[Mesa-users] Question about running many similar simulations on a cluster

[Aaron Dotter]

Hi Connor,

MESA V (https://ui.adsabs.harvard.edu/abs/2019ApJS..243...10P/abstract) has
a discussion devoted to the scaling of MESA simulations with the number of
cores.  The long and short of it is that if you are using a smaller nuclear
network, you are probably better off using ~4 cores and running more
individual jobs at once than using more cores and fewer jobs.  Assuming of
course that you have enough RAM on each node to run, say, 5 jobs at once.

I don't know how other people do this but I create a new directory for each
job when running on a cluster.  That directory contains the unique inlist
file as well as unique output.

Hope this helps.

Aaron

On Sun, Oct 24, 2021 at 7:06 PM Connor Jennings <cjennings2023 at berkeley.edu>
wrote:

> Hello,
> My name is Connor Jennings. I'm a student at UC Berkeley using MESA in a
> research project. I want to run a lot MESA (I'm using version r15140)
> simulations for RR Lyrae stars on the Savio cluster (which runs on Linux)
> here at Berkeley, and I have a few questions about the best way to do this.
> Our plan is to generate a grid of initial parameters, and then run a
> simulation for each space on the grid so we can run each simulation in
> parallel. My current understanding is that we would have to create a new
> folder for each simulation, even though the only thing different in the
> folders would be a few lines in the inlist file. Is there a more efficient
> way to do this, or do we expect to need to create 1000 folders for 1000
> simulations, etc. ?
> Additionally, Savio has the ability to run multiple programs on the same
> node, so I am wondering how MESA's speed scales with its number of cores.
> I.e. If I have access to two nodes each with 20 cores each and need to run
> 10 simulations, would it be faster to run 1 simulation on each node using
> all 20 cores, and do that 5 times, or to run 5 simulations per node using 4
> cores each and do that once?
> Thank You,
> Connor Jennings
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