In a sentence, primarily due to cost and power constraints mobile devices don't (currently) have the horsepower to do any serious *generic* number crunching, as would be required for anything of interest to this community.
On the topic of using otherwise-idle compute time, our group has a publicly available service for doing molecular replacement which accesses a federation of computing centers across the US (through Open Science Grid): https://portal.nebiogrid.org/secure/apps/wsmr/ We regularly secure 50-150,000 hours per day of computing time from OSG. We're in the process of improving this and adding in additional services. Watch this space. For those with more of an interest on this topic, you can read on below. Regards, Ian This thread raises some interesting questions, but indicates a lack of understanding of the difference between what a mobile device like an iPhone, iPad, or Android can do compared to a rack-mounted server, desktop computer, or even laptop. The number crunching mobile devices are capable of is for specific sorts of data like audio and video codecs which are offloaded to specialized hardware and which can't (currently) be reused for other applications (like protein structure studies). GPUs are showing how this can change, but I wouldn't hold your breath. I think power and battery life will continue to be challenges for mobile devices for a long time, so even if generic computing ability catches up with "conventional" desktop/server capabilities, few people will want their batteries drained by their device running continuously doing an MD simulation or structure refinement. On 2/25/11 5:01 PM, Xiaoguang Xue wrote: > Well, maybe building a distributed computing network （Like Fold@Home) > by iphone is an improvement of the clusters. Let's think about a > phenomenon, the most common functions of our iphone are calling, > playing music, and maybe gaming, so most of the time the phone is > idle. Why don't we try to use these idle computing time to help us > doing some more important and interesting things, like determining the > proteins structures US-based non-commercial researchers can access Open Science Grid (http://www.opensciencegrid.org/), which consists of a federation of about 80,000 compute cores, by registering for a certificate and joining (or forming) a Virtual Organization. We host a Virtual Organization in OSG called "SBGrid" which is open to all SBGrid consortium members (http://sbgrid.org/). We regularly get 2000-4000 compute cores from OSG for extended periods (12-96 hours), so it is a very powerful resource. Another alternative for structural biologists who could benefit from >1000s of compute cores is to get an allocation at a national supercomputing center. In the US, NERSC or TeraGrid are good routes for this, and many options exist. In Europe EGI and DEISA provide a similar "one stop shop" for federated grid computing and supercomputing center access. http://www.nersc.gov/ https://www.teragrid.org/ http://www.egi.eu/ http://www.deisa.eu/ Finally, you can benefit from the millions of desktop computers out there with super-powerful compute cores and GPUs that spend most of the time (often >90%) completely idle using "screen saver computing". Here there is really only one option which is BOINC, developed by the group that created SETI@Home. Rosetta is (sort-of) available this way through Rosetta@home, developed by the Baker Lab. http://boinc.berkeley.edu/ http://boinc.bakerlab.org/ > I also noticed that there is some progress in grid computing on iphone > and PS3. So I think it's possible to apply this technique to > structural biology. > http://www.sciencedaily.com/releases/2010/04/100413072040.htm I think adding "iPhone" to the title of that article was just to attract readers. They are only using the standard web-browsing features available on pretty much any smart phone or mobile device to view web-portal views of computational infrastructure. All the actual computing was done on PS3s (and only 16 of them). In other words, if you consider browsing to EBI or RCSB to access some sequence alignment program or view some protein structures, then you can say "I've used an iPhone for grid computing". Most people, however, would question the accuracy of this association.
