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发表于 2013-2-6 18:03:43
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本帖最后由 cuihao 于 2013-2-24 20:52 编辑
IBM helped you out in customizing the protein-prediction algorithms for various platforms. Can you tell us how much they contributed?
IBM帮你们把蛋白质预测算法移植到了不同的平台上。请您谈谈他们提供了多大帮助。
Ram: All the customisation was done by IBM engineers. We just gave them the original software and ran sanity checks on the output. I’m a strong free software and anti IP proponent, to the degree that I encourage commercial use without restrictions on the software (people can always use the public domain versions if they want to).
Ram:所有的移植工作都是都是由IBM工程师完成的。我们只是提供了原始的软件,并对程序结果进行适当的检验。我鼓励无条件的商业化使用我的软件(人们只要有意愿,就可以随便使用公有领域中发布的版本),在这个角度上,我是个坚定的自由软件支持者和反版权人士。
How much time did you save by using the World Community Grid’s infrastructure compared to if you would’ve set it up all on your own, like other projects do?
比起独立完成(就像其他项目一样),利用WCG节省了多少时间呢?
Ram: IBM took about six months or so to port our software, so I presume it would’ve required that kind of an investment. Keep in mind that they had a lot of prior experience with BOINC. IBM now maintains the code and does the PR and runs the predictions for us. I’d say this would be a full time programmer/sysadm type of person and if I had that extra money, I’d rather spend it on someone doing the basic research.
Ram:IBM花了大约半年来移植软件,所以我假定这部分投资是必需的。别忘了他们有不少和BOINC打交道的经验。现在,IBM负责维护代码、搞公关并为我们运行预测程序。我要说的是,找一个全职的程序员或系统管理员大概也能完成这些事。但要有这闲钱,我宁愿雇人来搞基础研究。
If there are flaws about BOINC, which would you like to be addressed first?
如果说BOINC有什么缺陷,您首先想到了什么呢?
Ram: I can’t think of any in the way we did it with IBM, but without IBM, the PR machine has to be powerful to get people on board. It’s more than just recruiting people, but also motivating them as IBM does with badges and giving them a sense of community and providing a support infrastructure. This is hard for a research lab to do on their own (it can be done, but is it really the best use of our talents is the questions).
Ram:在和IBM合作的过程中,我实在想不出什么问题。要是没了IBM,非得找个强大的公关才能吸引人气。公关不仅仅是召集人,还要像IBM那样激发他们的热情,搞点奖励、给大家一种集体荣誉感并提供 support infrastructure。这些事单靠实验室很难完成(其实也能完成,但把我们的智慧耗费在这种事情上大概不怎么值得)。
Programming and debugging is an iterative process. Looking at your sourcecode-repository, how many releases of the software were necessary until you got the cow flying?
编程和调试是个反复的过程。看看你们的源代码库,在确定万事具备之前,你们发布过多少个版本呢?
Ram: For this case, internally we probably had about 10 or so iterations in total, but the basic science part of the software is something that has evolved over 18 years.
Ram:对于目前这个软件,内部发布的大概有10个。但要追溯软件的基础的科学部分,可能已经演变了至少18年。
How did you do beta-testing, did you use the publicly available beta-projects at WCG? Or, were you actually just doing it in your lab?
你们是怎么做 beta 测试的?是使用的 WCG 中公开的 beta 测试项目机制,还是自己在实验室里做?
Ram: It was mostly in our group. We just submitted sequences for which we knew the answers and we did a dry run initially with the same sequences.
Ram:大部分是我们小组自己搞的。我们仅仅是提交已经知道结果的序列,用同样的序列进行测试。
I’m curious there – were these structures predicted by other algorithms or was that done the hard way, using X-ray crystallography?
我很好奇——这些序列的结果是使用其他算法得到的,还是使用更复杂的X射线结晶学方法得到的?
Ram: These were done the hard way, at the bench. These are our gold standard for when we know we’re right or wrong, so we benchmark our methods against all this. When we did the rice project, we did sequences with known answers to see how well things would work and that there was no chance of anything going wrong.
Ram:在实验室里利用复杂的方法得到的。这些结果是判断方法正确性的黄金标准,所以我们把每个数据都测试了一遍。搞水稻项目时,我们把所有已知序列都做了测序,以检查运行情况,并确保不会出现任何问题。
How was is like getting in touch with the community? Was the feedback helpful? How many people from your team were actually dealing with the community?
和志愿者团体交流的感觉如何?他们的反馈信息有用吗?您的团队中又有多少人实际负责和志愿者打交道?
Ram: At its peak, we had 3 people dealing with the community, our sysadm and project lead Michal Guerquin, our programmer and scientist Ling-Hong Hung, and myself. Opening our software to the Grid and the community definitely presented some challenges, which I believe will be the focus of our first paper. An interesting tangent of that is that we’ve had to port some of our analysis software to work on GPUs so we could handle all this data. So some good technological developments here that we’ll be writing about shortly.
Ram:最多的时候,我们有三个人负责和志愿者团体打交道:系统管理员兼项目领导 Michal Guerquin,程序员和科学家 Ling-Hong Hung,以及我本人。向 WCG 和志愿者团体公开我们的软件确实带来了一些挑战,我认为这会成为我们第一份论文的重点。扯点有趣的题外话,我们曾不得不移植一些分析软件,使其在GPU上工作,这样我们就能处理所有这样的数据。所以还会简要写一些有关这里的优秀技术开发的内容。
A lot of people are concerned about “Frankenfood”. Your project’s website explicitly states that this is not about genetic engineering, but about finding the most nutritious rice-strains for interbreeding with other rice-crops. Is there anything you’d like to explain to people who are still concerned?
许多人都很关注“转基因食品”(原文“Frankenfood”是贬义的说法)的问题。你们的项目主页明确说明,此项目的目的是寻找用于杂交的最具营养的水稻品种,与基因工程无关。但有些人仍心存疑虑,对他们您有什么要说明的吗?
Ram: We’re simply extending what farmers have been doing for millenia in a more rational way, and also what has been going on in nature for billions of years. The problem to us is scientific and all knowledge that is produced (which from our end will be completely free and transparent) can be used in various ways according to the will of the people. But we have governments and politicians to handle the deeper societal implications. What I mean by this is that people should petition their representatives, as they are doing successfully in many parts of the world, to decide where to go with genetically modified organisms, which I see as ultimately having a socioeconomic/political solution.
Ram:同样的事情,农民们已经做了上千年,自然界中更是持续了上亿年,我们只是用科学的方法拓展了它。我们关心的是科学问题,所有现有的知识(在我们看来都是自由和透明的)因人的意志不同可以有各种用途。至于社会影响,还有我们的政府和政治家应对。我的意思是,民众应当向他们的代表提出请求(因为他们是许多领域中的佼佼者),以决定转基因食品的未来。我认为这就是社会经济学/政治上的最终解决方案。
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