12 December 2015

12 December 2015

Farm status
Parallella's and Pi's are crunching Einstein work

The Intel-GPU machines are crunching Seti work overnight, only because its too hot during the day.

The Nvida-GPU machines are off.

As you'd know from reading my blog I have a "farm" of machines that currently are running BOINC to do the task scheduling. I had an idea that rather than running BOINC on each machine, why not run it on one machine and have it use MPI to communicate with the others and run tasks that way. If other people are interested in this idea then lets talk.

To that end I was following the instructions from the University of Southampton in setting up an MPI cluster using my redundant Raspberry Pi B models. The details about their Lego Supercomputer can be found Here. In the end it was still compiling the MPI software after some hours, despite the fact that I overclocked the Pi in question to 1Ghz. I gave up and went to bed. I will have to kick it off when I have plenty of time to waste seeing as it takes so long on the old B model.

The idea is that one would replace the BOINC API calls with MPI calls. Each app runs stand-alone, which most science apps seem to be written to do anyway, and then just passes the result files back for the BOINC client to handle. A better solution would be to have both sets of code and then the app can work via MPI or the BOINC API.

The BOINC client would need to be updated to check the status of worker machines and give tasks to the worker machines as needed. Exactly what a real compute cluster does, only BOINC is doing the scheduling and still handling the file transfers, etc.

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