10 year anniversary of evolution@home
Thank you for all your CPU-time contributions. The last decade got evolution@home off the ground. The next one will make it grow.
Since evolution@home started 10 years ago, over 650 years of CPU-time have been donated by hundreds of people like you who have a computer connected to the Internet and an interest in science. The results compiled have contributed to more than five peer-reviewed publications. Thank you for making that possible!
2001 Start of evolution@home by Laurence Loewe in Germany
2002 First publication on evolution@home from a global computing point of view
2003 evolution@home moves with Laurence Loewe to the University of Edinburgh in Scotland
2006 First publication of simulation results on a population genetics question
2008 Rechenkraft BOINCyoyo joins the effort and contributes hundreds of years of computing time since then
2010 evolution@home moves with Laurence Loewe to the Evolutionary Systems Biology Group at the University of Wisconsin-Madison in the USA
2011 evolution@home team is forming in Madison in the EvoSysBio Group, infrastructure development picks up pace
There is lots of work to do in developing evolution@home! Here in Madison we are in the process of building the foundation for an infrastructure that will make it much easier to explore by simulation how biological systems change over time. This is a huge effort that has many aspects and needs the contributions of a wide range of disciplines from biology over math to computer science. Accordingly, people in the evolution@home team have very diverse backgrounds. Currently, we are building interfaces that make it easy to integrate this diverse expertise into a single system.
Tangible projects: After numerous requests and a long waiting time we have finally made progress with porting the currently active evolution@home Simulator005 to Linux and modern versions of Mac OSX. We plan to release this soon, thanks to the heroic battles of Matt Myers with intricate details of how compilers have changed their interpretation of C++ in the last 10 years. While this change will not look like much on the outside, it is a huge step forward, as the code is now working on the modern compilers that have taken the place of the famous Codewarrior tools. Stay tuned for the update.
Data handling work: For those of you who have requested full automation of task downloads, results submissions and high scores updates: We are actively working on developing the infrastructure that is required to handle all this for computing projects with a broad range of complexities. It would be easy to come up with something that will work for the current projects, but break for the next projects with different computational complexities. This would eventually lead to the need for another complicated transition that will include another re-evaluation of technologies and take up much time. But wait a moment, evolution@home is in exactly such a transition at the moment, because the simple initial system of handling data and analyses got overwhelmed. So why not try to make better choices this time. Many details need to be considered and anticipated in building this infrastructure and the constant change of technologies available for implementation adds its own challenges. We know we will not be able to find the perfect solution. However, we are working to make our prototype count in our quest for a solution that supports the enabling infrastructure that we want to build.
Modelling language work: We are working towards building a biologist-friendly model description language that makes it easy to describe simulation models. This will bring a big change to evolution@home, as it will break up the link between compiled simulator code (e.g. Simulator005) and simulated model (e.g. Muller's ratchet). Building on formal modelling approaches from systems biology, we are working on a new language that allows biologists to define a model that will then run on a more or less generic simulator. This eliminates the need for evolution@home to release many simulators for analyzing many models. This language will substantially improve the research infrastructure that evolution@home will be able to provide. That's why we are excited about it!