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Stanford's goal: to understand protein folding, protein aggregation, and related diseases.



What are proteins and why do they "fold"? Proteins are biology's workhorses -- its "nanomachines." Before proteins can carry out their biochemical function, they remarkably assemble themselves, or "fold." The process of protein folding, while critical and fundamental to virtually all of biology, remains a mystery. Moreover, perhaps not surprisingly, when proteins do not fold correctly (i.e. "misfold"), there can be serious effects, including many well known diseases, such as Alzheimer's, Mad Cow (BSE), CJD, ALS, and Parkinson's disease.

What does Folding@Home do? Folding@Home is a distributed computing project which studies protein folding, misfolding, aggregation, and related diseases. Stanford uses novel computational methods and large scale distributed computing, to simulate timescales thousands to millions of times longer than previously achieved. This has allowed us to simulate folding for the first time, and to now direct Stanford's approach to examine folding related disease.



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Revised plans for BigAdv (BA) experiment.
King_N
[H]ard|Folding Administrator


Posts: 101
Points: 2,811,473
Work Units: 6,593

Posted: Tue Jan 28, 2014 09:47 pm
Stanford is revising it's plans for BigAdv.

Quote:
Weve put a lot of time into reading the comments about the BA experiment and have come to some conclusions regarding how we should proceed. BA was originally conceived as an experiment to push FAH as close to what you could run on a traditional supercomputer as possible, doing calculations that most researchers thought could never run on a distributed computing platform. In order to make this possible, the requirements for BA would have to be pretty extreme and constantly updating (much like how supercomputers are constantly being updated to the latest hardware).


Full article: here.
Looking back at 2013 and forward to 2014.
King_N
[H]ard|Folding Administrator


Posts: 101
Points: 2,811,473
Work Units: 6,593

Posted: Mon Dec 30, 2013 07:08 am
Quite a bit of information from Stanford was released this month.


Looking back at 2013 and forward to 2014.

Quote:
As the year ends, its a natural time to look at some key highlights of weve done in 2013 and look ahead to whats on deck for 2014. One of the challenges of science results can easily take a year for us to run on FAH, analyze, and publish. So, the work of 2012 comes out in 2013 and the projects running in 2013 get to reach the public in 2014. So, it makes sense to talk about both work thats been going on this year and how all of this will shape up in 2014. Weve been doing a lot behind the scenes in 2013 and Im excited about all of this getting out to the public in 2014. Here are some key developments.

FAH development in 2013. Weve had several new developments in how FAH works, from both the donor perspective as well as how FAH works behind the scenes. With the addition of new programmer Yutong Proteneer Zhao, Core 17 was a big advance for FAH. It brought the most advanced features from the OpenMM GPU code, especially major speed increases for AMD/ATI cards. Moreover, it also brought a natural path to true Linux GPU support and lots of useful scientific updates. The v7 client continues to advance, with a new web interface; these simplifications have been important especially for certain partners who have wanted to see an easier to use FAH client before they can help us push for greater deployment. Adaptive sampling approaches have been a part of how FAH works, but weve also been moving to automate this process, leading to more powerful ways we can use the power of the FAH clients.


Full Article: here.



Key new results published in Nature Chemistry

Quote:
A key new work from the Pande Group just came out in Nature Chemistry and got a nice holiday present: our work on the cover!

Briefly, we applied methods developed and honed on Folding@home to Google Exacycle (Googles massively parallel cloud resource a lot like running Folding@home behind their firewall). The resources that Google donated to PG/Folding@home was pretty massive, allowing us to tackle a really significant and challenging problem in biology and drug design.


Full Article: here.




Changes to the bigadv threshold

Quote:
We have a policy of periodically re-evaluating the bigadv program, including the threshold required to run bigadv projects.

It is the intent of bigadv to match large and resource-intensive work units with some of the most powerful machines used by FAH donors. This most powerful line naturally advances with computing power. To date, bigadv has been a CPU-based program, and with increasing numbers of CPU cores and power of those cores, we have decided to lay out a roadmap of bigadv threshold changes for the next several months.


Feb 17 (two months from today): bigadv threshold will become 24 cores

Apr 17 (four months from today): bigadv threshold will become 32 cores


Full Article: here.
Changes in Core17: update and move to full fah
King_N
[H]ard|Folding Administrator


Posts: 101
Points: 2,811,473
Work Units: 6,593

Posted: Mon Nov 25, 2013 07:36 pm
There are some new changes to Core 17.

Quote:
Core17 Release Notes:

-Much more responsive exiting

-Fixed bugs related to visualization for next version of the FAHViewer

-Disabled some internal debug code

-For Windows NVIDIA Users running on a single GPU, weve enabled a new feature called temperature control that pauses the core internally. This is disabled by default.

-To enable temperature control, a pair of additional arguments are required:

-tmax (maximum temperature threshold in Celsius), must be less than 110

-twait (minimum wait duration in seconds), must be at least 900

-if temperature > tmax, then the GPU waits for at least twait seconds

-these can be passed in via extra-core-args in the config.xml file :

<slot id=0&#8242; type=GPU>

<extra-core-args v=-tmax=80 -twait=900&#8242;/>

</slot>

-Removed dependency of glib.
Congratulations to Michael Levitt
King_N
[H]ard|Folding Administrator


Posts: 101
Points: 2,811,473
Work Units: 6,593

Posted: Mon Oct 28, 2013 10:51 pm
Dr. Levitt a pioneer in using Molecular Dynamics to study proteins (a method which is at the heart of most of F@Hs calculations.) was awarded a Nobel Prize.

Quote:
Michael Levitt, PhD, has dramatically advanced the field of structural biology by developing sophisticated computer algorithms to build models of complex biological molecules.

Applying known three-dimensional structures and basic principles of physical chemistry as complementary guidelines, this modeling can, for example, predict a protein's molecular structure on the basis of that protein's amino-acid sequence.


Full Article : here.
GPU 16 core approaching end of life.
King_N
[H]ard|Folding Administrator


Posts: 101
Points: 2,811,473
Work Units: 6,593

Posted: Mon Sep 30, 2013 01:25 am
GPU Core 16 is now approaching end of life status.

Quote:
Our projects which use Core16 have completed and this means that Core16 is reaching its end of life, as the Core17 GPU core has some key features needed in new projects. We do not have an ETA for the last Core16 WU, but it is likely soon, i.e. in a week or two.
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