><p>This puts the job in the queue. It will run on the compute nodes in due course.</p></li>
<li><p>Jobs will run under their group's RRG allocation, or, if the group has none, under a RAS allocation (previously called `default' allocation).</p></li></ul>
<li><p>In most cases, you will want to submit from your $SCRATCH directory, so that the output of your compute job can be written out (as mentioned above, $HOME is read-only on the compute nodes).</p>
<li><p>Jobs will run under their group's RRG allocation, or, if the group has none, under a RAS allocation (previously called 'default' allocation).</p></li>
<li><p>Some example job scripts can be found below.</p></li>
</ul>


<!--T:77-->
<!--T:77-->
Line 468: Line 342:
<ul>
<ul>
<li><p>Scheduling is by node, so in multiples of 40-cores.</p></li>
<li><p>Scheduling is by node, so in multiples of 40-cores.</p></li>
<li><p>Maximum walltime is 24 hours (or 12 hours for users without an allocation).</p></li>
<li><p> Your job's maximum walltime is 24 hours.</p></li>
<li><p>Jobs must write to your scratch or project directory (home is read-only on compute nodes).</p></li>
<li><p>Jobs must write to your scratch or project directory (home is read-only on compute nodes).</p></li>
<li><p>Compute nodes have no internet access.</p>
<li><p>Compute nodes have no internet access.</p>
<p>Download data you need beforehand on a login node.</p></li></ul>
<p>[[Data_management_at_Niagara#Moving_data | Move your data]] to Niagara before you submit your job.</p></li></ul>
 
== SLURM nomenclature: jobs, nodes, tasks, cpus, cores, threads  == <!--T:172-->
 
<!--T:173-->
SLURM, which is the job scheduler used on Niagara, has a somewhat different way of referring to things like mpi processes and threads tasks.  The SLURM nomenclature is reflected in the names of scheduler option (i.e., resource requests). SLURM strictly enforces those requests, so it is important to get this right.
 
<!--T:174-->
{| class="wikitable"
!term
!meaning
!SLURM term
!related scheduler options
|-
|job
|scheduled piece of work for which specific resources were requested.
|job
|<tt>sbatch, salloc</tt>
|-
|node
|basic computing component with several cores (40 for Niagara) that share memory 
|node
|<tt>--nodes -N</tt>
|-
|mpi process
|one of a group of running programs using Message Passing Interface for parallel computing
|task
|<tt>--ntasks -n --ntasks-per-node</tt>
|-
|core ''or'' physical cpu
|A fully functional independent physical execution unit.
| - 
| -
|-
|logical cpu
|An execution unit that the operating system can assign work to. Operating systems can be configured to overload physical cores with multiple logical cpus using hyperthreading.
|cpu
|<tt>--ncpus-per-task</tt>
|-
|thread
|one of possibly multiple simultaneous execution paths within a program, which can share memory.
| -
| <tt>--ncpus-per-task</tt> '''and''' <tt>OMP_NUM_THREADS</tt>
|-
|hyperthread
|a thread run in a collection of threads that is larger than the number of physical cores.
| -
| -
|}


== Scheduling by node == <!--T:79-->
== Scheduling by node == <!--T:79-->
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.


<!--T:80-->
<!--T:80-->
<ul>
<ul>
<li><p>All job resource requests on Niagara are scheduled as a multiple of '''nodes'''.</p></li>
<li><p>All job resource requests on Niagara are scheduled as a multiple of '''nodes'''.</p></li>
<li>The nodes that your jobs run on are exclusively yours.
<li>The nodes that your jobs run on are exclusively yours, for as long as the job is running on them.
<ul>
<ul>
<li>No other users are running anything on them.</li>
<li>No other users are running anything on them.</li>
Line 532: Line 359:
</li>
</li>
<li><p>Whatever your requests to the scheduler, it will always be translated into a multiple of nodes allocated to your job.</p></li>
<li><p>Whatever your requests to the scheduler, it will always be translated into a multiple of nodes allocated to your job.</p></li>
<li><p>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.</p></li>
<li><p>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.</p></li>
<li><p>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.</p></li></ul>
<li><p>If you run serial jobs you must still use all 40 cores on the node.  Visit the [https://docs.scinet.utoronto.ca/index.php/Running_Serial_Jobs_on_Niagara serial jobs] page for examples of how to do this.</p></li>
 
<li><p>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 [mailto:support@scinet.utoronto.ca contact us] to get assistance.</p></li></ul>
== Hyperthreading: Logical CPUs vs. cores == <!--T:81-->
 
<!--T:82-->
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.
 
<!--T:83-->
So the OS and scheduler see 80 logical cores.
 
<!--T:84-->
80 logical cores vs. 40 real cores typically gives about a 5-10% speedup (Your Mileage May Vary).
 
<!--T:85-->
Because Niagara is scheduled by node, hyperthreading is actually fairly easy to use:
 
<!--T:86-->
<ul>
<li>Ask for a certain number of nodes N for your jobs.</li>
<li>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)</li>
<li>But you should also test if running 80xN mpi processes or threads gives you any speedup.</li>
<li>Regardless, your usage will be counted as 40xNx(walltime in years).</li>
</ul>


== Limits == <!--T:175-->
== Limits == <!--T:175-->
Line 575: Line 381:
|Compute jobs with an allocation||compute || 50 || 1000 || 1 node (40 cores) || 1000 nodes (40000 cores)|| 15 minutes || 24 hours
|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
|Compute jobs without allocation ("default")||compute || 50 || 200 || 1 node (40 cores) || 20 nodes (800 cores)|| 15 minutes || 24 hours
|-
|-
|Testing or troubleshooting || debug || 1 || 1 || 1 node (40 cores) || 4 nodes (160 cores)|| N/A || 1 hour
|Testing or troubleshooting || debug || 1 || 1 || 1 node (40 cores) || 4 nodes (160 cores)|| N/A || 1 hour
Line 587: Line 393:
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.
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.


== SLURM Accounts == <!--T:179-->
== File Input/Output Tips == <!--T:224-->


<!--T:180-->
<!--T:225-->
To be able to prioritise jobs based on groups and allocations, the SLURM scheduler uses the concept of ''accounts''.  Each group that has a Resource for Research Groups (RRG) or Research Platforms and Portals (RPP) allocation (awarded through an annual competition by Compute Canada) has an account that starts with <tt>rrg-</tt> or <tt>rpp-</tt>SLURM assigns a 'fairshare' priority to these accounts based on the size of the award in core-years. Groups without an RRG or RPP can use Niagara using a so-called Rapid Access Service (RAS), and have an account that starts with <tt>def-</tt>.
It is important to understand the file systems, so as to perform your file I/O (Input/Output) responsiblyRefer to the [[Data_management_at_niagara | Data management at Niagara]] page for details about the file systems.
 
* Your files can be seen on all Niagara login and compute nodes.
<!--T:181-->
* $HOME, $SCRATCH, and $PROJECT all use the parallel file system called GPFS.
On Niagara, most users will only ever use one account, and those users do not need to specify the account to SLURM.  However, users that are part of collaborations may be able to use multiple accounts, i.e., that of their sponsor and that of their collaborator, but this mean that they need to select the right account when running jobs.  
* 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.
<!--T:182-->
* Avoid reading and writing lots of small amounts of data to diskMany small files on the system waste space and are slower to access, read and writeIf you must write many small files, use [https://docs.scinet.utoronto.ca/index.php/User_Ramdisk ramdisk].
To select the account, just add
* Write data out in a binary format. This is faster and takes less space.
 
* The [https://docs.scinet.utoronto.ca/index.php/Burst_Buffer Burst Buffer] is better for i/o heavy jobs and to speed up [https://docs.scinet.utoronto.ca/index.php/Checkpoints checkpoints].
    <!--T:183-->
#SBATCH -A [account]
 
<!--T:184-->
to the job scripts, or use the <tt>-A [account]</tt> to <tt>salloc</tt> or <tt>debugjob</tt>.  
 
<!--T:185-->
To see which accounts you have access to, or what their names are, use the command
 
    <!--T:186-->
sshare -U
 
== Passing Variables to Job's submission scripts == <!--T:187-->
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,
 
<!--T:188-->
#SBATCH --export=ALL
 
<!--T:189-->
and you will have access to any predefined environment variable.
 
<!--T:190-->
A better way is to specify explicitly which variables you want to pass into the submision script,
 
  <!--T:191-->
sbatch --export=i=15,j='test' jobscript.sbatch
 
<!--T:192-->
You can even set the job name and output files using environment variables, eg.
 
  <!--T:193-->
i="simulation"
j=14
sbatch --job-name=$i.$j.run --output=$i.$j.out --export=i=$i,j=$j jobscript.sbatch
 
<!--T:194-->
(The latter only works on the command line; you cannot use environment variables in <tt>#SBATCH</tt> lines in the job script.)
 
<!--T:195-->
'''Command line arguments:'''
 
<!--T:196-->
Command line arguments can also be used in the same way as command line argument for shell scripts. All command line arguments given to sbatch that follow after the job script name, will be passed to the job script. In fact, SLURM will not look at any of
these arguments, so you must place all sbatch arguments before the script name, e.g.:
 
<!--T:197-->
sbatch  -p debug  jobscript.sbatch  FirstArgument SecondArgument ...
 
<!--T:198-->
In this example, <tt>-p debug</tt> is interpreted by SLURM, while in your submission script you can access <tt>FirstArgument</tt>, <tt>SecondArgument</tt>, etc., by referring to <code>$1, $2, ...</code>.
 
== Email Notification == <!--T:199-->
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.
 
    <!--T:200-->
#SBATCH --mail-user=YOUR.email.ADDRESS
    #SBATCH --mail-type=ALL
 
<!--T:201-->
If you omit the mail-user option, the scheduler will use the primary email address associated with your Compute Canada account.
 
<!--T:202-->
The sbatch man page (type <tt>man sbatch</tt> on Niagara) explains all possible mail-types.


== Example submission script (MPI) == <!--T:90-->
== Example submission script (MPI) == <!--T:90-->
Suppose you want to run an [[MPI]] application called <tt>appl_mpi_ex</tt> with 320 processes. The job script could look as follows:
</translate>
</translate>
<source lang="bash">
<source lang="bash">
#!/bin/bash  
#!/bin/bash  
#SBATCH --nodes=8
#SBATCH --nodes=2
#SBATCH --ntasks=320
#SBATCH --ntasks=80
#SBATCH --time=1:00:00
#SBATCH --time=1:00:00
#SBATCH --job-name mpi_ex
#SBATCH --job-name mpi_job
#SBATCH --output=mpi_ex_%j.txt
#SBATCH --output=mpi_output_%j.txt
 
#SBATCH --mail-type=FAIL
cd $SLURM_SUBMIT_DIR
cd $SLURM_SUBMIT_DIR
 
module load intel/2018.2
module load intel/2018.2
module load openmpi/3.1.0rc3
module load openmpi/3.1.0
 
mpirun ./appl_mpi_ex
mpirun ./mpi_example
# or "srun ./mpi_example"
</source>
</source>
<translate>
<translate>
<!--T:91-->
<!--T:91-->
Submit this script (if it is called mpi_ex.sh) with the command:
Submit this script from your scratch directory with the command:
<source lang="bash">nia-login07:~$ sbatch mpi_ex.sh</source>
<source lang="bash">nia-login07:scratch$ sbatch mpi_job.sh</source>
 
<!--T:226-->
<ul>
<ul>
<li><p>First line indicates that this is a bash script.</p></li>
<li>First line indicates that this is a bash script.</li>
<li><p>Lines starting with <code>#SBATCH</code> go to SLURM.</p></li>
<li>Lines starting with <code>#SBATCH</code> go to SLURM.</li>
<li><p>sbatch reads these lines as a job request (which it gives the name <code>mpi_ex</code>)</p></li>
<li>sbatch reads these lines as a job request (which it gives the name <code>mpi_job</code>)</li>
<li><p>In this case, SLURM looks for 8 nodes with 40 cores on which to run 320 tasks, for 1 hour.</p></li>
<li>In this case, SLURM looks for 2 nodes (each of which will have 40 cores) on which to run a total of 80 tasks, for 1 hour.<br>(Instead of specifying <tt>--ntasks=80</tt>, you can also ask for <tt>--ntasks-per-node=40</tt>, which amounts to the same.)</li>
<li><p>Once it found such a node, it runs the script:</p>
<li>Note that the mpifun flag "--ppn" (processors per node) is ignored.</li>
<li>Once it found such a node, it runs the script:
<ul>
<ul>
<li>Change to the submission directory;</li>
<li>Change to the submission directory;</li>
<li>Loads modules;</li>
<li>Loads modules;</li>
<li>Runs the <code>appl_mpi_ex</code> application with mpirun (srun should work too).</li></ul>
<li>Runs the <code>mpi_example</code> application (SLURM will inform mpirun or srun on how many processes to run).
</li>
</li>
<li>To use hyperthreading, just change <tt>--ntasks=320</tt> to <tt>--ntasks=640</tt>, and add <tt>--bind-to none</tt> to the mpirun command (the latter is necessary for OpenMPI only, not when using IntelMPI).</li>
</ul>
<li>To use hyperthreading, just change --ntasks=80 to --ntasks=160, and add --bind-to none to the mpirun command (the latter is necessary for OpenMPI only, not when using IntelMPI).
</ul>
</ul>


== Example submission script (OpenMP) == <!--T:87-->
== Example submission script (OpenMP) == <!--T:87-->


<!--T:88-->
Suppose you want to run a single-node, multi-threaded application called <tt>appl_openmp_ex</tt> that uses [[OpenMP]]. The job script could look as follows:
</translate>
</translate>
<source lang="bash">#!/bin/bash
<source lang="bash">#!/bin/bash
#!/bin/bash
#SBATCH --nodes=1
#SBATCH --nodes=1
#SBATCH --cpus-per-task=40
#SBATCH --cpus-per-task=40
#SBATCH --time=1:00:00
#SBATCH --time=1:00:00
#SBATCH --job-name openmp_ex
#SBATCH --job-name openmp_job
#SBATCH --output=openmp_ex_%j.txt
#SBATCH --output=openmp_output_%j.txt
 
#SBATCH --mail-type=FAIL
cd $SLURM_SUBMIT_DIR
cd $SLURM_SUBMIT_DIR
 
module load intel/2018.2
module load intel/2018.2
 
export OMP_NUM_THREADS=$SLURM_CPUS_PER_TASK
export OMP_NUM_THREADS=$SLURM_CPUS_PER_TASK
 
./openmp_example
./openmp_example
# or "srun ./openmp_example".
# or "srun ./openmp_example".
Line 722: Line 469:
<translate>
<translate>
<!--T:89-->
<!--T:89-->
Submit this script (if it is called openmp_ex.sh) with the command:
Submit this script from your scratch directory with the command:
<source lang="bash">nia-login07:~$ sbatch openmp_ex.sh</source>
<source lang="bash">nia-login07:scratch$ sbatch openmp_job.sh</source>
* First line indicates that this is a bash script.
* First line indicates that this is a bash script.
* Lines starting with <code>#SBATCH</code> go to SLURM.
* Lines starting with <code>#SBATCH</code> go to SLURM.
Line 735: Line 482:
* 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>.


= Monitoring queued jobs = <!--T:92-->
== Monitoring queued jobs == <!--T:92-->


<!--T:93-->
<!--T:93-->
Line 743: Line 490:
<ul>
<ul>
<li><p><code>squeue</code> or <code>sqc</code> (a caching version of squeue) to show the job queue (<code>squeue -u $USER</code> for just your jobs);</p></li>
<li><p><code>squeue</code> or <code>sqc</code> (a caching version of squeue) to show the job queue (<code>squeue -u $USER</code> for just your jobs);</p></li>
<li><p><code>qsum</code> shows a summary of qudue by user
<li><code>qsum</code> shows a summary of qudue by user
<li><p><code>squeue -j JOBID</code> to get information on a specific job</p>
<li><code>squeue -j JOBID</code> to get information on a specific job
<p>(alternatively, <code>scontrol show job JOBID</code>, which is more verbose).</p></li>
<p>(alternatively, <code>scontrol show job JOBID</code>, which is more verbose).</p></li>
<li><p><code>squeue --start -j JOBID</code> to get an estimate for when a job will run; these tend not to be very accurate predictions.</p></li>
<li><p><code>squeue --start -j JOBID</code> to get an estimate for when a job will run; these tend not to be very accurate predictions.</p></li>
<li><p><code>scancel -i JOBID</code> to cancel the job.</p></li>
<li><p><code>scancel -i JOBID</code> to cancel the job.</p></li>
<li><p><code>sinfo -pcompute</code> to look at available nodes.</p></li>
<li><p><code>jobperf JOBID</code> to get an instantaneous view of the cpu and memory usage of the nodes of the job while it is running.</p></li>
<li><p><code>jobperf JOBID</code> to get an instantaneous view of the cpu and memory usage of the nodes of the job while it is running.</p></li>
<li><p><code>sacct</code> to get information on your recent jobs.</p></li>
<li><p><code>sacct</code> to get information on your recent jobs.</p></li>
Line 754: Line 500:


<!--T:103-->
<!--T:103-->
For more information, check out the wiki page devoted to [[Running jobs]].
Further instructions for monitoring your jobs can be found on the [https://docs.scinet.utoronto.ca/index.php/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-->
Line 772: Line 518:
<!--T:207-->
<!--T:207-->
'''Support'''
'''Support'''
 
Contact our [[Technical support]]
<!--T:208-->
* support@scinet.utoronto.ca
* niagara@computecanada.ca


</translate>
</translate>

Latest revision as of 15:34, 11 July 2024

Other languages:

Specifications[edit]

The Niagara cluster is a large cluster of 1548 Lenovo SD350 servers each with 40 Intel "Skylake" cores at 2.4 GHz. The peak performance of the cluster is 3.02 PFlops delivered / 4.75 PFlops theoretical. It is the 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 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]

Access to Niagara is not enabled automatically for everyone with an Alliance account, but anyone with an active Alliance account can get their access enabled.

If you have an active Alliance account but you do not have access to Niagara yet (e.g. because you are a new user and belong to a group whose primary PI does not have an allocation as granted in the annual Alliance RAC), go to the opt-in page on the CCDB site. After clicking the "Join" button on that page, it usually takes only one or two business days for access to be granted.

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 work on Niagara. If you are not it will be worth your time to review the Linux introduction or to attend a local "Linux Shell" workshop.

As with all SciNet and Alliance compute systems, access to Niagara is done via ssh (secure shell) only. As of January 22 2022, authentication is only allowed via SSH keys. Please refer to this page to generate your SSH key pair and make sure you use them securely.

Open a terminal window (e.g. PuTTY on Windows or MobaXTerm), then ssh into the Niagara login nodes with your CC credentials:

$ ssh -i /path/to/ssh_private_key -Y MYCCUSERNAME@niagara.scinet.utoronto.ca

or

$ ssh -i /path/to/ssh_private_key -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 possibly an archive directory.

$PROJECT=/project/g/groupname/myccusername

$ARCHIVE=/archive/g/groupname/myccusername

NOTE: Currently archive space is available only via HPSS, and is not accessible on the Niagara login, compute, or datamover nodes.

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 at Niagara 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 at Niagara 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 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
  • 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:

    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 standard Alliance software stack which is available on Alliance's other clusters (including Graham, Cedar, Narval, and Beluga):

      module load CCEnv arch/avx512
      (without the arch/avx512 module, you'd get the modules for a previous generation of CPUs)

      Or, if you want the same default modules loaded as on Cedar, Graham, and Beluga, then do

      module load CCEnv arch/avx512 StdEnv/2018.3

    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. intelintel/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.

    Using 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 Alliance 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 Alliance 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 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:scratch$ sbatch jobscript.sh
      
    • This puts the job in the queue. It will run on the compute nodes in due course.

    • In most cases, you will want to submit from your $SCRATCH directory, so that the output of your compute job can be written out (as mentioned above, $HOME is read-only on the compute nodes).

    • Jobs will run under their group's RRG allocation, or, if the group has none, under a RAS allocation (previously called 'default' allocation).

    • Some example job scripts can be found below.

    Keep in mind:

    • Scheduling is by node, so in multiples of 40-cores.

    • Your job's 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.

      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 24 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 at Niagara 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]

    #!/bin/bash 
    #SBATCH --nodes=2
    #SBATCH --ntasks=80
    #SBATCH --time=1:00:00
    #SBATCH --job-name mpi_job
    #SBATCH --output=mpi_output_%j.txt
    #SBATCH --mail-type=FAIL
     
    cd $SLURM_SUBMIT_DIR
     
    module load intel/2018.2
    module load openmpi/3.1.0
     
    mpirun ./mpi_example
    # or "srun ./mpi_example"
    

    Submit this script from your scratch directory with the command:

    nia-login07:scratch$ 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 2 nodes (each of which will have 40 cores) on which to run a total of 80 tasks, for 1 hour.
      (Instead of specifying --ntasks=80, you can also ask for --ntasks-per-node=40, which amounts to the same.)
    • Note that the mpifun flag "--ppn" (processors per node) is ignored.
    • Once it found such a node, it runs the script:
      • Change to the submission directory;
      • Loads modules;
      • Runs the mpi_example application (SLURM will inform mpirun or srun on how many processes to run).
    • To use hyperthreading, just change --ntasks=80 to --ntasks=160, 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]

    #!/bin/bash
    #!/bin/bash
    #SBATCH --nodes=1
    #SBATCH --cpus-per-task=40
    #SBATCH --time=1:00:00
    #SBATCH --job-name openmp_job
    #SBATCH --output=openmp_output_%j.txt
    #SBATCH --mail-type=FAIL
     
    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 from your scratch directory with the command:

    nia-login07:scratch$ 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_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 or sqc (a caching version of squeue) to show the job queue (squeue -u $USER for just your jobs);

    • qsum shows a summary of qudue by user
    • 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.

    • 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

    Support Contact our Technical support