Distributed Computing Basics: What Are BOINC & Folding At Home?

By Published August 12, 2017 at 9:00 pm

Computers have come a long way since their inception. Some of the first computers (built by the military) used electromagnets to calculate torpedo trajectories. Since then, computers have become almost incomprehensibly more powerful and accessible to the point at which the concept of virtual reality headsets aren’t even science fiction.

In gaming PCs, these power increases have often been used to ensure higher FPS, faster game mechanics, and more immersive graphics settings. Despite this, the computational power in modern PCs can be used for a variety of applications. Many uses such as design, communication, servers, etc. are well known, but one lesser known use is contributing to distributed computation programs such as BOINC and Folding@Home.

BOINC (Berkeley Open Infrastructure for Network Computing) and Folding@home (also sometimes referred to as FAH and F@H) are research programs that utilize distributed computing to provide researchers large amounts of computational power without the need of supercomputers. BOINC allows for users to support a variety of programs (including searching for extraterrestrial life, simulating molecular simulations, predicting the climate, etc.). In contrast, Folding@home is run by Stanford and is a singular program that simulates protein folding.

First we’ll discuss what distributed computing is (and its relation to traditional supercomputers), then we’ll cover some noteable projects we’re fond of.


How Distributed Computing Works

Scientists normally use supercomputers to simulate and analyze a variety of situations pertaining to protein folding, protons colliding in CERN, universe expansion, theoretical astrophysics, and so on. This would normally entail buying, maintaining, and running massive supercomputers. In the last ~15 years though, distributed computing programs have seen moderate to substantial success. Rather than rely upon traditional supercomputers, researchers split up the tasks to be done and send each (relatively small) job to volunteer PCs for remote computation, at which point the job is sent back to a central server. The server splits up, assigns, and collects work units.

Despite the idea of people contributing their PC – and electricity – for free possibly sounding idealistic, it’s actually common and effective. From about 2007 to 2011, the Folding@home network was more powerful than the fastest supercomputer in the world in x86 TFLOPS. Currently it isn’t the most powerful, but Stanford recently announced that the F@H network is approaching 100 PFLOPS – an impressive milestone.

Folding@home focuses on protein folding whereas BOINC is simply an open framework that any researcher can utilize, so there is a variety of projects to contribute to.

Stanford’s Folding@home

In living organisms, proteins help to digest food, kill viruses, regulate mood, and perform a ton of functions in the human body on the small scale. In order to perform these incredibly important functions -- we’d die without them, after all -- proteins have to fold and unfold correctly. Unfortunately, sometimes proteins misfold. This doesn’t always cause problems, but can cause illnesses such as cancer, Alzheimer’s, Huntington’s, Parkinson's, and more.


By simulating how proteins fold and misfold, Folding@Home enables researchers to better understand how and why proteins misfold, which is essential for creating treatments of the illnesses caused by misfolding.


BOINC Projects


Starting off with a project sufficiently sci-fi esque, we have SETI@home. Run by UC Berkeley, SETI@home analyzes radio signals from space to search for signs of intelligent extraterrestrial life. Currently, no proof of extraterrestrial life has been discovered, but that doesn’t stop it from being one of the most prominent – and ambitious – BOINC projects.



Climateprediction.net is a more down to Earth project that is meant to better understand and reduce uncertainty in climate modeling. This allows researchers to better understand weather patterns and how the climate is affected by humans and natural processes.


Similar to Folding@home, Rosetta@home aims to better humanity’s understanding of proteins. The project differs in that Rosetta@home focuses more on predicting protein design, structure, and docking rather than the process of protein folding. Folding@home and Rosetta@home actually complement each other well as projects since they oftentimes verify the other’s results, and both provide information and knowledge the other project can use to improve.


The large hadron collider (LHC) at CERN is an incredibly complex machine utilized for high-speed particle collisions in order to study particle physics. LHC@home is run by CERN in order to simulate particle collisions to provide reference measurements for real-world tests by the LHC. In addition, there is LHC@home Sixtrack which runs simulations in order to better upgrade and maintain the LHC.

Closing Words

In recent years, advances in personal computers and the development of distributed computing have allowed for normal people to easily contribute to projects that better humanity’s understanding of climate, physics, the universe, and biology. The projects listed above are but some of the available projects anyone can contribute to (many others are listed here by BOINC). Because BOINC and F@H can be set to only compute when the computer is idle, they don’t even affect day-to-day usage.

Ultimately, contributing to projects such as these is an easy way for anyone to make a difference – however small it may be – in society’s understanding of physics, illnesses, the universe, and science overall.

- Michael Kerns

Last modified on August 12, 2017 at 9:00 pm
Michael Kerns

Michael Kerns first found us when GN's Editor-in-Chief was tirelessly answering questions on reddit pertaining to a new product launch, likely after the Editor had stayed up all night writing the news post. Michael offered a tired Editor reprieve, taking over the role of questions-answerer-extraordinaire when it was most needed. These days, Michael can be found pulling his mechanical keyboard collection apart and building Frankenstein's Monster-like monsters of keyboards. Michael wrote the vast majority of our mechanical keyboard dictionary and is an expert in keyboards.


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