== Getting an account ==

more to come...
== ssh configuration ==

You can add the following lines to `~/.ssh/config` on your local machine:
{{{
#!sh
Host frontera.tacc.utexas.edu frontera
     HostName frontera.tacc.utexas.edu
     User YOURUSERNAME
}}}
and replace `YOURUSERNAME` by your TACC username.

Make sure to also include the following in your `~/.ssh/config`:
{{{
#!sh
Host *
   ControlMaster auto
   ControlPath ~/.ssh/sockets/%r@%h-%p
   ControlPersist yes
}}}

It will allow you to use existing ssh connection for multiple sessions. As long as you have an active connection, ssh will not need a password or token to create a new session. You may need to `mkdir ~/.ssh/sockets` if this directory does not exist.


Once this is done, you can ssh frontera by simply doing:
{{{
#!sh
ssh frontera
}}}


== Environment ==

On frontera, add the following lines to `~/.bash_login`:
{{{
#!sh
export ISSM_DIR=PATHTOTRUNK
source $ISSM_DIR/etc/environment.sh
module load petsc/3.15
}}}

''Log out and log back in'' to apply this change.

== Installing ISSM on frontera ==

frontera will ''only'' be used to run the code, you will use your local machine for pre and post processing, you will never use frontera's matlab. You can check out ISSM and install the following packages:
 - m1qn3

Use the following configuration script (adapt to your needs):

{{{
#!sh
./configure \
   --prefix=$ISSM_DIR \
   --with-wrappers=no \
   --with-mpi-include="$TACC_IMPI_INC" \
   --with-mpi-libflags="-L$TACC_IMPI_LIB/release_mt -lmpi" \
   --with-petsc-dir="$TACC_PETSC_DIR" \
   --with-petsc-arch=$ISSM_ARCH \
   --with-metis-dir="$TACC_PETSC_DIR/$PETSC_ARCH" \
   --with-mkl-libflags="-L$TACC_MKL_LIB -mkl=parallel" \
   --with-mumps-dir="$TACC_PETSC_DIR/$PETSC_ARCH" \
   --with-scalapack-dir="$TACC_PETSC_DIR/$PETSC_ARCH" \
   --with-m1qn3-dir="$ISSM_DIR/externalpackages/m1qn3/install" \
   --enable-debugging \
   --enable-development
}}}

== Installing ISSM with Matlab on frontera ==

If you want to use frontera to process the model after running it and keep the data  on frontera, you can install ISSM with Matlab interface. Before doing the following steps, you should check with TACC to make sure you have the access to Matlab on frontera, see: https://docs.tacc.utexas.edu/software/matlab/


You can check out ISSM and install the following packages:
 - triangle
 - m1qn3

You will need to use interactive mode to compile ISSM with Matlab: https://docs.tacc.utexas.edu/software/idev/


Use the following configuration script (adapt to your needs):

{{{
#!sh
./configure \
   --prefix=$ISSM_DIR \
   --with-matlab-dir="/home1/apps/matlab/2023a/" \
   --with-triangle-dir=$ISSM_DIR/externalpackages/triangle/install \
   --with-mpi-include="$TACC_IMPI_INC" \
   --with-mpi-libflags="-L$TACC_IMPI_LIB/release_mt -lmpi" \
   --with-petsc-dir="$TACC_PETSC_DIR" \
   --with-petsc-arch=$ISSM_ARCH \
   --with-metis-dir="$TACC_PETSC_DIR/$PETSC_ARCH" \
   --with-mkl-libflags="-L$TACC_MKL_LIB -mkl=parallel" \
   --with-mumps-dir="$TACC_PETSC_DIR/$PETSC_ARCH" \
   --with-scalapack-dir="$TACC_PETSC_DIR/$PETSC_ARCH" \
   --with-m1qn3-dir="$ISSM_DIR/externalpackages/m1qn3/install" \
   --enable-debugging \
   --enable-development
}}}

You need to compile ISSM serially with `make install`.

Remember frontera is a remote cluster, use `matlab -nodesktop -nosplash -r "addpath $ISSM_DIR/src/m/dev; devpath;` when running Matlab.

Before downloading the `.outbin`, you will need to set
```
md.cluster.name = oshostname()
md.miscellaneous.name = the_file_name_of_outbin
```
Then, run `md=loadresultsfromcluster(md, 'runtimename', the_folder_name_in_execution)`
== frontera_settings.m ==

You have to add a file in `$ISSM_DIR/src/m` entitled `frontera_settings.m` with your personal settings on your local issm install:

{{{
#!m
cluster.login='seroussi';
cluster.codepath='/home1/03729/seroussi/trunk-jpl/bin/';
cluster.executionpath='/work/03729/seroussi/trunk-jpl/execution/';
}}}

use your username for the `login` and enter your code path and execution path. These settings will be picked up automatically by matlab when you do `md.cluster=frontera()`

Note that the `executionpath' creates temporary binary files that can be removed once the job is complete. For this reason, you can set the path to be somewhere on the $SCRATCH filesystem, which is unlimited temporary storage on frontera.


== Running jobs on frontera  ==

On frontera, each node has 56 cores and you can use any multiple of 56 for the total number of processors. The more nodes and the longer the requested time, the more you will have to wait in the queue. So choose your settings wisely:

 {{{
#!m
md.cluster=frontera('numnodes',2);
}}}

Before you run your job, make sure to have an active open ssh connection to frontera so that you don't need to enter your password.

To manually submit a job on frontera, do:
 {{{
#!m
sbatch job.queue
}}}

Now if you want to check the status of your job and the queue you are using, type in the bash with the frontera session:
 {{{
#!sh
showq -u USERNAME
}}}

You can delete your job manually by typing:
{{{
#!sh
scancel JOBID
}}}

where JOBID is the ID of your job (indicated in the Matlab session). Matlab indicates too the directory of your job where you can find the files `JOBNAME.outlog` and `JOBNAME.errlog`. The outlog file contains the informations that would appear if you were running your job on your local machine and the errlog file contains the error information in case the job encounters an error. 

== Use DeepXDE  ==
Fontera supports container by a software called `apptainer` [https://apptainer.org]. A precompiled DeepXDE image with Tensorflow v.2 backend is available at docker://chenggongdartmouth/deepxde:v1.2 or at docker://mkrish234/deepxde:v0.3 . 

You might need to build an appraiser image from the Docker image in Frontera. 
First find the path to your login node on Frontera with `pwd`. Then, allocate a compute node with the following 
{{{
idev -m 60 -p rtx -N 1 -n 8
}}}
You will need to load the `apptainer` module as follows
{{{
module load tacc-apptainer
}}}
Build the apptainer image from the Docker image as follows
{{{
apptainer build <PATH_TO_LOGIN_NODE>/deepxde docker://<DOCKER_IMAGE>
}}}

The following is an example of using DeepXDE to run a script ./test.py on Frontera (with GPU node):
{{{
#!/bin/bash

#SBATCH -J job_name           # job name
#SBATCH -o output.%j          # output file named, output.jobID
#SBATCH -e error.%j           # error file named, error.jobID
#SBATCH -p rtx                # queue name
#SBATCH -N 1                  # number of nodes requested
#SBATCH --ntasks-per-node 4   # tasks per node
#SBATCH -t 10:00:00           # time, hh:mm:ss
#SBATCH --mail-user=<EMAIL_ADDRESS>
#SBATCH --mail-type=all

module load tacc-apptainer
stdbuf -i0 -o0 -e0 apptainer exec --nv --bind ~/:/mnt ~/deepxde python -u /mnt/test.py
}}}