Niagara
Expected availability: April 2018 |
Login node: niagara.computecanada.ca |
Globus endpoint: TBA |
System Status Page: https://wiki.scinet.utoronto.ca/wiki/index.php/System_Alerts |
Niagara is a homogeneous cluster, owned by the University of Toronto and operated by SciNet, intended to enable large parallel jobs of 1040 cores and more. It was designed to optimize throughput of a range of scientific codes running at scale, energy efficiency, and network and storage performance and capacity.
The user experience on Niagara will be similar to that on Graham and Cedar, but slightly different. Specific instructions on how to use the Niagara cluster will be available in April 2018.
Niagara is an allocatable resource in the 2018 Resource Allocation Competition (RAC 2018), which comes into effect on April 4, 2018.
Niagara installation update at the SciNet User Group Meeting on February 14th, 2018
Niagara installation time-lag video
Niagara hardware specifications
- 1500 nodes, each with 40 Intel Skylake cores at 2.4GHz, for a total of 60,000 cores.
- 202 GB (188 GiB) of RAM per node.
- EDR Infiniband network in a so-called 'Dragonfly+' topology.
- 6PB of scratch, 3PB of project space (parallel filesystem: IBM Spectrum Scale, formerly known as GPFS).
- 256 TB burst buffer (Excelero + IBM Spectrum Scale).
- No local disks.
- No GPUs.
- Rpeak of 4.61 PF.
- Rmax of 3.0 PF.
- 685 kW power consumption.
Attached storage systems
Home space 600TB total volume Parallel high-performance filesystem (IBM Spectrum Scale) |
|
Scratch space 6PB total volume Parallel high-performance filesystem (IBM Spectrum Scale) |
|
Burst buffer 256TB total volume Parallel extra high-performance filesystem (Excelero+IBM Spectrum Scale) |
|
Project space 3PB total volume. Parallel high-performance filesystem (IBM Spectrum Scale |
|
Archive Space 10PB total volume High Performance Storage System (IBM HPSS) |
High-performance interconnect
The Niagara cluster has an EDR Infiniband network in a so-called 'Dragonfly+' topology, with four wings. Each wing of maximually 432 nodes (i.e., 17280) has 1-to-1 connections. Network traffic between wings is done through adaptive routing, which alleviates network congestion and yields an effective blocking of 2:1 between nodes of different wings.
Node characteristics
- CPU: 2 sockets with 20 Intel Skylake cores (2.4GHz, AVX512), for a total of 40 cores per node
- Computational performance: 3 TFlops theoretical peak.
- Network connection: 100Gb/s EDR Dragonfly+
- Memory: 202 GB (188 GiB) of RAM, i.e., a bit over 4GiB per core.
- Local disk: none. GPUs/Accelerators: none.
- Operating system: Linux CentOS 7
Scheduling
The Niagara cluster will use the Slurm scheduler to run jobs. The basic scheduling commands will therefore be similar to those for Cedar and Graham, with a few differences:
- Scheduling will be by node only. This means jobs will always need to use multiples of 40 cores per job.
- Asking for specific amounts of memory will not be necessary and is discouraged; all nodes have the same amount of memory (202GB/188GiB minus some operating system overhead).
Details, such as how to request burst buffer usage in jobs, are still being worked out.
Software
- Module-based software stack.
- Both the standard Compute Canada software stack as well as cluster-specific software tuned for Niagara will be available.
- In contrast with Cedar and Graham, no modules will be loaded by default to prevent accidental conflicts in versions. There will be a simple mechanism to load the software stack that a user would see on Graham and Cedar.
Migration to Niagara
Migration for Existing Users of the GPC
- Accounts, $HOME & $PROJECT of active GPC users transferred to Niagara (except dot-files in ~).
- Data stored in $SCRATCH will not be transfered automatically.
- Users are to clean up $SCRATCH on the GPC as much as possible (remember it's temporary data!). Then they can transfer what they need using datamover nodes. Let us know if you need help.
- 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 no later than May 9, 2018.
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.
Using Niagara (Quickstart)
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
or
$ ssh -Y MYCCUSERNAME@niagara.computecanada.ca
- The Niagara login nodes are where you develop, edit, compile, prepare and submit jobs.
- These login nodes are not part of the Niagara compute cluster, but have the same architecture, operating system, and software stack.
- The optional
-Y
is needed to open windows from the Niagara command-line onto your local X server. - To run on Niagara's compute nodes, you must submit a batch job.
Storage Systems and Locations
Home and scratch
You have a home and scratch directory on the system, whose locations will be given by
$HOME=/home/g/groupname/myccusername
$SCRATCH=/scratch/g/groupname/myccusername
nia-login07:~$ pwd
/home/s/scinet/rzon
nia-login07:~$ cd $SCRATCH
nia-login07:rzon$ pwd
/scratch/s/scinet/rzon
Project location
Users from groups with a RAC allocation will also have a project directory.
$PROJECT=/project/g/groupname/myccusername
IMPORTANT: Future-proof your scripts
Use the environment variables (HOME, SCRATCH, PROJECT) instead of the actual paths! The paths may change in the future.
Storage Limits on Niagara
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.
$BBUFFER
stands for the Burst Buffer, a functionality that is still being set up. This will be a faster parallel storage tier for temporary data.
Moving data
Move amounts less than 10GB through the login nodes.
- Only Niagara login nodes visible from outside SciNet.
- Use scp or rsync to niagara.scinet.utoronto.ca or niagara.computecanada.ca (no difference).
- This will time out for amounts larger than about 10GB.
Move amounts larger than 10GB through the datamover node.
- From a Niagara login node, ssh to
nia-datamover1
. - Transfers must originate from this datamover.
- The other side (e.g. your machine) must be reachable from the outside.
- If you do this often, consider using Globus, a web-based tool for data transfer.
Moving data to HPSS/Archive/Nearline using the scheduler.
- HPSS is a tape-based storage solution, and is SciNet's nearline a.k.a. archive facility.
- Storage space on HPSS is allocated through the annual Compute Canada RAC allocation.
Software and Libraries
Modules
Once you are on one of the login nodes, what software is already installed?
- Other than essentials, all installed software is made available using module commands.
- These set environment variables (
PATH
, etc.) - Allows multiple, conflicting versions of a given package to be available.
- module spider shows the available software.
nia-login07:~$ 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
...
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:
A Niagara software stack tuned and compiled for this machine. This stack is available by default, but if not, can be reloaded with
module load NiaEnv
The same software stack available on Compute Canada's General Purpose clusters Graham and Cedar, compiled (for now) for a previous generation of CPUs:
module load CCEnv
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.
intel
→intel/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.
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).
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
------------------------------------------------------------------------------------------------------
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
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
Where:
S: Module is Sticky, requires --force to unload or purge
Can I Run 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
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
main.c module.c
nia-login07:~$ icc -c -O3 -xHost -o main.o main.c
nia-login07:~$ icc -c -O3 -xHost -o module.o module.c
nia-login07:~$ icc -o main module.o main.o -lgsl -mkl
nia-login07:~$ ./main
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 commandnia-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.
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.
Example submission script (OpenMP)
#!/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
cd $SLURM_SUBMIT_DIR
module load intel/2018.2
export OMP_NUM_THREADS=$SLURM_CPUS_PER_TASK
./openmp_example
# or "srun ./openmp_example".
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.
Example submission script (MPI)
#!/bin/bash
#SBATCH --nodes=8
#SBATCH --ntasks=320
#SBATCH --time=1:00:00
#SBATCH --job-name mpi_job
#SBATCH --output=mpi_output_%j.txt
cd $SLURM_SUBMIT_DIR
module load intel/2018.2
module load openmpi/3.1.0rc3
mpirun ./mpi_example
# or "srun ./mpi_example"
nia-login07:~$ 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.
Monitoring queued jobs
Once the job is incorporated into the queue, there are some command you can use to monitor its progress.
squeue
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 -j JOBID -o "%.9i %.9P %.8j %.8u %.2t %.10M %.6D %S"
to get an estimate for when a job will run.scancel -i JOBID
to cancel the job.sinfo -pcompute
to look at available nodes.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.
- Burst buffer (to come) is better for i/o heavy jobs and to speed up checkpoints.