Spencer Lyon

# HPC

· by Spencer Lyon · Read in about 6 min · (1075 Words)
tips HPC computing

# Julia and mercer

Here are some tips, tricks I’ve picked up for working with Julia on NYUs super computer.

## Installing Julia

I have a shell script that I periodically run to download the latest released version of Julia:

#!/usr/bin/env sh

wget -O julia_binary.tar.gz https://julialang.s3.amazonaws.com/bin/linux/x64/0.4/julia-0.4-latest-linux-x86_64.tar.gz

rm -rf $WORK/src/julia* mkdir -p$WORK/src/julia
tar -C $WORK/src/julia -zxf julia_binary.tar.gz --strip-components=1 rm julia_binary.tar.gz # prepend julia to path export PATH=$WORK/src/julia/bin:$PATH # remove old symlink and make a new one mkdir$WORK/bin
rm -f $WORK/bin/julia ln -s$WORK/src/julia/bin/julia $WORK/bin/julia  I put this in a file $WORK/bin/update_julia, then whenever I need to update my julia installation I do bash $WORK/bin/update_julia. This script will put the Julia binary in $WORK/bin/julia (that’s what I enter to run Julia.)

## Installing specific packages

Most packages are installable using either Pkg.clone or Pkg.add. However, some require extra setup.

Here are specailized instructions for installing specific packages.

### HDF5.jl

I first tried Pkg.add("HDF5"). That didn’t work. The problem is that I don’t have access to a package manager on mercer, so I need to link against libhdf5 that is already on mercer.

I tracked down the shared library on mercer and found that it was at the following location (NOTE: you might want to check it there are more recent versions available):

/share/apps/hdf5/1.8.14/openmpi/intel/lib/libhdf5.so.9.

Then I edited $HOME/.julia/v0.4/HDF5/deps/deps.jl to look like this: # This is an auto-generated file; do not edit # Pre-hooks # Macro to load a library macro checked_lib(libname, path) ((VERSION >= v"0.4.0-dev+3844" ? Base.Libdl.dlopen_e : Base.dlopen_e)(path) == C_NULL) && error("Unable to load \n\n$libname ($path)\n\nPlease re-run Pkg.build(package), and restart Julia.") quote const$(esc(libname)) = $path end end # Load dependencies @checked_lib libhdf5 "/share/apps/hdf5/1.8.14/openmpi/intel/lib/libhdf5.so.9" # Load-hooks  You might need to create both the HDF5/deps folder and the file deps.jl. You should now be able to start a Julia session and run using HDF5 and it will work without a problem. You do not need to run Pkg.build("HDF5") after updating deps.jl ### MbedTLS.jl If you need to install MbedTLS.jl or if it is a dependency of something else you need to install, you will probably see an error about cmake not being available when you do Pkg.add("MbedTLS"). The fix here is to simply run module load cmake at the shell prompt, then start Julia in that same session, and try Pkg.add("MbedTLS") or Pkg.build("MbedTLS") again (run Pkg.build if you already tried Pkg.add and it failed). # Mercer tips/tricks • Three steps to check CPU utilization of a running job. 1. See what nodes your job is running on by executing qstat -at -u$USER -n -1,
2. Run ssh X where X is the name of the node from the previous command. Note that you can do this from the login node on mercer
3. Once on the compute node run htop -u $USER # MPI jobs I got this script from here NOTE: if you are using Julia with multiple processors, skip this section and move to the next one. #!/bin/sh ############################################################################## # IMPORTANT: the next line determines how many nodes to run on # nodes is number of nodes, ppn= processors (cores) per node #PBS -l nodes=2:ppn=4 # # Make sure that we are in the same subdirectory as where the qsub command # is issued. # cd$PBS_O_WORKDIR
#
#  make a list of allocated nodes(cores)
#  Note that if multiple jobs run in same directory, use different names
#     for example, add on jobid nmber.
cat $PBS_NODEFILE > nodes # How many cores total do we have? NO_OF_CORES=cat$PBS_NODEFILE | egrep -v '^#'\|'^$' | wc -l | awk '{print$1}'
NODE_LIST=cat $PBS_NODEFILE  # # Just for kicks, see which nodes we got. echo$NODE_LIST
#
# Run the executable. *DO NOT PUT* a '&' at the end!!
#
mpirun -np $NO_OF_CORES -machinefile nodes ./pi3 >& log # #########################################  The following also looked like good resources: ## Julia on a cluster I can’t just do julia -p N or addprocs(N) to get it to work. That would give me N procs on the login node. What I need instead is to use the machinefile option for starting Julia and give it the $PBS_NODEFILE. This is an example of a PBS script I had that worked:

#PBS -l nodes=1:ppn=20
#PBS -l walltime=10:00:00
#PBS -N gerzensee
#PBS -M spencer.lyon@nyu.edu
#PBS -m abe
#PBS -j oe
#PBS -t 1,9

module purge

# this moves us to the directory where qsub was submitted
# should be $WORK/Research/Gerzesee/Code/international cd$PBS_O_WORKDIR

# cat $PBS_NODEFILE | sed -e 's/.local$/-ib.ibnet/' > my_machines
# cat $PBS_NODEFILE > my_machines # run the code! -- use machinefile to start one julia on each process /work/sgl290/bin/julia --machinefile$PBS_NODEFILE driver.jl


In this example I started two jobs (with PBS_ARRAYID equal to 1 and 9). Each job used 20 cores on one node for 10 hours. The path /work/sgl290/bin/julia is the path that was set up for me by running the shell script from above.

In this example driver.jl looked like this:

include("main.jl")
using JLD

for i in workers()
remotecall_fetch(i, include, "main.jl")
end

# set up arguments
model_id = parse(Int, get(ENV["PBS_ARRAYID"], "1"))

# CODE TO DO THE WORK USING using all the cores.


There are a few things to point out about this code. First main.jl is a file that collects all the code I will be running. I first call include("main.jl") and then go through all the workers and call remotecall_fetch(i, include, "main.jl") to load it on each process. I do it this way for a few reasons:

• Loading is only on the master process first allows all precompilation to take place without multiple processes trying to write the same .ji files at the same time
• I include the file sequentially on all workers again so that no worker steps on another worker’s toes.

I then extract an integer model_id that specifies which job is currently running. This number corresponds to the job number from the pbs script (integers 1 and 9 in the example above). I use this to drive which parameterization I am working with.

The comment at the end is simply there as a placeholder for you to put the code that actually does the work.

# Sharing folders

To share a folder /scratch/sgl290/awesomeness with user abc123 I would need to enter the following commands on mercer:

setfacl -m u:abc123:rx /scratch/sgl290
setfacl -Rm u:abc123:rwx,d:u:abc123:rwx /scratch/sgl290/awesomeness


The first command gives read and execute permissions to my scratch folder – necessary for letting them enter the folder and it’s children.

The second command gives him read, write, exceute permissions to the awesomeness folder all sub files/folders.