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http://folding.stanford.edu/English/FAQ-NVIDIA-GPU3
A Brief History of FAH: From Tinker to Gromacs to GPU to GPU2 to GPU3
NVIDIA GTX 480
Introduction
Since 2000, Folding@home (FAH) has lead to a major jump in the capabilities of molecular simulation. By joining together hundreds of thousands of PCs throughout the world, calculations, which were previously considered impossible, have now become routine. FAH has targeted the study of protein folding and protein folding diseases, and numerous scientific advances have come from the project.
In 2006, we began looking forward to another major advance in capabilities. This advance utilizes the new, high performance Graphics Processing Units (GPUs) from ATI to achieve performance previously only possible on supercomputers. With this new technology, as well as the new Cell processor in Sony's PlayStation 3, we will soon be able to attain performance on the 100 gigaflop scale per computer. With this new software and hardware, we will be able to push Folding@home a major step forward.
In 2008, we have developed a second generation GPU core (GPU2). This core is much more sophisticated than the original, with higher reliability, ease of use, and much more scientific calculation capabilities.
Our goal is to apply this new technology to dramatically advance the capabilities of Folding@home, applying our simulations to further study of protein folding and related diseases, including Alzheimer's Disease, Huntington's Disease, and certain forms of cancer. With these computational advances, coupled with new simulation methodologies to harness the new techniques, we will be able to address questions previously considered impossible to tackle computationally, and make even greater impacts on our knowledge of folding and folding related diseases.
Folding@home debuts with the Tinker core (October 2000)
In October 2000, Folding@home was officially released. The main software core engine was the Tinker molecular dynamics (MD) code. Tinker was chosen as the first scientific core due to its versatility and well laid out software design. In particular, Tinker was the only code to support a wide variety of MD force fields and solvent models. With the Tinker core, we were able to make several advances, including the first folding of a small protein starting purely from sequence (subsequently published in Nature).
A major step forward: the Gromacs core (May 2003)
After many months of testing, Folding@home officially rolled out a new core based on the Gromacs MD code in May 2003. Gromacs is the fastest MD code available, and likely one of the most optimized scientific codes in the world. By using hand tuned assembly code and utilizing new hardware in many PCs and Intel-based Macs (the SSE instructions), Gromacs was considerably faster than most MD codes by a factor of about 10x, and approximately a 20x to 30x speed increase over Tinker (which was written for flexibility and functionality, but not for speed).
However, while Gromacs is faster than Tinker, it has limits to what it can do; for example, it does not support many implicit solvent models, which play a key role in our folding simulations with Tinker. Thus, while Gromacs significantly sped certain calculations, it was not a replacement for Tinker, and so the Tinker core will continue to play an important role in Folding@home (including a recent paper in Science). For these reasons, points for Gromacs WUs were set to be consistent with points for Tinker WUs, as both play an important role in the science of FAH. Moreover, we switched the benchmark machine to a 2.8 GHz Pentium 4 (from a 500MHz Celeron) in order to allow us to fairly benchmark these types of WUs (as the benchmark machine needed to have hardware support for SSE).
The next major step forward: Streaming Processor cores (September 2006)
Much like the Gromacs core greatly enhanced Folding@home by a 20x to 30x speed increase via a new utilization of hardware (SSE) in PCs, in 2006, Folding@home has developed a new streaming processor core to utilize another new generation of hardware: GPUs with programmable floating-point capability. By writing highly optimized, hand tuned code to run on ATI X1900 class GPUs, the science of Folding@home will see another 20x to 30x speed increase over its previous software (Gromacs) for certain applications. This great speed increase is achieved by running essentially the complete molecular dynamics calculation on the GPU; while this is a challenging software development task, it appears to be the way to achieve the highest speed improvement on GPU's.
In addition, through collaboration with Pande Group, Sony has developed an analogous core for the PS3's Cell processor (another streaming processor), which should see a significant speed increase for the science over the types of calculations we could previously do on a x86/SSE Gromacs core as well. Following what we did with the introduction of Gromacs, we will now switch benchmark machines and include an ATI X1900XT GPU in order to be able to benchmark streaming WUs (which cannot be run on non-GPU machines). This machine will also benchmark CPU units (which continue to be of value since GPUs work only for certain simulations) without using its GPU.
The second generation GPU core, aka GPU2, for ATI hardware (April 2008)
After running the original GPU core for quite some time and analyzing its results, we have learned a lot about running GPGPU software. For example, it has become clear that a GPGPU approach via DirectX (DX) is not sufficiently reliable for what we need to do. Also, we've learned a great deal about GPU algorithms and improvements. One of the really exciting aspects about GPU's is that not only can they accelerate existing algorithms significantly, they get really interesting in that they can open doors to new algorithms that we would never think to do on CPUs at all (due to their very slow speed on CPUs, not but GPU's).
After much effort, we have taken all we've learned about GPUs from the first generation client and produced a second generation client. This new client appears to be faster, more reliable, and has more scientific functionality. The preliminary results so far from it look very exciting, and we're excited to now open up the client for FAH donors to run.
The second generation GPU core (GPU2) for NVIDIA (June 2008)
In collaboration with NVIDIA, we have released a GPU2 core for NVIDIA hardware.
The third generation GPU core (GPU3) for NVIDIA (May 2010)
Due to its great computational abilities, our GPU2 client has had a great scientific impact so far. In our most recent FAH paper (also see the movie), the GPU clients play a star role in allowing Folding@home to push to unprecedented levels, simulating protein folding on the millisecond timescale in an atomistic model.
GPU3 brings several key new features to Folding@home. In particular, GPU3 will allow for greatly enhanced science: including more accurate models, new science can be done, 2x faster execution of the science, more stable simulations, OpenCL support for run time science optimizations, and greater flexibility for adding new scientific capability. This is accomplished through the use of the http://simtk.org/home/openmm/OpenMM GPU library (which originally came from FAH GPU code, but has been significantly enhanced by Simbios staff).
GPU3 also lays down the foundation for future incorporation of OpenMM's support of OpenCL, which will also bring some very important new scientific features, especially in terms of on-the-fly runtime optimizations of the scientific code. However, at the moment, OpenCL is not supported in the current GPU3 NVIDIA client.
General instructions
This web page will serve as the FAQ and Release Notes for this new client, and we will update this page as more information becomes available.
The FAH GPU Client installer should do everything one needs. It installs the new v6.x SysTray style client, as well as DLL files used by this new client. Download the client from the High Performance Client Download Page for folding experts. The Windows GPU Guide can help you install the GPU3 client.
Basic Requirements:
* a GeForce, Quadro, or Tesla card that supports CUDA (G80 or later for the most part)
* A CUDA 2.2+ capable driver, version 185.55 or newer is recommended. Or 195.62 for GTX 2xx cards (download the 195.62 driver for Win XP, Win XP 64 bit, Vista/Win7, and Vista/Win7 64 bit). 197.41 for GTX 4xx cards.
* Windows operating system (32 or 64 bit), XP or newer.
In some cases, donors have found problems with older drivers, so to be safe, we strongly recommend that donors use a more recent driver (197.45).
While the GPU3 client is not beta, the core is still a beta release and we expect there will be bugs, flaws, problems, etc. To minimize problems, we have been testing the cores extensively in house and they run well there. However, it's our experience that running in the controlled setup in our lab and running "out in the wild" are very different situations.
As in the use of any beta software, please make sure to back up your hard drive, and do not run this client on any machine which cannot tolerate even the slightest instability or problems.
下载链接：http://foldingforum.org/viewtopic.php?f=24&t=14671 |
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发表于 2010-5-26 07:11
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