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楼主: vmzy

[独立平台] [生命科学类] Folding@Home

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发表于 2008-6-9 01:24:46 | 显示全部楼层
N卡客户端。。先看效率再说,我关注G92与RV670的效率对比
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发表于 2008-6-9 05:14:24 | 显示全部楼层
游戏的效率对比容易找,FAH项目的对比就难了。
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 楼主| 发表于 2008-6-9 17:32:19 | 显示全部楼层
June 06, 2008
GPU1 has been retired, GPU2 for NVIDIA release nearing

Just a reminder: we've retired GPU1 today.  As of 9:30am pacific time, new assigns for the GPU1 client will go to 0.0.0.0.  We will keep the data server up for a few more days to collect old WU's, but we will repurpose that server in about a week (the deadline time on the GPU1 WU's was 6 days).

I'd like to personally thank all the GPU1 folders, whose work has lead to the GPU2 clients, for both ATI and NVIDIA.  Just as we turn the page on GPU1, we are nearing our open beta release for the GPU2/NVIDIA client.  If all goes well, we hope to have that available in a week.  I'll give an update if it looks like it will be delayed more than a week.
大意:
GPU1终止,GPU2 NVIDIA版即将发布

GPU1今天终止,任务分配服务器已经关闭。任务接收服务器将于一周后关闭。

感谢大家为GPU1所做的贡献。我们将在一周内发布GPU2 NVIDIA版客户端。

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发表于 2008-6-9 17:56:58 | 显示全部楼层
NV客户端终于要出了==
可惜我的88GTS反厂换新了,要是现在出只能用85GT跑了。。。
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发表于 2008-6-9 23:46:04 | 显示全部楼层
哦也
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 楼主| 发表于 2008-6-10 10:25:16 | 显示全部楼层
June 09, 2008
GPU2 auto core upgrade to v1.03

We've set an auto core upgrade to v1.03 for the GPU2 client.  The 1.03 core has much better behavior for R600 cards and in general seems much more stable and better behaved than previous cores.
大意:
GPU2计算内核(自动)升级至1.03

新版改进了与R600的兼容性。更加稳定,性能得到改善。

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发表于 2008-6-10 15:34:24 | 显示全部楼层
原帖由 vmzy 于 2008-6-9 17:32 发表
June 06, 2008
GPU1 has been retired, GPU2 for NVIDIA release nearing

Just a reminder: we've retired GPU1 today.  As of 9:30am pacific time, new assigns for the GPU1 client will go to 0.0.0.0.  We wil ...


一周内? 好期待
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 楼主| 发表于 2008-6-11 10:36:14 | 显示全部楼层
根据历史经验来看,周五(北京时间周六)发布N版GPU的可能性很大。
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发表于 2008-6-11 11:34:49 | 显示全部楼层
开始期待着周6的到来。。
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发表于 2008-6-11 23:35:03 | 显示全部楼层
实习忙啊……周日回来瞄一眼
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 楼主| 发表于 2008-6-13 15:48:35 | 显示全部楼层
June 12, 2008
GPU2 PPD increase

With new revisions to the GPU2 core code, the GPU2 code is doing more science per ever in the same amount of time.  In the spirit of having the points equate to how much science is being done, we are going to increase the PPD of the GPU2 benchmark machine (ATI 3850 board -- see the FAQ for details) to 1500 PPD.  We will revalue the most recent WU's (472X) and all future WU's will use this new PPD for benchmarking.

大意:
GPU2提高标准积分

新版内核性能得到改善,故将标准积分调整至1500(详见FAQ页面)。近期(472X)和将来的任务将会按照新计分标准给分。

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发表于 2008-6-14 03:48:27 | 显示全部楼层
为即将来到的GPU计算风暴做准备。调高GPU2的分数,提高GPU FOLDER的积极性。这回的商业运作的味道越来越重了
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发表于 2008-6-14 09:45:48 | 显示全部楼层
呵呵,我倒觉得对项目来说,一定的市场运作还是有意义的:)
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 楼主| 发表于 2008-6-16 17:18:53 | 显示全部楼层
June 15, 2008
What does the SMP core do?

Our SMP core is very different than the way other distributed computing projects handle multi-core CPU's, and I thought it might be interesting for the FAH community to hear about the differences, pro and con.  As I think most people interested in computers know, Moore's law stating that the transistor count in CPUs will double every 1.5 years has continued for decades.  Most people think of Moore's law in terms of the speed of CPU's, but this isn't what Moore originally had in mind.  In the past, more transistors have lead to greater CPU speeds, but that has essentially ended (at least for traditional CPU's) a few years ago.  

But if Moore's law is still marching along (as it is), what do all those transistors do?  Over the last few years, more transistors have translated into more CPU cores, i.e. more CPUs on a chip.  While this is not what we wanted, this is perhaps not necessarily a disaster, if one can use these multiple CPUs to get faster calculations.  If we simply do more calculations (i.e. multiple Work Units, or WU's, simultaneously) not faster calculations (a WU completed in less time), distributed computers will run into the same problems that face supercomputers: how to scale to lots and lots of processors -- i.e. how can we use all these processors to do a calculation faster over all.

In FAH, we've taken a different approach to multi-core CPUs.  Instead of just doing more WU's (eg doing 8 WU's simultaneously), we are applying methods to do a single WU faster.  This is typically much more valuable to a scientific project and it's important to us.  However, it comes with new challenges.  Getting a calculation to scale to lots of cores can be a challenge, as well as running complex multi-core calculations originally meant for supercomputers on operating systems not meant for this (eg Windows).

Right now, our SMP client seems to be running fairly well under Linux and OSX -- operating systems based on UNIX, as is found on supercomputers.  We use a standard supercomputing library (MPI) to run these WU's and MPI behaves well on Unix-based machine.  MPI does not run well on Windows and we've been running into problems there.  However, as Windows MPI implementations mature, our SMP/Windows app will behave better.  Along the way, we also have a few tricks up our sleeve which may help as well.  However, if we can't get it to run as well as we'd like on Windows, we may choose to overhaul the whole code, as we did with the GPU1 client (which was really hard to run).

We're very excited about what the SMP client has been able to do so far.  One of our recent papers (#53 in our papers web site http://folding.stanford.edu/English/Papers) would have been impossible without the SMP client and represents a landmark calculation in the simulation of protein folding.  We're looking forward to more exciting results like that in the years to come!

大意:
讲解了SMP客户端的特点

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发表于 2008-6-17 15:36:12 | 显示全部楼层
原帖由 Youth 于 2008-6-14 09:45 发表
呵呵,我倒觉得对项目来说,一定的市场运作还是有意义的:)


只是你没有领教过NVIDIA的商业手段和“高尚”的商业道德。和当年的Intel比起来,Nvidia有过之而无不及。你如果没有上船,只是看着显卡的更新换代,那不会有什么感觉,但如果你刚买了没有多久,他就推出一项新功能说,他不买我的新产品就不能使用新功能。而实际上老产品并非不能支持新功能,虽然速度也许慢点,但其实根本不影响效果。他只是他希望你掏银子给他,不要继续用老产品,或者掏钱给AMD,而不管你刚刚买了还不到半年。
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