Redline Folding @ OC3D Page: 1

Redline Folding @ OC3D

Team 98860 background

The Redline name started as an idea by a member of the Futuremark forums, Phil, who created Redline 3D as an elite overclocking team. Redline 3D was an invitation only group selected by Phil and OK'ed by existing members. Thus a rather elite group of overclockers were chosen for their ability and accomplishments with their given hardware, but not necessarily because they were on top of the ORB. This happened back in the heyday of MadOnion and into early Futuremark, which used to be a forum heavily involved in overclocking and benchmarking.

Even to those who were not on the Redline 3D team, Phil was known by most on the forums as a helpful, knowledgeable, all-around great person. It was a shock to all of us when we found out he had passed away in a swimming accident.

Several years had passed when kup decided to create a folding team in Phil’s honor. Initially the team only had a few members, all of whom defected from Futuremark’s folding team because of a lack of support. These members were kup, stevehat1, and nikk. Several more people followed shortly after as members of Futuremark continued to defect. The idea was to have a forum where we could actively promote the folding cause and campaign for new members without worrying about breaking forum rules.

At the height of Redline Redux —appropriately named in honor of Phil— there were only 12 regular members. Yet we bonded and remained competitive. There were ups and downs, but eventually we found ourselves at a point where we could seriously contend for a spot in the top 100 teams in the Folding@Home project. To give this some perspective, there are currently over 1,500 active folding teams being supported by over 460,000 active processors from all over the world. The average team in the top 100 has over 140 members—and yet our 12-person team was closing in on spot #100.

It was around this time that kup was approached by TTL at OC3D with the prospect of Redline joining OC3D and merging teams. The proposal was enticing, and it was intended to benefit both Redline and OC3D: Redline gets a larger home with the potential to grow the folding team, and OC3D revives its then-ailing folding team with new spirit and power; it was a win-win. We decided to go for it, and here we are today: united, more powerful, and now bearing down on the top 50 teams!


So, what exactly IS folding?  

The Folding@Home project has been around for almost 10 years, promoted and advertised by such organizations as EVGA, MaximumPC and HardOCP, and the most common question we still come across is “what is folding?” To put it simply, Folding@Home is a project created by Stanford University to simulate and understand protein folding. Why is this important? Because when proteins in the body don’t fold correctly, it can ultimately lead to the development of diseases like Parkinson’s disease, Huntington’s disease, Alzheimer’s, sickle-cell, cystic fibrosis, and cancer. The goal of the Folding@Home project is to better understand protein folding in an attempt to one day be able to cure these diseases.

Folding@Home uses the processing power of your computer or PS3 to simulate protein folding. A couple hundred thousand computers around the world simultaneously work on separate parts of the protein, breaking it up in small enough sections so that the work can be completed in a timely manner. This is called distributed computing. Before this concept of distributed computing, the only way to perform such extensive calculations was to use a supercomputer. And yet the world’s second fastest supercomputer, the Tianhe-1A, has only half the processing power of the entire Folding@Home project. To put it another way, Folding@Home has more processing power than some of the fastest supercomputers in the world combined, totaling over 6.3 petaflops. This is an amazing amount of processing power that is only possible through the contributions of every single participant in the project.


Okay, but does F@H actually do anything?

For the quickest information about Stanford’s results, go to their Diseases Page to read about many of the diseases they are currently studying through folding, how protein folding relates to disease, and a timeline of their work on each disease. Consider this a sort of overview for most of us who aren’t technical enough to read their peer-reviewed papers. For those of you who have a more thorough understanding of the science, you can read about all of their peer-reviewed papers here. Keep in mind, as Stanford notes, that these papers are written for other scientists, so the content is very technical. Still, going through the abstracts can give you a great sense of what Stanford is working on as well as the kinds of results they are seeing. It is also worth noting that Stanford publishes their results publicly, for everybody to read. Doing so helps to ensure that not just Stanford scientists, but scientists around the world are able to use the Folding@Home results towards their own independent research if they so choose.

Have there been any huge breakthroughs in the science since the project started? Many critics might say no, simply because a de-facto cure has not been discovered for any of these diseases yet. But what these critics don’t understand is that we can’t expect to see concrete results overnight. There have been results, and lots of them: one recent (and particularly notable) paper involves folding the Abeta peptide, which, according to Stanford, is believed to be linked to Alzheimer’s disease. The research has found a stable form of a misfolded Abeta, which could lead to new methods of Alzheimer’s therapy.  More information on this exciting research can be found on the F@H blog here. Is it groundbreaking? That’s up to the individual to decide, but we may be witnessing the beginning of some very promising breakthroughs in this type of research. The point, though, is that even if no groundbreaking research has surfaced yet, the Folding@Home project has still enabled scientists for the first time to be able to look at protein folding in a way that was previously not possible. Truthfully, we are probably at the beginning of a long-winded road towards the ability to cure some of these diseases. But this project is not about instant results. It’s about working towards something that might one day save the lives of millions of people, including yourself or a close relative; which brings us to why we fold…


Why we fold

What keeps us all folding? Why do some of us endure the searing heat and annoying hum of multiple dedicated folding computers in our bedrooms? Why do most us find ourselves checking the stats page 8 times a day, waiting for that recently completed work unit to show up under our name? If you ask anybody who folds, most will give you a personal reason. It’s usually because a friend or relative has been affected by one of the mentioned diseases. In some cases the person folding has been personally affected by something like cancer. In the case of the Redline team, we continue to fold with Phil in our thoughts and as our inspiration. Many other teams have similar motivation. Yet the varying reasons why people fold share a common, underlying idea: for the vast majority of us who are not scientists, Folding@Home gives us empowerment. The project gives us the encouragement that we too can contribute to curing something as complicated and atrocious as cancer. It allows us to help in one of the only ways we can: by donating computational time that makes the Folding@Home project possible. It’s a way to actually see how our donations are being used by science, unlike other types of monetary donations. But most of all, it’s a chance for us to do some good, be a little competitive, and have some fun all at the same time.

 

How do I get started?
 
There are several types of F@H clients that are available for use depending on the type of hardware your computer has and your computer’s operating system. For simplicity, we will show you how to use the program FAH GPU Tracker V2 which allows you to fold on your CPU and certain GPUs. This is the easiest way to get set up and folding quickly. Once you become more familiar with F@H, you may eventually opt to run more advanced types of clients.

Of course, if you are already familiar with F@H, you can skip right ahead and configure your client(s) to fold for team 98860 – that is the Redline team here at OC3D. You can also head on over to our Folding Forum for help at any time if you have questions.

Setup

1. First, go hereand obtain a F@H passkey. This passkey is used to help identify your unique contribution to the project, and it allows you to receive a point bonus for running certain clients. Fill out your donor name (the username you would like to fold under) and email address and Stanford will email your passkey to you. Keep your passkey in a safe place and don’t give it out. You will use it later.

2. Now click here to download the latest version of the Tracker program. Extract the contents into a folder anywhere you like.

3. Find FAH GPU Tracker V2.exe in the folder you just created and run it. A dialog box will open asking if you would like to download the FAH clients. Click yes. You should see the following:

Redline Folding @ OC3D  


4. Once the download is finished, click on Setup > Configure in the Tracker program. It should open up the following window:

Redline Folding @ OC3D  

 

5. Check the box at the top left to enable CPU folding. If your CPU has two or more cores, select to use the SMP client. Otherwise, leave the selection on the single-core client. For SMP settings, you typically want to allow all CPU cores. If you have a fast 8-thread CPU (or higher) and run it 24/7, you may wish to select the –bigadv option for extra big work units. Select the Add –advmethods checkbox if you want to run beta work units. Leave the Client Options at the bottom as they are.

6. If you have a video card that is capable, select the Enable GPU folding option. All Nvidia cards 8800 series and up are capable of folding, and Nvidia 400/500 series cards work best. ATI HD 2000 series and up also support folding, but it is not currently recommended with GPU Tracker (for ATI users, try the new F@H version 7 client). To set up GPU folding, either click Autodetect GPUs button or you can choose to set it up manually. First, select the Enable GPU0 checkbox. If you are running an Nvidia 400 or 500 series card, select the GPU3 client. For non-Fermi cards, leave it blank. Typically you don’t need to force GPU selection. Finally, select the Add –advmethods checkbox if you wish to run beta work units. Repeat this process if you want to run F@H on multiple cards.

Note: It is recommended you update to the latest driver version of your video card for GPU folding.
 
7. Now we need to configure your username and team number. Click on the Tracker Settings tab at the top of the Configuration window.

Redline Folding @ OC3D  

Under Name, type in the same name you used in Step 1. Type in 98860 for the team number (this is Redline @ OC3D’s number) and finally copy + paste the passkey you obtained in Step 1 in the Passkey box. Click Apply and make sure your name and team number appear at the bottom of the main GPU Tracker window. You can now click Start all Clients to begin folding.

8. As you can see, the Tracker has many other options you can use to get the most out of F@H. This guide only covers the basics to help you get folding right away, but feel free to play with these settings or ask in the forum if you have any questions about these.


PS3 Client

Sony’s Playstation 3 can also run Folding@Home! If you have PS3 system version 1.6 or later, there will be a F@H icon in the Network column of the main PS3 menu. Simply configure it to use whatever folding name you want and team 98860.


As always, if you have any questions, feel free to ask them in the Redline Folding at OC3D forum. We have a very active team and there is always somebody who will be willing and able to help you.

That is it! You are now folding with the rest of us for team 98860: Redline @ OC3D. Your computer is helping to cure disease using your idle computing time. Welcome to the team!

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