[独立平台] [生命科学类] Folding@Home

vmzy

July 09, 2012
Slow unfolded-state structuring revealed by simulation and experiment
Guest post from Dr. Vincent Voelz, Temple University
Using protein folding simulations alongside experiments remains challenging because the two techniques often "see" very different things. Simulation trajectories "see" every atom in a single protein in microscopic detail, while experiments often "see" only bulk properties averaged over large ensembles of molecules. For example, in the last few years, we have built kinetic network models of ever larger and slower-folding proteins. These models can have huge numbers of states and many possible folding pathways, yet experimental folding kinetics can be fit to models having only two or three states.
In a new paper, we try to bridge these two levels of detail using a combination of simulation and experiment to study the early folding events of ACBP, a 86-residue helix-bundle protein that folds on the ~10 millisecond timescale, one of the largest, slowest-folding proteins we have studied to date. Previous experiments suggested that ACBP folds via a "three-state" mechanism, with an intermediate forming on the ~100 µs timescale. To understand the molecular events underlying the formation of this intermediate, we used Folding@Home to generate tens of thousands of GPU-accelerated trajectories, and stitched these together to build a kinetic network model of the complete folding reaction (see figure below). By comparing our model to the results of state-of-the-art experiments (single-molecule FRET, Trp-Cys quenching, and time-resolved FRET) we found something surprising -- the folding relaxation timescale around ~100 µs corresponds to the heterogeneous formation of unfolded-state structure, rather than some discrete structural state.
This work is exciting because it shows that our models can predict atomically detailed mechanistic information about folding (currently very difficult to obtain experimentally) while simultaneously providing accurate predictions of quantities seen in bulk folding experiments.


大意：
蛋白质模拟和实验很难关联，因为模拟出来的是原子级的细节，而实验观察到的大多数分子级的。而模拟一般又很难进行大分子级的长时间折叠模拟。
最新我们发表了论文，利用GPU客户端对ACBP大分子进行了10毫秒级的折叠模拟。然后与实验结果进行了详细比对，有了很多惊人发现。
未来我们将可以利用模拟得到更多的细节信息，而这些信息目前是无法通过实验观测到的。

vmzy

July 16, 2012
New GPU-powered algorithms

Guest post from Dr. Xuhui Huang, Hong Kong University of Science and Technology

In this post, I want to introduce a new GPU-powered clustering algorithm we recently developed to analyze the large molecular dynamics simulation datasets generated by Folding@home. Folding@home can generate enormous sets of protein structures. A critical step in analyzing these large datasets involves some form of reduction in the dataset, usually in the form of clustering. We recently developed a GPU powered clustering algorithm using the intrinsic properties of a metric space to rapidly accelerate the clustering. Overall, our algorithm is up to two orders of magnitude faster than the CPU implementation, and holds even more promise with the ever increasing performance in GPU hardware.

This algorithm should facilitate numerous applications. For example, one of the systems we tested our code on is the human islet amyloid polypeptide (hIAPP) peptide, whose aggregation is implicated in Type 2 diabetes.  We hope further analysis of this data will provide insights that will inform the development of treatments for diabetes.
大意：
香港科技大学的Xuhui Huang教授开发了新的gpu集群算法，用以进行大分子的动态模拟，比cpu快2个量级。目前用这个算法对与II型糖尿病有关联的islet amyloid polypeptide (hIAPP胰岛淀粉肽)进行测试研究。
译者注：传说中的gpu-smp要问世了？

vmzy

July 17, 2012
Bonus for A4-core based projects

We've noticed a significant number of high priority projects are trailing behind existing projects. Newer projects are aimed at interpreting and guiding experiments where the full power of Folding@home (F@h) is essential to continue pushing the boundaries of scientific and medical discoveries.

The main cause of this issue is the core version needed to run these simulations. Many of our newer SMP projects use the A4 core, which has several scientific advancements, while existing projects use the still important A3 core. The A4 core is not compatible with Clients below version 6.34 and many donors are still running these older Client versions.

This presents an opportunity to encourage people to donate their cycles towards these vital A4 projects. To emphasize the scientific importance of these work units, we are boosting the base points of all A4 work units by 10% when uploaded (Note that this bonus will not be reported by V7 or by the 3rd party applications which project PPD but the points will appear when your statistics are credited). The quick return bonuses will be calculated on top of the increased base points. This will start on Monday July 23, 2011, and we will keep this 10% bonus in effect for at least 3 months as a trial period, but plan to keep it longer, as needed.

To participate, donors should be running a recent version of the F@h Client. We strongly encourage Windows users to update to the much improved V7 Client. Although F@h Client v6.34 or newer is sufficient to participate for any supported operating system. Please note the Linux and OSX V7 Clients are a work in progress and feedback is welcomed.

v7 Clients:
Windows/Linux: Visit our home page, http://folding.stanford.edu/English/HomePage
Mac OSX: v7 for OSX is still in testing. For a beta copy: https://fah-web.stanford.edu/projects/FAHClient/wiki/BetaRelease

Old v6.34+ Clients
Windows/Linux: http://folding.stanford.edu/English/DownloadWinOther  
大意：
我们发现，当前有些非常重要的新项目进展很缓慢。这些新项目大都使用A4内核，而6.34以下版本的FAH客户端不支持此内核。
为此，我们‘做了一个艰难的决定’，当任务上传后，将基础分上调10%（注：任务本身的基础分没有改变，所以v7和第三方工具算出的ppd没有任何变化。仅仅在服务器端授予积分时改分）。‘临时新政’将于7月23日起实施（注：官方手抖了年份打成去年了，呵呵），暂定实施3个月，届时将根据效果决定是否延期。

vmzy

July 23, 2012
Searching for new drug targets
Guest post from Dr. Gregory Bowman, UC Berkeley
Most rational drug design efforts assume the target protein exists in a single structure and that the structure of one region of the protein--called the active site--allows the protein to perform some function. Once this assumption is made, the only way to manipulate a protein’s activity is with inhibitors that bind the active site tightly enough to block it from performing its intended function. Unfortunately, this strategy only works for ~15% of proteins, greatly limiting the number of proteins we can manipulate for therapeutic purposes.
In a recent article published in the Proceedings of the National Academy of Sciences (link), I showed that simulations run on Folding@home can reveal new ways of manipulating a protein's activity. Specifically, I start off by recognizing that proteins are actually flexible and then use Folding@home to enumerate the different conformations a protein adopts. I then use statistical analysis to find parts of the protein that can communicate with the active site through a process called allostery. These regions--called allosteric sites--are attractive drug targets as the binding of small molecules to them can be communicated to the active site, ultimately affecting activity.
As a proof of principle, I showed that my approach can identify a known allosteric site in Beta-lactamase (see figure below). This protein is an important drug target because it can confer bacteria with antibiotic resistance by breaking down antibiotics like penicillin. I also use my approach to predict new allosteric sites in Beta-lactamase and two other proteins that play important roles in immune deficiencies and HIV. Now I'm performing experiments to test my predictions. It will require a lot more of your WUs, but I hope this type of approach can eventually lead to new pharmaceuticals.


On the left is a structure of Beta-lactamase that most people would think of as the structure of this protein. However, the right shows a different structure with a drug (cyan) bound in a pocket that isn’t visible in the structure on the left. Binding of this drug somehow affects the structure near the active site (green). Using my approach, I’m able to start with the structure on the left and then predict the existence of the structure on the right and the allosteric site the drug is bound to.
大意：
传统药物设计理论认为，蛋白质存在某种活性点，使蛋白质失效的唯一方法就是找到一种能和该活性点紧密结合的药物。不过这种方法只对15%的蛋白质有用。
在最近发表的文章中，我使用FAH模拟发现，蛋白质存在许多变构点，当药物与这些点结合后，蛋白质的构型会发生变化，从而使活性发生改变。
为了证明这个理论，我使用了β-内酰胺酶（该蛋白质与细菌的抗药性密切相关）的变构点进行研究。将来我将对β-内酰胺酶的新变构点和其他一些免疫缺陷和艾滋病相关的蛋白质变构点进行研究。如果研究成功，最终这将导致制药学发生巨变。

左图是β-内酰胺酶的结构，右图是药物（青绿色）与它结合后的结构。绿色为传统的活性点。

Bonus for A4-core based projects –– now in effect
A brief update to our previous blog post on the A4 bonus: the bonus is now in effect.
A4内核的加分计划正式开始实施

金鹏

烦请V版编辑翻译


by kasson » Tue Jul 31, 2012 2:03 am

We announced at the beginning of the year that the bigadv program would be moving to clients with 16+ cores. At this point, we are only serving 16+ BA work units. We do continue to evaluate the program and may make changes (in either direction) in the future as both the scientific work we are doing and the capabilities of donor machines continue to change.

Thanks for folding!
大意：
从现在起，BA任务的核心下限改为16核。将来会根据科研要求及志愿者装备情况继续调整核心下限。

vmzy

August 20, 2012
MSMBuilder: Open source code from the FAH developer community

Guest post from Dr. Gregory Bowman, UC Berkeley
We’ve been making a lot of progress with developing Markov state model (MSM) methods for analyzing the data we generate with the help of the FAH community. For those of you with a theory background, MSMs are just discrete-time master equation models. For everyone else, MSMs are a way of describing the conformational space a protein (or other biomolecule for that matter) explores as a set of states (i.e. distinct structures) and the transition rates between them. Much of the theory underlying these methods is quite old but their use has been limited by the challenges inherent to identifying a reasonable set of states.
During my time in the Pande lab, I worked with Xuhui Huang (now at the Hong Kong University of Science and Technology) to develop new methods for building MSMs from the large data sets we generate with FAH. Together, we started an open source software package called MSMBuilder (here) to automate the process of building MSMs. Now a number of more recent additions to the Pande lab are helping Xuhui, Vijay, and me in continuing to develop the software.
As we just released an update to MSMBuilder, I was looking back at some of our user statistics and was pleased to see how quickly our project is gaining traction. Since its initial release in 2009, there have been over 1,600 unique downloads of MSMBuilder. One cute feature of our webpage—provided by the SimTk software consortium at Stanford—is that you can go look where all of our users are (here). Its fun to see that MSMBuilder is being used on 5 continents. Maybe most importantly, MSMBuilder has been used in at least 40 publications to date. MSMBuilder is coming up at conferences with increasing frequency too, so I look forward to reporting back on our growth in another year or so.
大意：
开发了MSMBuilder开源工具。使用马科夫状态模型算法用于对fah的计算结果进行统计研究。

vmzy

September 10, 2012New methods for analyzing FAH data
Guest post from Dr. Gregory Bowman, UC Berkeley
Two general objectives of the Folding@home project are (1) to explain the molecular origins of existing experimental data and (2) to provide new insights that will inspire the next generation of cutting edge experiments. We have made tremendous progress in both areas, but particularly in the first area. Obtaining new insight is even more of an art and, therefore, less automatable.
To help facilitate new insights, I recently developed a Bayesian algorithm for coarse-graining our models. To explain, when we are studying some process—like the folding of a particular protein—we typically start by drawing on the computing resources you share with us to run extensive simulations of the process. Next, we build a Markov model from this data. As I’ve explained previously, these models are something like maps of the conformational space a protein explores. Specifically, they enumerate conformations the protein can adopt, how likely the protein is to form each of these structures, and how long it takes to morph from one structure to another. Typically, our initial models have tens of thousands of parameters and are capable of capturing fine details of the process at hand. Such models are superb for making a connection with experiments because we can capture all the little details that contribute to particular experimental observations. However, they are extremely hard to understand. Therefore, it is to our advantage to coarse-grain them. That is, we attempt to build a model with very few parameters that is as close as possible to the original, complicated model. If done properly, the new model can capture the essence of the phenomenon in a way that is easier for us to wrap our minds around. Based on the understanding this new model provides, we can start to generate new hypotheses and then test them with our more complicated models and, ultimately, via experiment.
Statistical uncertainty is a major hurdle in performing this sort of coarse-graining. For example, if we observe 100 transitions between a pair of conformations and each of these transitions is slow, then we can be pretty sure this is really a slow transition. However, if we only observe another transition once and it happens to occur slowly, who knows? It could be that it is really a slow transition. On the other hand, it could be we just got unlucky.
Existing methods for coarse-graining our Markov models assume we have enough data to accurately describe each transition. Therefore, they often pick up these poorly characterized transitions as being important (for protein folding, we typically care most about the slow steps, so slow and important are synonymous). The new method I’ve developed (describedhere) explicitly takes into account how many times a transition was observed. Therefore, it can appropriately place emphasis on the transitions we observed enough times to trust while disregarding the transitions we don’t trust. To accomplish this, I draw on Bayesian statistics. I can’t do this subject justice here, but if you’re ever trying to make sense of data that you have varying degrees of faith in, I highly recommend you look into Bayesian statistics.

大意：
分析FAH数据的新方法
FAH的目标主要有2个，1、解释现有分子实验数据。2、为下一代的创新实验提供指导、开拓思路。我们在第一项方面取得了长足进步，而第二项进展比较慢（因为这货属于技术创新的范畴，很难一蹴而就）。
为了促进创新，最近我开发了贝叶斯算法版的粗粒化模型。目前我们研究的过程大概是，先利用大家的计算力，对蛋白质进行模拟，然后利用模拟数据构造马尔科夫模型。我以前解释过，这些模型就像是研究蛋白质的空间广谱构型图，特别是，蛋白质所有的可能形成的结构，蛋白质如何形成这些结构，以及蛋白质变形的过程以及需要花费的时间。一般来说，我们的原始模型有上万个参数，可以得到非常多的模拟细节，来解释实验结果。但这依然很难理解。因此，我们想把模型粗粒化，用尽量少的参数控制复杂模型。这将有助于我们认识现象后面的本质。今后新的模型可以让我们提供更多的假设，并由模型验证，最终由实验验证。
粗粒化模型最大的障碍就是统计上的不确定性。比如，我们对某对构型进行了100次转换，每次都很慢，我们可以确信这个转换是很慢。如果我们对另一个转换只进行了1次转换，那就不敢保证这个转换是慢的，因为或许我们只是恰好观测到了最慢的那一次。
现在采用的粗粒化我们的马尔科夫模型的方案是，假设我们已经有了足够的可以精确描述转换的数据。然后选出最重要的（就蛋白质折叠而言，折叠越慢意味着越重要），舍弃不重要的（详见原文中链接）。为了达到目的，我们使用了贝叶斯统计方法。

译者注：这篇文章个人感觉比较晦涩，翻译水平不给力，大家凑合着看吧。

vmzy

September 24, 2012
New Gromacs, new you

Guest post from Profs Kasson and Shirts, UVA and Mr. Coffland

A new version of Gromacs (4.6) is coming, and we’re working to bring it to Folding@home.  The new code contains a number of improvements (more than you’d expect for a minor version number!), and we’ll post about some of the individual features as we go.  Not all of them will be available on F@h immediately, as some will require substantial development work over the next few months.  But some of the basics are new free energy methods from our very own Prof. Michael Shirts, new and slightly faster inner-loop code, and some important tweaks to parallelization.  Free energy calculations allow us to calculate things like how tightly drugs bind to proteins and the strength of attraction between protein components when pulled apart.  And you, of course, know what faster inner-loop code and better parallelization mean!

Gromacs is an interesting piece of simulation software in that it’s heavily optimized both for single-computer performance (part of why we chose it for F@h in the first place) and for parallel scaling.  A lot of codes choose to emphasize one or the other.  But Gromacs tries to do both.  That will have some interesting and useful implications for F@h particularly as we look at more and more cores on donor CPU’s (and things like GPU integration).  That’s all for now; we’ll keep you posted on progress.

Thanks!
The 4.6 Core Team (Profs. Kasson, Shirts, and the indefatigable Mr. Coffland)
大意：
Gromacs 4.6即将发布，我们准备移植到FAH中。新版本添加了很多新功能。将来会慢慢移植到FAH中，届时我们也会做介绍。一些基本的更新包括：新的自由能算法（可以计算药物和蛋白质的结合能，以及蛋白质分子间的吸引力），更快的内联代码，并行的优化（后两项的作用你懂得，传说中的鸡血代码）。

vmzy

OCTOBER 21, 2012
Unified GPU/SMP benchmarking scheme: equal points for equal work

The current benchmarking calculations for SMP and GPU projects are performed on different machines since originally the SMP cores could not perform the calculations that the GPUs cores could and vice versa (GPUs were only for implicit solvent calculations and SMP only for explicit solvent calculations). With recent advances in both cores and completion of our testing of these capabilities to ensure agreement, we are now confident we can do the same work on both cores. Thus, we feel that it is time to unify GPU and SMP benchmarking, both for simplicity and fairness.

In order to complete the move towards this plan of "equal points for equal work," new GPU projects will be benchmarked using the existing SMP benchmarking scheme. Based on our internal tests, the end effect of this new, unified benchmarking scheme would boost the points for the GPU projects, both in terms of base points but also by bringing Quick Return Bonuses to GPU clients. In order to test the new scheme, we have started a GPU3 project (Project ID: 8057) and released it for beta testing. Once the benchmarking scheme has been tested, all the current GPU projects will be re-benchmarked to reflect the changes in the benchmarking scheme.
大意：
GPU/SMP积分改制：实现同工同酬
当前GPU/SMP是依照不同的标准给分的（主要是gpu没有奖励分）。因为GPU主要进行隐式溶剂计算，而SMP主要进行显示溶剂计算。因此两者不好统一打分。经过我们的不懈努力和研究，我们觉得现在是时候统一了，这样不仅简化了积分系统，也增加了公平性。
为此，我们开始测试8057任务，调整了基础分也加入了奖励积分。测试结束后，将对所有gpu项目进行调整。

vmzy

OCTOBER 22, 2012
Life with Playstation ending, FAH team continuing to look to push the envelope

For several years, we have worked closely with Sony to bring Folding@home to the PS3.  We're excited about what we've been able to do.  Since the PS3 started folding in 2007, we've done some really amazing things, with several announcements this year acknowledging advancements in Alzheimer's Disease, Cancer (and this link), Influenza,Type II Diabetes, and other new drug targets. We've come a long way in the last 5 yearsand we have a lot going on to continue our tradition of pushing the envelope into new technologies.

大意：
ps3结束了与fah的合作，合作始于2007年，5年间对疾病和药物研究作出了不小的贡献。接下来我们将继续努力，不断的超越极限。

vmzy

OCTOBER 30, 2012
Version 7.2.9 of the Folding@home software is now available

We are happy to announce that version 7.2.9 of the Folding@home software is now available at folding.stanford.edu. The ultimate goal of Folding@home has always been to support disease research but we've also understood that one of the best ways to do this is to make folding fun and easy. This is why we continual push to make the Folding@home software easier to install and use while still adding advanced features for power users optimizing their machines for maximum points. This software release makes strides forward on all fronts.

One of the more visually interesting and fun features is our much improved 3D viewer. It is now able to display proteins from many more folding projects, works on more graphics cards and uses less CPU time. This code is also being used as the basis for the upcoming screensaver which is currently in testing.

Those with the latest and greatest hardware will be glad to know that this version supports automatic updating of the GPU white-list. In practical terms, this means Folding@home will be able to support new graphics hardware more quickly, as it becomes available and with out requiring new software. We will publish a new GPU white-list periodically and the client will automatically update its list of supported GPUs on startup.

We are also proud to announce that we recently hired OSX guru Kevin Bernhagen. He has been working hard to bring the OSX release up to our standards. With the v7.2.9 release we are taking the v7 software for OSX out of beta for the first time. There is still much work to do but this release should offer many improvements over the v6 beta that was previously the recommend release for OSX and should integrate better with the OSX environment better than the previous beta software.

Many other improvements have been made. The folding forum thread titled FAHClient V7.2.9 (8th Open-Beta) lists the changes in more detail. While you're at it, join in the forum discussions and let us know if you run into problems, have a great idea or just what to tell us about the awesome new folding rig you've setup.

We are far from done improving Folding@home. Many new features are in the works including simpler installers, even better OSX support and easier more intuitive user interfaces. There are also some surprises on the drawing board which we are very excited about but not yet ready to announce. So stay tuned and thank you for continuing to help support disease research at Stanford and universities all over the world.

大意：
发布7.2.9版FAH客户端。
改进了蛋白质的3d显示，现在很多项目都可以实时显示蛋白质图像了，并且减少了cpu占用，将来屏保程序也将采用此代码，不过目前屏保代码还在内测中。
GPU白名单文件将自动更新。
完善了osx客户端。
未来我们还将不断优化v7客户端。

The Folding@home article on Wikipedia is now a Featured Article

Here's a guest post from Jesse Victors, one of the volunteers helping with Folding@home documentation.

I am pleased to announce that the Folding@home article on Wikipedia is now a Featured Article. Following a peer review and a thorough month-long discussion, other editors agreed that it met the Featured Article criteria. This means that it's encyclopedic, well written, comprehensive, well researched, neutral, stable, and uses summary style. If you are new to the Folding@home project, or would like to learn more, I would highly recommend that you read this article. There are plenty of details on all aspects of Folding@home, but I tried to avoid technical language so it should be understandable by almost anyone. I've also summarized many of publications from FAH (see the Papers page) as well as other scientific literature, which can be helpful if you're curious about how this project works or what it has accomplished so far. The article is currently scheduled to appear on Wikipedia's Main Page as a Featured Article of the Day on November 1st, so keep an eye out for that!

大意：
Wikipedia上的FAH词条被列为精品文章。建议不论是新手还是老人，都可以去看看。11月1日，FAH词条将被Wikipedia置顶于首页。

vmzy

NOVEMBER 01, 2012
Today, FAH is the featured article on Wikipedia

Today, FAH is the featured article on Wikipedia.  We mentioned this earlier, but here's the snapshot.  Thanks to everyone who've contributed to making this possible!

大意：
今日FAH词条被Wikipedia置顶。

vmzy

NOVEMBER 06, 2012
Update on on-going software development in FAH

We have several on-going software development efforts and I'd like to give donors an update.

v7 client. Joe Coffland and his team have been working hard on new client releases. 7.2.9 has just been released and a new version will be undergoing beta testing soon. Moreover, we are continuing work on improving the v7 client for windows and squashing the remaining bugs. Moreover, there's additional effort in OSX due to the hiring of a programmer (Kevin Bernhagen) just for the OSX client, as well as additional work for smoother OSX and linux installs.

Gromacs core. The Gromacs core team (Prof. Michael Shirts and Prof. Peter Kasson and their labs, at the University of Virginia) are working on the new cores based on the new version of gromacs (4.6).

New OpenMM core. The OpenMM team at Stanford (Dr. Peter Eastman and Yutong Zhao) are working on speed improvements for OpenMM (the basis of the FAH GPU core) in general, but in particular optimizations for Kepler and AMD (in coordination with engineers at NVIDIA and AMD, respectively). Yutong has a new FAH GPU core working in the lab and we are doing internal testing on it.  Since openMM is full open source, you can see more details, including a commit and change log, at the openMM web site (https://simtk.org/home/openmm).

New FAH viral ad campaign.  We're also working on a new landing page for FAH and a new video to advertise FAH.  This new web/video campaign is coordinated with new client/installer changes to make FAH easier to install and run, especially for those new to Folding@home.

We understand that donors don't get to see all of what's going behind the scenes, so we'll try to post these sorts of updates more frequently.
大意：
FAH软件开发进展
虽然v729才发布不久，新版很快将开始公测。我们一直在不断的优化v7客户端，当然主要精力暂时在win上。不过我们雇了Kevin Bernhagen来优化苹果平台。
Gromacs团队在抓紧整合4.6版新内核。
GPU团队主要在优化速度（主要是和N、A官方人员一同优化Kepler和AMD），正在进行内测。因为OpenMM是开源的，希望有识之士能来一起帮忙优化。
网站方面，我们在制作新的首页，并且制作了一个新的广告视频。

vmzy

NOVEMBER 08, 2012
Planned server room maintenance: Saturday, November 10th, from 5AM to 8AM

One of our key server rooms will undergo network maintenance on Saturday, November 10th, from 5AM to 8AM pacific time.  During the maintenance window, we expect that the servers in that room will be unreachable, hopefully for only 30 minutes each, but potentially for the full time range.  We note that this is only one of our server rooms, so the FAH backend should still be primarily operational, but some donors will see some issues with returning work during this time.  We also stress that the FAH server backend is architected such that even when servers are down, the points for donors will not be lost, and just the accounting for those points will be delayed until the servers are back up.
大意：
11月10日周六晚21点至凌晨，有个机房进行网络维护，届时某些任务估计暂时无法上传。

vmzy

Tue Nov 20, 2012 10:05 pm
Folding servers Vsp12[a-g] will be down for maintenance
Vsp12 will be taken down for maintenance today (Nov 20) afternoon and is planned to be back up later in the evening.
All the interfaces on this machine (Vsp12a,b,c,d,e,f,g with server addresses 171.67.108.58, 59, 60, 141, 142, 143, 144) hosting projects with ID in the range 8001-8067 will be affected.
This includes several GPU3 and SMP A4 (multi+uniprocessor) projects. This server hosts a large number of current FAH projects but donors would be able to get work units from other
servers with similar work units. Thank you for your cooperation.

EDIT: [3:16 PM PST] The maintenance period has now been extended till tomorrow afternoon. The server is working right now but will be down sometime later. We are trying to minimize the downtime. Thanks.
大意：
vsp12物理服务器例行维护，计划从11月20日中午至次日中午（米国太平洋时间）。届时171.67.108.58, 59, 60, 141, 142, 143, 144虚拟服务器将停机，其上的GPU3、smp项目也会暂停。