From CommunityData

Note Note: This page is intended to replace the main CommunityData:Hyak page in the near future. This is a part of our transition to the new Slurm-based job scheduler. Some of the sections may be incomplete, and the instructions may not work. Feel free to edit and fix the content that is incorrect/out-of-date.

To use Hyak, you must first have a UW NetID, access to Hyak, and a two factor authentication token. Details on getting set up with all three are available at CommunityData:Hyak setup.

There are a number of other sources of documentation:

Setting up SSH

When you connect to SSH, it will ask you for a key from your token. Typing this in every time you start a connection be a pain. One approach is to create an .ssh config file that will create a "tunnel" the first time you connect and send all subsequent connections to Hyak over that tunnel. Some details in the Hyak documentation.

I've added the following config to the file ~/.ssh/config on my laptop (you will want to change the username):

 Host hyak-mox
     User sdg1
     ControlPath ~/.ssh/master-%r@%h:%p
     ControlMaster auto
     ControlPersist yes
     Compression yes

Note Note: If your SSH connection becomes stale or disconnected (e.g., if you change networks) it may take some time for the connection to time out. Until that happens, any connections you make to hyak will silently hang. If your connections to ssh hyak are silently hanging but your Internet connection seems good, look for ssh processes running on your local machine with:

ps ax|grep hyak

If you find any, kill them with kill <PROCESSID>. Once that is done, you should have no problem connecting to Hyak.

Connecting to Hyak

To connect to Hyak, you now only need to do:

ssh hyak-mox

It will prompt you for your UWNetID's password. Once you type in your password, you will have to respond to a [2-factor authentication request].

Setting Up Hyak

When setting up Hyak, you must first add this stanza to the very bottom of your .bashrc file. Generally, you can simply edit the following file on Hyak: ~/.bashrc

## START hyak-cdsc specific options -- BOTTOM OF FILE
source /etc/profile.d/
alias big_machine='srun -p mako -A mako --mem=200G --time=500:00:00 --pty bash -l'
alias any_machine='srun -p mako -A mako --mem=100G --time=500:00:00 --pty bash -l'
alias build_machine='srun -p build --mem=100G --time=2:00:00 --pty bash -l'
alias queue_state='squeue -p mako'
module load pandoc/2.2.1
module load R/3.5.0
umask 007
## END hyak-cdsc specific options -- BOTTOM OF FILE

The final line is particularly important. If you do not do this, the files you create on Hyak will be able to be read or written by others in the group!

I also add these two lines to my Hyak .ssh/config:

ForwardX11 yes
ForwardX11Trusted yes

These lines will mean that if I have "checked out" an interactive machine, I can ssh from my computer to Hyak and then directly through an addition hop to the machine (like ssh n0652). Those ForwardX11 lines means if I graph things on this window, they will open on my local display.

Moving files from ikt to mox

You can copy files at high speed without a password between the Hyak systems using commands like the ones below (instructions from the Hyak documentation).

From ikt to mox

   ikt1$ hyakbbcp myfile
   ikt1$ hyakbbcp -r mydirectory

From mox to ikt

   mox1$ hyakbbcp myfile
   mox1$ hyakbbcp -r mydirectory

Once you do this, you will need to restart bash. This can be done simply by logging out and then logging back in or by restarting bash with the command exec bash.

Running Jobs on Hyak

When you first log in to Hyak, you will be on a "login node". These are nodes that have access to the Internet, and can be used to update code, move files around, etc. They should not be used for computationally intensive tasks. To actually run jobs, there are a few different options, described in detail in the Hyak User documentation. Following are basic instructions for some common use cases.

Interactive nodes

Interactive nodes are systems where you get a bash shell from which you can run your code. This mode of operation is conceptually similar to running your code on your own computer, the difference being that you have access to much more CPU and memory. To check out an interactive node, run the big_machine or any_machine command from your login shell. Before running these commands, you will want to be in a tmux or screen session so that you can start your job, and log off without having to worry about your job getting terminated.

Note Note: At a given point of time, unless you are using the ckpt (formerly the bf) queue, you can have one instance of big_machine and three instances of any_machine running at the same time. You may need to coordinate over IRC if you need to use a specific node for any reason.

Killing jobs on compute nodes

The Slurm scheduler provides a command called scancel to terminate jobs. For example, you might run queue_state from a login node to figure out the ID number for your job (let's say it's 12345), then run scancel --signal=TERM 12345 to send a SIGTERM signal or scancel --signal=KILL 12345 to send a SIGKILL signal that will bring job 12345 to an end.

Parallel R

The nodes on Hyak have 28 CPU cores. These may help in speeding up your analysis significantly. If you are using R functions such as lapply, there are parallelized equivalents (e.g. mclappy) which can take advantage of all the cores and give you a 2800% boost! However, something to be aware of here is your code's memory requirement—if you are running 28 processes in parallel, your memory needs can also go up to 28x, which may be more than the ~200GB that the big_machine node will have. In such cases, you may want to dial down the number of CPU cores being used—a way to do that globally in your code is to run the following snippet of code before calling any of the parallelized functions.

options(mc.cores=20)  ## tell the mc* functions to use 20 cores unless otherwise specified

More information on parallelizing your R code can be found in the parallel package documentation.

Jupyter Notebook on Hyak

Set up a password for Jupyter Notebook on Hyak

Working on Hyak from a local emacs client

Custom software in Hyak

R packages

To install a R package that's not available globally, you can check out a build node, and install the package locally. Here's how to do it:

$ build_machine
$ R

This will start R, where you can install a package in the usual way. The build node has access to the Internet, so it will be able to download the required source packages, etc.

> install.packages('lme4')

Python Packages

Custom modules

Software on Hyak can be outdated, or in some cases, not available at all. In some of these situations, it may be possible to use environment modules to install and run software without necessitating administrative (root) privileges. For example, it is possible to have and run the newest version of R that is installed in a central, shared directory, and it is even possible to have multiple versions of R available in parallel. The following subsection shows how to do this. Ordinarily, this should not be necessary on a day-to-day basis.

Installing and making available a custom module

Note Note: If you are using screen to run and manage your builds, keep in mind that screen drops a few environment variables such as LD_LIBRARY_PATH, which may mess up your build process. You should check that all the relevant environment variables are set before starting your build.

The first step toward installing and making available a custom module (in this case, R 3.5.0) is to spin up the build node, download R, compile it with a specific prefix, and install it.

$ build_machine
$ module load contrib/texlive/2017  # loads the texlive module that is helpful for generating R documentation
$ module load contrib/openblas/0.2.20  # loads the openblas library, which speeds up some R operations significantly
$ wget
$ tar xzvf R-3.5.0.tar.gz
$ cd R-3.5.0
$ ./configure --prefix=/gscratch/mako/modules/sw/R/3.5.0  --with-x --enable-R-shlib --with-lapack --with-blas="-L/sw/contrib/openblas/0.2.20/lib -lopenblas"
$ make
$ make install

The --prefix option to ./configure tells the build scripts that R is going to be installed in /gscratch/mako/modules/sw/R/3.5.0. This follows a convention that we picked—software in modules should go into /gscratch/mako/modules/sw/{SOFTWARE_NAME}/{SOFTWARE_VERSION}. The --prefix option is the most important flag for ./configure—any other flag or option will be specific to the software being installed.

The second step is to write a modulefile. This contains the metadata about our module. Edit the file /gscratch/mako/modules/modulefiles/R/3.5.0 to contain the following

proc ModulesHelp { } {
        puts stderr "\tModule providing R 3.5.0."

module-whatis "Module providing R 3.5.0."

module load contrib/openblas/0.2.20
prepend-path    PATH            /gscratch/mako/modules/sw/R/3.5.0/bin
prepend-path    MANPATH         /gscratch/mako/modules/sw/R/3.5.0/share/man

# The following line prevents everyone from installing libraries in the global namespace
file mkdir ~/R/x86_64-pc-linux-gnu-library/3.5

Note that the filename follows a similar convention as --prefix earlier (/gscratch/mako/modules/modulefiles/{SOFTWARE_NAME}/{SOFTWARE_VERSION}). This file sets up the PATH and MANPATH environment variables appropriately so that the specified version of R can be accessed and run as needed. There are many more directives that can go into the modulefile—see man modulefile for details on those directives.

Once this file is written out, the module avail command should list R/3.5.0 as an available module. This is because the module system is set up to look inside /gscratch/mako/modules/modulefiles for module files, thanks to the MODULEPATH variable that is set through .bashrc. The command module load R/3.5.0 should make R available and ready for use. To avoid running module load R/3.5.0 whenever you log in, you can add the command at the end of your .bashrc file (after the section that sets MODULEPATH).