Introduction#
BOINC (Berkeley Open Infrastructure for Network Computing) is an open network computing platform used for volunteer computing and grid computing. BOINC was originally developed to support SETI@home and has since become the most mainstream distributed computing platform used in various disciplines such as mathematics, physics, chemistry, life sciences, and earth sciences. The development of BOINC aims to help researchers conveniently access the computing resources of volunteers distributed around the world. Many research institutions lack funding, but many scientific research projects require significant computational power. Therefore, distributed computing is used to process large amounts of data, and the computational power contributed by users is used to calculate projects in mathematics, physics, chemistry, life sciences, and earth sciences.
Tutorial#
First, open https://boinc.berkeley.edu/download.php to download and install.
It is recommended to download the version with VirtualBox, as some projects require it.
After installation, the startup interface looks like this:
It is recommended to switch to the advanced interface for easier modification of settings.
To run BOINC, you need to join a project first.
After clicking, you will see various projects with descriptions. If they are in English, you can copy and translate them.
Although you can create an account by clicking "Next," I recommend clicking the website link to register on the webpage, where you can modify your information.
Most registration pages look like the image below. Some websites use recaptcha, so you may need software like steam++ to assist with access.
After completing the registration, go back to BOINC, add the project, and select "I have already registered."
Finally, click "Finish."
You can join my team at https://arkarchive.org/boinc.html
Recommendations#
Using the CPU has lower efficiency, so it is recommended to only use the GPU. You can modify the computational parameters on the website to the following:
After testing, it was found that running PrimeGrid with an AMD graphics card does not affect transcoding speed and does not significantly increase power consumption. However, calling CUDA with nVidia will affect transcoding speed.
However, only the majority of astronomical, physical, and mathematical projects support GPU acceleration. Except for the gpugrid project, other projects in the field of biology do not support GPU acceleration.
Others#
Some projects can be used to earn (or lose) money with BOINC, even not enough to cover electricity costs. If you want to make money, it is not recommended to try. However, if you want to share computing power, you can refer to the next tutorial in this series.