Edit: Did any of you contribute spare cycles?
Originally posted May 19, 2020 on AIXchange
Alternatives to running SETI@home.
Many years ago as a young-ish administrator, I ran SETI@home. There were clients for different operating systems, including AIX. It was easy to see how different processors affected the speed of completing work units.
As of March 30, SETI@home no longer sends data for clients to work on, but if you still enjoy using your spare machines, or have considered setting up a spare machine for distributed computing like this, they suggest some alternatives:
“… we encourage you to continue donate computing power to science research—in particular, research on the COVID-19 virus. The best way to do this is to join Science United and check the Biology and Medicine box.”
As noted on the Science United site:
“BOINC is the preeminent platform for volunteer computing (VC). It is used by most VC projects, including SETI@home, Einstein@home, Climateprediction.net, IBM World Community Grid, and Rosetta@home.
“Science United is a new way to participate in BOINC. With Science United, computer owners volunteer for science areas rather than for specific projects. Science United assigns computers to appropriate projects; these assignments may change over time.
“We call this the coordinated model for VC. It has the advantage that new projects can get computing power without having to do their own publicity and volunteer recruitment. The goal is to provide the power of VC to thousands of scientists, rather than a few dozen as was previously the case. …
“The user interface of Science United is designed to appeal to a wider audience than the current BOINC user base, which is mostly male and tech-savvy. For example, Science United has no leader boards. …
“Science United is also intended to serve as a unified “brand” for VC, so that it can be marketed more effectively.”
Another project, Folding@home, does similar work with spare cycles:
“What is distributed computing?… the calculations we wanted to do would take about a million days on a fast processor. So it seemed natural that we might be able to get it done in 10 days if we had access to 100,000 processors. By using distributed computing, we can split up the simulation, run each piece through a computer, and then combine them together afterwards. This really sped up our results.”
If you’ve ever wondered what you can do to help, this is something to consider.