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 [log in to unmask]  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.