Become part of a global super-computer network for astronomy research

February 2022

Distributed volunteer cloud computing for science research and other purposes has been around for a decade or two now. You can donate your computer's spare CPU/GPU time (and part of your electricity bill and carbon footprint) to science research by installing an application that receives tasks from a central server (usually maintained by a university or research organisation), which then computes the results on your PC before sending it back.

When thousands of volunteers globally donate their computer power to these projects, they create distributed super-computers of significant capability.

You can control how much of your computer's resources are dedicated to the task, and most software for these kinds of projects allows you to automatically stop processing research tasks when you need to use the computer for your own tasks.

I use the BOINC client (available for PC, Mac and Linux), which lets you choose from a variety of distributed computing projects.

I participate in the following astronomy projects:

MilkyWay@Home – “creating a highly accurate three dimensional model of the Milky Way galaxy ... which provides knowledge about how the Milky Way galaxy was formed and how tidal tails are created when galaxies merge”.

Einstein@Home – “searching for weak astrophysical signals from spinning neutron stars (often called pulsars) using data from the LIGO gravitational-wave detectors, the Arecibo radio telescope, and the Fermi gamma-ray satellite ... volunteers have already discovered about fifty new neutron stars, and we hope to find many more”.

In a recent research release, the MilkyWay@home volunteer supercomputer was used to determine the shape and dark matter content of an ultrafaint dwarf galaxy:

I find it rewarding to think I contributed to this and other recent discoveries in some small way.

I have dedicated an old PC to the task, which I leave running 24/7, using the BOINC client (but you can easily use your day-to-day PC for the task, with minimal disruption to your normal PC use) . The electricity cost in Melbourne, Australia, running an old 8-core i7 with a GTX 780 GPU, at 90% full CPU load (throttled down by 10% to keep the thermal levels lower), is working out to about $1/day. The carbon footprint is something to consider, but I believe I can make up for this impact by running my air conditioner and heater a bit less, and making extra sure I turn off lights in rooms when I don't need them. Anyone living where renewable energy is available can contribute with essentially zero energy costs and zero emissions.

Energy usage may be especially efficient during winter if you live in colder climates, as every watt of CPU/GPU energy turns into about a watt of heat energy. So your PC will contribute to heating your home using the same energy you contribute to science research.

Ashley Flynn – Games and Simulations Software Engineer Portfolio and contact –

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