[独立平台] [生命科学类] Folding@Home

vmzy

DECEMBER 03, 2012
The Protein-Folding Problem, 50 Years On

Guest post from Dr. Gregory Bowman, UC Berkeley

Ken Dill, a long-standing leader in protein folding, just published a beautiful review articleabout progress in the field.  The main point is that what began as a specific research question has now evolved into an entire field with numerous research directions.  It’s would be difficult to provide a more eloquent explanation than Ken’s, so here are a few excerpts from the article

    “The protein-folding problem was first posed about one half-century ago. The term refers to three     broad questions: (i) What is the physical code by which an amino acid sequence dictates a protein’s     native structure? (ii) How can proteins fold so fast? (iii) Can we devise a computer algorithm to     predict protein structures from their sequences?...  computer simulations of the physical forces in     chemically detailed models have now achieved the accurate folding of small proteins…  What began as     three questions of basic science one half-century ago has now grown into the full-fledged research     field of protein physical science.”

Insights and achievements from Folding@home are highlighted on a number of occasions throughout the article.  So, congrats to all for helping to establish this ever-growing field.

Also, there's a nice video about this online for those who are interested

大意：
介绍了蛋白质折叠的50年发展史。在我朝不存在的一个视频网站上有一段介绍视频，详情见官方帖子。

vmzy

DECEMBER 06, 2012
Unified GPU/SMP benchmarking scheme implemented

The  unified GPU/SMP benchmarking scheme will be rolled out today on FAH. All the future GPU projects would now be benchmarked using the new scheme. Most of the existing GPU projects have been re-benchmarked to reflect the changes in the benchmarking scheme. We are still in the process of re-benchmarking some old projects assigned to ATI and G80 GPUs. The uniform benchmarking scheme significantly boosts the base points for all GPU projects. However, Quick Return Bonus for the GPU clients has not been introduced at this stage, but will be introduced once we work out an issue on our side. We would like to thank all the beta testers who participated in testing the unified benchmarking scheme.
大意：
今天起统一GPU/SMP的积分机制，未来所有GPU任务都会有奖励分。目前除了个别比较老的任务（比如ATI和G80专用），其他的任务大部分都已经对基础分做了调整。不过由于服务器这边代码没部署完，所以奖励分暂时不发放，一旦服务器部署完毕，就将启用奖励分。

qscgy44

"未来所有GPU任务都会有奖励分"

vmzy

DECEMBER 08, 2012
AS patch for GPU assignments

We've been seeing donor reports of WU assignment issues for GPUs (WU's intended only for G80 GPUs going to Fermi and Kepler).  We finished an AS patch yesterday, gave it a day of testing, then rolled it out this morning to address this issue.  We generally don't like to roll out new AS code this quickly, but this time it seemed important to address this issue quickly.  We hope that as of 7:30am pacific time, this issue is now addressed, but we'll be keeping an eye out during the day to see.
大意：
GPU AS服务器升级
有些G80专用任务被发给了Fermi和Kepler。昨天我们修复了这个bug，测试了一天。今天把代码紧急上线了。希望不要出大问题。


Updates on GPU issues

We've been working to fix two issues with GPU clients in FAH.  Here's an update:

1) There was an issue with NVIDIA clients with G80 GPUs getting stuck in a core_outdated download infinite loop.  This has now been resolved.  This was caused when we stopped older projects which used core_11 (which the G80's were primarily running) and now the G80's are directed to more recent projects.  However, with the ending of the old projects and the start of the new ones, that means G80 GPUs go to core_15, which has much more strict testing for GPU memory errors.  Several donors have reported that these tests are failing with their boards.  We are looking into whether this is an issue with our test or potentially that the boards are not capable of running the latest core.  So, while the core_outdated loop issue appears now to be fixed, there is another unresolved issue which we are continuing to look into.

2) There was a second issue with ATI clients getting directed to servers running NV WU's.  This error is also unresolved at the moment, but we have a handle on what's happening on our end and have a team working on it.  I don't have any news here to report other than we can see the issue cause in our logs, which is the first step to fixing it.
大意：
1、我们废掉了core_11，现在统一使用core_15。但是由于服务器代码问题出现了G80死循环下载core_15的bug，不过现在这个bug已经解决了。可是由于core_15与部分G80卡不兼容，出了不少问题，我们正在着手解决此问题。
2、某些ATI卡收到了N卡任务。我们正在调查此问题。


GPU update

We've put a new revised AS up and we think this should fix the recent issues. We will of course continue to monitor the situation.
大意：
升级了AS代码，解决了今天出现的问题。继续监控看是否会出其他问题。

vmzy

DECEMBER 10, 2012
Meet new FAH GPU programmer Yutong Zhao


We have had an unfilled spot in our GPU programming team for a few months and I'm happy to announce that we recently made a great new hire: Yutong Zhao.

Yutong completed his undergraduate degree in Math, Chemistry, and Biochemistry from the University of Toronto, and a Masters degree in Computational Chemistry from HKUST, focusing on GPU-powered clustering algorithms. Previously, he has also worked on projects such as FoldIt! Currently, he is the lead developer of the Folding@Home GPU core and aims to extend functionality while increasing maintainability. He also plays a key role on the OpenMM side, he works on devising parallel algorithms to speed up MD simulations. He also maintains a blog detailing some of his algorithms and problems on www.proteneer.com .
大意：
GPU团队新增人员——Yutong Zhao
早年在多伦多大学拿到数学、化学、生物化学3学士学位，后来在香港科技大学拿到计算化学硕士学位。之前参与了FoldIt和OpenMM 的开发。现在主要负责代码重构以及并行加速算法研究。有兴趣技术宅的可以去他的博客看看。

vmzy

FEBRUARY 01, 2013
Known stats issue under investigation

We're having an issue with the interaction between our web main server and stats db.  We are looking into this.  It looks like the obvious fixes haven't worked, so we are escalating.  

The stats are being input fine, it's just with the reporting on the main web page.  If this continues, we may take the main web page stats pages down, but 3rd party stats should still work and be regularly updated.

As always, we'll update you on our progress with this issue.
大意：
统计服务器出现故障，正在修复中。

金鹏

FEBRUARY 01, 2013Known stats issue under investigation

We're having an issue with the interaction between our web main server and stats db.  We are looking into this.  It looks like the obvious fixes haven't worked, so we are escalating.  

The stats are being input fine, it's just with the reporting on the main web page.  If this continues, we may take the main web page stats pages down, but 3rd party stats should still work and be regularly updated.

As always, we'll update you on our progress with this issue.

Posted at 01:04 PM | Permalink

JANUARY 31, 2013FAH vm server went down, now back up

We have a VM server go down which brought down a few FAH services (notably web site and backup AS), but it's back up.  The stats viewing was unavailable during the outage, but the stats input to the db was unaffected.

Our sysadmins got the machine back up and all looks to be back in order.

Posted at 08:51 PM | Permalink

JANUARY 21, 2013Updated download for 6.41 GPU client

For those of you interested in the older 6.41 client, we've updated the download links for the 6.41 GPU client.  Please find it in the normal place:

http://folding.stanford.edu/English/DownloadWinOther

This is likely only of interest to a very small community as we highly recommend most people to use the latest v7 client.

Windows XP/2003/Vista/7 GPU3 (required for Fermi) System tray client with special viewer for NVIDIA GPU's (installer msi).

6.41

Windows XP/2003/Vista/7 GPU3 (required for Fermi) no-nonsense console client.

6.41

vmzy

FEBRUARY 11, 2013

New methods development

Guest post from Dr. Greg Bowman, University of California, Berkeley

Markov state models (MSMs) are a powerful approach for investigating the dynamics of proteins and other biomolecules. The Folding@home team has helped to pioneer the development of these methods and continues to make important contributions to their further development.  For example, the Huang lab at the Hong Kong University of Science and Technology has created an exciting new method for coarse-graining Markov models (the paper is available here).

One of the major challenges in this area is that the high-resolution Markov models capable of making quantitative predictions of experiments often have tens of thousands of parts.  As you can imagine, it is hard to look at each of these parts and the interactions between them to understand the model.  Therefore, it is valuable to create a new model with, say, a dozen states that still captures much of the behavior of the more complex model.

The new method from the Huang lab makes use of a mathematical principle called a Nystrom expansion to build more accurate coarse-grained models.  The key advantage of this approach is that one can quickly identify the most important pieces of a model and prove that the remaining pieces can safely be ignored (or merged into the more important parts).  As a proof of principle, the Huang lab has shown they can build much better models for a few small proteins than is possible with previous methods.

大意：
香港科技大学的黄教授利用奈斯特龙展开定理粗化了马尔科夫模型，可以利用最小的计算量得出最多的有效结果。目前已经对小蛋白质分子做了很好的优化。

vmzy

FEBRUARY 18, 2013
New FAH client, web site, and video

We've rolled out the latest version 7.3 client to the main web site.  This new client should be much easier to install and comes with a new web interface which is simpler and easier to use.  But in addition, we've been trying to communicate our goals and mission more clearly.  Our first steps there are a new web site and a new video.  The video in particular is something that we're all very excited about, since it explains to a broad audience what FAH is all about.
大意：
发布7.3版客户端，对界面做了较大改动，增加了网页界面。
对网站和介绍视频进行了更新。

注：7.3版目前低级bug较多，建议新手不要使用，老手谨慎升级。
目前已知问题：
1、web界面必须联网才能使用。
2、fah运行中，系统无法进入休眠状态。
3、经常无法连接client，无法查看log。
4、默认不会使用全部资源，每次启动后都需要手工调至full状态，非常麻烦。

视频地址请到原文，翻墙后查看。http://folding.typepad.com/news/ ... site-and-video.html

vmzy

FEBRUARY 27, 2013
Past the 10 Petaflop scale

Folding@home has historically been an extremely powerful computing resource, hitting many major computing milestones.  For example, we were awarded a Guinness World Record for being the first to reach a petaflop (10^15 floating point operations per second).

We keep track of the power of Folding@home on our osstats page.  Recently, we found an issue with our reporting.  In particular, we were investigating a major under-reporting (OSX stats reported that there were no OSX machines at all). A few months ago, Christian Schwantes (FAH Team member) rewrote our main stats scripts and he fixed a very old bug in the stats reporting. That bug had a workaround in the osstats2 page, so now the workaround was failing and that led to finally getting osstats2 working.

After checking the db with the raw files from the work servers (it's an important check that we can know what the right answer is from this more laborious manual process of going through the WS logs), this result is now correct, fixing the previous under-reporting. We also now are keeping better track of the Fermi (and later) class of NV GPUs. We were under-reporting their FLOP count and that alone was what make a huge difference in the FLOPs reported.

The upshot of all of this is that we now are no longer under-reporting our stats and the reported FLOPs has gone up significantly, to about 12 PFLOPs.  This puts Folding@home past the 10 PetaFLOP scale, which is itself a very significant amount of computer power.

For more information, please see our FLOPS FAQ, whichis useful in discussing this topic, which is surprisingly complicated.
大意：
计算速度超过10P，注：1P的吉尼斯世界纪录是FAH拿到的哦！
最近OSX系统的统计出了问题，所以我们安排人对统计程序及日志代码走查了一遍，不但修正了OSX的bug，还发现N卡的统计数据有问题（速度偏低了）。我们现在对统计进行了修正。目前计算速度达到12P了。

vmzy

MARCH 01, 2013

FAH paper listed amongst best of 2012 by Biophysical Journal

Biophysical Journal announced their "Best of 2012" paper collection.  We were excited that one of our papers was included.  That work, "Protein Folding is Mechanistically Robust" investigates how key aspects of FAH technology (MSMs) can yield new insights into protein folding in some unexpected ways.  Congratulations to Jeffery Weber for his work.  We've posted the technical abstract below as well.

ABSTRACT.  Markov state models (MSMs) have proven to be useful tools in simulating large and slowly-relaxing biological systems like proteins. MSMs model proteins through dynamics on a discrete-state energy landscape, allowing molecules to effectively sample large regions of phase space. In this work, we use aspects of MSMs to ask: is protein folding mechanistically robust? We first provide a definition of mechanism in the context of Markovian models, and we later use perturbation theory and the concept of parametric sloppiness to show that parts of the MSM eigenspectrum are resistant to perturbation. We introduce a new, to our knowledge, Bayesian metric by which eigenspectrum robustness can be evaluated, and we discuss the implications of mechanistic robustness and possible new applications of MSMs to understanding biophysical phenomena.

大意：
FAH论文获Biophysical杂志2012最佳文章（之一）称号

vmzy

MARCH 05, 2013
Introducing Folding@Home Core 17 – GPU zeta core

As also announced on OpenMM/Folding@home programmer Yutong "proteneer" Zhao's web site, we are happy to announce that Folding@Home Core 17 has entered Beta. Externally, you probably won’t notice too much of a difference. Internally, this is a complete overhaul that brings many new features, and sets a strong foundation for the future of GPU core development. In addition, the restructuring brings much tighter integration of the core with the rest of the development within Folding@Home.

We’re also introducing an explicit solvent project (p7661) as part of the Beta. To keep the credit assigned to these projects consistent with previous explicit solvent work units run on CPUs, we are also awarding a quick return bonus with a k-factor of 0.75. This reflects the additional scientific value of these units, and keeps the Folding@Home credit awards consistent across different architectures.

Usage:
This is a still a very new core, a lot of the features have yet to be fully tested. Thus, as is the beta policy, no official support is given. You must enable the -beta flag on FAHClient, ie. set client-type=beta. If you’re using client 7.2.x or earlier, there are two options:
1. Specify -gpu-vendor=XXX, where XXX is either nvidia or ati
2. If -gpu-vendor is not specified, the core will automatically guess the platformId.
Otherwise, 7.3.6 lets you specify the particular -gpu-vendor as an option
Supported NVIDIA cards: Fermi or better (Titan does not work atm, as NVIDIA needs to publish new OpenCL drivers)
Supported ATI cards: HD5000 or better
As always, please use the latest drivers (Win XP is NOT supported due to super-old AMD drivers).

Key Features:
Cleaner Code
We have deprecated several layers of GROMACs and other wrappers as the old architecture severely limited the types of simulations that can be run. Much of the work on the new core has been to replace existing features. The resulting code is now more streamlined and integrated. We also anticipate that this major re-design will allow us to introduce new features into the Folding@Home much faster.

Serialization
We have introduced a new serialization mechanism that allows Pande Group researchers to setup significantly more diverse simulations. Pande Group researchers can now easily setup jobs and projects using Python (with a much richer and easier to use set of libraries), while the core maintains its speed by virtue of being written in C++. We achieved this using a serialization technique, whereby all details of a simulation are encapsulated using a standardized format that is then be passed around between language barriers. This also drastically reduces the dependencies needed by the Work Server and other parts of Folding@Home.

A single unified core now runs both NVIDIA and AMD cards
Before we had two development branches for NVIDIA and AMD cards. It was a difficult and cumbersome task to debug and maintain. We couldn’t easily mix runs and gens produced by different GPU types. Now, using OpenCL, a single core supports not only AMD and NVIDIA, but theoretically any OpenCL-capable device.

Improved Stability
By reducing the amount of boilerplate code, we’ve also increased the robustness and stability of the core. The log files should also now be much more informative. There are also a lot of useful debugging features built right into the core to help PG developers nail down hard to find bugs.

Extra special thanks to our testers:
Jesse_V, k1wi, artoar_11, bollix, ChelseaOilman, bruce, Demonfang, Grandpa_01, EXT64, Flaschie, HayesK, jimerickson, mmonnin_, P5-133XL, Patriot, rhavern, sc0tty8, SodaAnt, SolidSteel144, EvilPenguin, art_l_j_PlanetAMD64, thews, cam51037, Pin, muziqaz, baz657, PantherX, QINSP, Schro, and hootis.

大意：
FAH开始测试core17
core17几乎重写了代码，为将来的各项改进打下基础，测试项目为p7661，此项目有奖励分，奖励系数为0.75。

参与方法：由于此内核还在测试，所以可能不稳定。
首先，你要给客户端加beta参数（client-type=beta），如果客户端显卡识别有误，你也可以用-gpu-vendor=XXX参数强行指定显卡类型。
其次，你需要支持的显卡。N卡：fermi及以上（Titan由于opencl驱动问题，暂不支持）。A卡：HD5000及以上（由于A卡的xp驱动太老，可能无法支持）
再次，最好升级到最新的驱动，以便对opencl提供最佳支持。

亮点：
1、代码重构。有些老代码很低效，也不支持新功能。所以完全重写了。
2、新的序列化技术。PG小组现在可以使用python客户端直接设置发布新任务，做更多的模拟，而计算部分也用c++重写了，尽量保持计算高效的同时，降低了科学家的任务发布复杂度。
3、N、A内核合体。以前维护2套内核的成本很高，现在由于采用了opencl技术，2个客户端合体了。而且理论上所有支持opencl的设备都可以用。
4、提高稳定性。代码重构的同时，加入了更多有用的log输出和debug功能，方便PG小组找bug。
5、致谢内测人员。


OpenMM Youtube channel

OpenMM is a key part of Folding@home, powering its GPU cores.  You can learn more about OpenMM at its youtube page, which includes technical videos on how you can incorporate OpenMM into your code.  It also includes an introduction to Markov State Models (MSMs), which is a key technology used in Folding@home.

http://www.youtube.com/user/SimbiosOpenMM
大意：
FAH的gpu主要使用的是OpenMM库，官方做了几个介绍视频，有兴趣的可以翻墙去看下。

译注：既然显卡奖励出来了，估计地主们的显卡升级潮也会到来，需要淘汰卡（尤其是免费用电）的朋友请常来看看，密切关注论坛的捐赠贴子。

vmzy

MARCH 06, 2013
FAH bench – FAH core/OpenMM-based benchmark for your GPU

As previously blogged, FAHBench is the official Folding@Home GPU benchmark. It measures the compute performance of GPUs for Folding@Home. In addition, by use of a loadable DLL system, it provides vendors and skilled hackers with a method make customized-plugins and test their results.

Info
Current release 0.5 – Jan/30/2013 (Stable)
-Updates:
-Minor performance improvements
Download Link (You must agree to Disclaimer on the bottom)

Usage
The program runs from the command line – allowing you to set up runs as needed. For example:
FAHBench.exe -deviceId 0 -platform OpenCL -precision single
Uses the OpenCL platform on the 0th (0-indexed) device, in single precision mode
NVIDIA cards can use either the OpenCL or the CUDA platform. ATI cards must use the OpenCL platform.

Contact
Yutong Zhao (proteneer at gmail)

Requirements
OpenCL:
Windows (tested on Win7, untested on others)
Latest NVIDIA/ATI Drivers (Exclusive-Or)
CUDA:
Microsoft has deprecated MSVS 2008 Express, the CUDA platform is no longer supported until NVIDIA ships a built-in JIT compiler.

Current Stats
These numbers measure the expected number of nanoseconds per day on a realistic simulation system. Time step used in integration is set to 2 femtoseconds.

System 1: DHFR, Single Precision

OpenCL
   HD7970: (Explicit 18.1 ns/day | Implicit 101.3 ns/day)
Tesla K20: (Explicit 18.1 ns/day | Implicit  84.5 ns/day)
GTX 660Ti: (Explicit 16.1 ns/day | Implicit  77.0 ns/day)
   HD4000: (Explicit  3.2 ns/day | Implicit  18.0 ns/day)
i7-3770K: (Explicit  3.1 ns/day | Implicit   3.4 ns/day)

(more to come)


Developers
It is very easy to test your own modifications the source code. Though note that the GPU code in OpenMM is LGPL – you must be able to provide us (the OpenMM developers) changes to the source code upon request.

1. Download the latest OpenMM from the svn repo: svn checkout https://simtk.org/svn/openmm
2. Build the projects OpenMM OpenMMSerialization OpenMMCUDA OpenMMOpenCL using CMake and VS2008
3. Replace the .dlls in the FAHBench folder with your own

It is not recommended to directly use FAHBench to ensure accuracy. OpenMM has its own suite of detailed unit tests that can pinpoint problems much easier. FAHBench serves as a final check.

Links
Folding@Home
OpenMM

Disclaimer
IN NO EVENT SHALL THE AUTHORS BE LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF STANFORD UNIVERSITY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE AUTHORS SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOTLIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE AND ACCOMPANYING DOCUMENTATION PROVIDED HEREUNDER IS PROVIDED "AS IS". THE AUTHORS AND STANFORD UNIVERSITY HAS NO OBLIGATION TO PROVIDE MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
大意：
官方发布opencl跑分测试程序（暂不支持cuda，程序仅在win7下测试过，其他系统不一定支持）。
大家开个帖子晒分吧。

vmzy

MARCH 07, 2013
In memory of Gordon T. and Rose Anne Smitheman

Today, we have a guest post by Team MaximumPC.  Two new work unit servers have been funded by the Folding@home (FAH) community in memory of Gordon T. Smitheman and his wife, Rose Anne.

Gordon, a dedicated member (username:gsmitheman) of Team MaximumPC (#11108), passed away January 25, 2012.  His death came just a couple of months after his beloved Rose passed away on November 27, 2011 after a battle with pancreatic cancer.

As evidenced by his 17,000 posts in the MaximumPC Folding Forum, Gordon was very active at promoting the project.  It wasn’t just the quantity, but the quality of his posts that made him a revered teammate.  His calling card was recognizing others: welcoming new folders, celebrating personal and team milestones, coordinating contests with prizes of hardware donated by him and others, and other posts that encouraged active participation in the forum.  He also visited other teams’ forums to extend greetings and recognize their milestones.

The impact of losing such a valuable teammate and genuinely kind-hearted person was hard to put into words, but many did their best in a forum thread titled “We Lost One of F@H's Greatest Champions - Gordon Smitheman.”

Teammate and FAH beta tester Michael “Doc” McCord, MD proposed a server purchase as a tribute to the tireless dedication Gordon demonstrated in promoting folding. The generosity of donors, representing numerous teams throughout the world, resulted in the funds to purchase not one, but two servers for the project.

Gordon greatly valued his family.  It was one of the few things that took precedence over folding.  But, his family was very supportive of his FAH activities.  It was for that reason naming the second server after Gordon’s wife, Rose, was a natural choice.

Many thanks to Dr. Pande, Dr. McCord, Team MaximumPC, and everyone who donated funds that made this commemoration possible.  Fold On!

大意：
纪念Gordon T. 和 Rose Anne Smitheman夫妇
Gordon卒于2012年1月25日，她的爱人Rose 因胰腺癌卒于2011年11月27日。 Smitheman 夫妇生前曾大力致力于推广和宣传FAH。在他们过世后队友发起了怀念贴，并募集了捐款，买了2台服务器，现赠与FAH官方。官方接受了捐赠，并分别以Smitheman 夫妇的名字为这2台服务器命名。
让我们向死者致敬，继续努力计算吧。

vmzy

MARCH 11, 2013
Inferring the Rate-Length Law of Protein Folding

Guest post from Dr. Gregory Bowman, University of California, Berkeley

One objective of the Folding@home project is to provide insight into general protein folding mechanisms that hold across a variety of systems.  For example, how much slower, on average, do longer proteins take to fold than shorter ones?  To address questions like this, Lane and Pande recently developed a theoretical framework for testing different models of the scaling of protein folding times with chain length against experimental observations (line here).  One of their major conclusions is that there is insufficient data to distinguish between many of the possible models.  All is not lost though.  The framework they developed also allows them to point out the types of measurements that need to be made to conclusively determine which of the models that have been proposed is best.  In the future, it will be exciting to begin both computational and experimental studies of these systems.
大意：
推测蛋白质折叠的率长值。
FAH的目标之一就是寻找不同系统中的共性。比如，蛋白质长尺度模拟比短尺度模拟一般要慢多少？为此专家们根据不同的模拟数据以及实验数据进行了数学建模。虽然最后由于数据的不足建模失败了。不过失败是成功她妈。因此，我们知道了我们大概还差哪些关键数据，今后我们会调整研究方向，补齐这些缺失的数据。