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Hello everybody, I do not find the download and install link of gpu relion version. Please, Could you send the request information to me? Thank you Hugo On 14/06/16 12:25, Alberto Riera wrote: > > Hi Erik, > > Thank you for the advice regarding the cards. It is actually true that > you usually do not care if one pixel in Fallout 4 does not render > properly. We will go for reference cards in this build since, sadly, I > will not use it for gaming. In principle money wise we are OK for a > single high-end system and the idea is to install 4 1080 on it. I am > still thinking about the chassis, though. Maybe it is better to go for > a 14 or 10 core Xeon with 128GB ECC, it should be more reliable than a > squeezed I7 (and run cooler) and it could be expanded in the future > with more RAM and another CPU. A system like this would be, with 14 > cores, around 10K. > > Regarding the distribution Ubuntu seems actually a very nice option > and I am much more familiar with this branch than with others. I am > afraid that maybe we will need to use RedHat in here, but let´s see... > > Best! > > Alberto > > > On 14/06/2016 11:09, Erik Lindahl wrote: >> Hi Alberto, >> >> We typically use Ubuntu (16.04LTS right now), but we've never had any >> compatibility issues - the NVIDIA drivers work fine for all modern >> Linux distros. >> >> The problem with overclocking is that vendors optimise the cards for >> graphics where you probably don't care of one pixel out of a billion >> has an incorrect color, and even with a high-end game the card will >> only run at 100% utilisation for very short periods. For computing, >> the situation is pretty much the opposite: Cards might be running at >> 100% 24/7/365, and we don't want to accept a single error. There have >> been many instances where vendors have been to aggressive, so to us >> it's simply not worth the risks of random errors to get 5-10% better >> performance. >> >> Many of the gaming cards actually have better cooling than the >> reference/Founder's edition if you only use a single card - they >> often pull in the air from the long side of the card and push it out >> on the other to improve the airflow. This works great... provided you >> only have a single card in the machine. However, with 2-4 cards it >> is important to get the hot air to flow out of the box rather than >> circulate inside it - for a server it would even be disastrous since >> front-to-back is the only possible way for the cooling air to flow. >> >> Finally, in particular for autorefine it will be beneficial >> (memory-wise) to have two cards, since we can put one model on each >> card in that case. Thus, if you are budget-limited, it will usually >> be a much better idea to get two 1070 cards than a single 1080. >> >> Cheers, >> >> Erik >> >> >> On Tue, Jun 14, 2016 at 10:55 AM, Alberto Riera >> <[log in to unmask] <mailto:[log in to unmask]>> wrote: >> >> Thank you all for the great advice! >> >> I am very glad to hear that a gaming rig should actually be >> enough :) 128GB of RAM for an I7 is actually overkill but with >> the new memories luckily it turns out to be possible. About the >> edition of the cards, I have always used overclocked EVGAs >> instead of the reference ones (only EVGA) but since actually the >> cooling system is quite different we will stick with the standard >> versions for this build. On a separate note: what operating >> system are you using right now? It would make sense to have the >> same distro in here :) >> >> Best! >> >> Alberto >> >> >> On 13/06/2016 21:45, Erik Lindahl wrote: >>> PS: >>> >>> I'll second Sjors and emphasize that *currently* the initial GPU >>> version becomes a bit too memory hungry beyond 450^2 pixels. >>> >>> 1) There are a few tricks that save a factor 2 already know, but >>> it can affect quality and is not something we recommend. >>> >>> 2) While this is NOT a promise, we have pretty good hopes we can >>> fix the memory consumption completely and make all images work >>> on consumer hardware in the future. >>> >>> Cheers, >>> >>> Erik >>> >>> Erik Lindahl <[log in to unmask] >>> <mailto:[log in to unmask]>> >>> Professor of Biophysics >>> Science for Life Laboratory >>> Stockholm University & KTH >>> Office (SciLifeLab): +46 8 524 81567 <tel:%2B46%208%20524%2081567> >>> Cell (Sweden): +46 73 4618050 <tel:%2B46%2073%204618050> >>> Cell (US): +1 267 3078746 <tel:%2B1%20267%203078746> >>> >>> >>> On 13 juni 2016, at 22:31, Erik Lindahl <[log in to unmask]> >>> wrote: >>> >>>> Hi Oliver et al., >>>> >>>> This far we've managed well even with 64GB on a workstation >>>> even when working with ribosomes. The memory requirements won't >>>> be proportional to the number of cards. >>>> >>>> When it comes to value for money, the king will be the 1070 >>>> cards released this weekend for $450. I haven't forgotten my >>>> promise to create a Web page with more info, but we got a bit >>>> delayed finishing a paper - we will have this online with the beta. >>>> >>>> However, one important thing if anybody wants to get hardware >>>> right away: Stay away from all overclocked "gaming" cards, and >>>> if you want to use multiple cards in a machine you should stick >>>> to the reference "Founder's edition" cards. Long story, but it >>>> has to do with the cooling airflow. >>>> >>>> We'll create recommendations for cheap workstations with 2 >>>> cards (~$1500), high-end workstations with 4 cards ($5-7k), and >>>> special cluster nodes with 4 cards ($6-8k). Note that most >>>> standard nodes will *not* accept consumer cards, so please >>>> don't rush out and buy any model prematurely, but wait 2-3 days >>>> and we'll have numbers & specs! >>>> >>>> >>>> Having said that, the whole point of this is that we want to >>>> make cryo-EM computing ridiculously cheap, and I think you'll >>>> be happy :-) >>>> >>>> Cheers, >>>> >>>> Erik >>>> >>>> Erik Lindahl <[log in to unmask] >>>> <mailto:[log in to unmask]>> >>>> Professor of Biophysics >>>> Science for Life Laboratory >>>> Stockholm University & KTH >>>> Office (SciLifeLab): +46 8 524 81567 <tel:%2B46%208%20524%2081567> >>>> Cell (Sweden): +46 73 4618050 <tel:%2B46%2073%204618050> >>>> Cell (US): +1 267 3078746 <tel:%2B1%20267%203078746> >>>> >>>> >>>> On 13 juni 2016, at 20:36, Oliver Clarke <[log in to unmask]> >>>> wrote: >>>> >>>>> Hi Sjors, >>>>> >>>>> We are currently in the same situation - trying to figure out >>>>> the optimal GPU-workstation setup for a given budget. >>>>> >>>>> How much RAM is too much? That is, if using dual 1080s, how >>>>> much RAM does one have to have to ensure that the max box size >>>>> will be limited by the GPU memory, rather than the amount of >>>>> RAM - because I am presuming that getting any more RAM than >>>>> that will be a waste (except if you want to preread all your >>>>> particles into RAM)? >>>>> >>>>> Cheers, >>>>> Oliver. >>>>> >>>>> On Mon, Jun 13, 2016 at 2:04 PM, Sjors Scheres >>>>> <[log in to unmask]> wrote: >>>>> >>>>> Hi Alberto, >>>>> >>>>> Please be advised that hopefully this week we (read Erik >>>>> Lindahl) will >>>>> come out with much more detailed information. I'll also >>>>> speak about this >>>>> at the GRC in Hong Kong. Meanwhile, have a look at my talk >>>>> at the CCPEM >>>>> Spring Symposium here: >>>>> https://sas.stfc.ac.uk/vportal/index.jsp >>>>> >>>>> For small particles as the ones you mention, four 1080s >>>>> (or even 1070s) >>>>> will surely do. 128Gb of RAM will also be enough, so your >>>>> cheap machine >>>>> should be able to process all those data in a matter of >>>>> days. You can also >>>>> buy several of those gaming machines and tie them together >>>>> using MPI. I >>>>> don't have experience at all with EC2, so I'll let someone >>>>> else comment on >>>>> that. >>>>> >>>>> When you do larger systems (e.g. ribosomes at very high >>>>> mag, viruses, etc) >>>>> and the box size becomes larger than say 450x450 pixels, >>>>> then the >>>>> GPU-memory on the 1080s will become too small, and you'd >>>>> have to work with >>>>> the more expensive cards. For the larger box sizes you >>>>> would also need >>>>> more RAM (again becoming more expensive as you mention >>>>> yourself). But as >>>>> said, for the majority of cases (boxsize <400x400) your >>>>> 'cheap option' >>>>> should do extremely well. I'd also buy a fast (ssd) hard >>>>> disk with it, as >>>>> access to disk will quickly become a next bottleneck. >>>>> >>>>> HTH, >>>>> Sjors >>>>> >>>>> >>>>> >>>>> >>>>> >>>>> > Hello! >>>>> > >>>>> > I am Alberto, a postdoc from the DNA replication group >>>>> in Imperial College >>>>> > (London). I know that this has been discussed in before >>>>> but with the >>>>> > upcoming release of the new GPU ready Relion it seems >>>>> that the time for >>>>> > buying a new system has come and we still have a few >>>>> questions. Maybe you >>>>> > will be able to help :) >>>>> > >>>>> > In the lab we mainly work with protein complexes that >>>>> are around 1 million >>>>> > Dalton or a bit bigger, and in our latest >>>>> reconstructions we have used >>>>> > with around 300K particles (sorted from a 1.2 million >>>>> particle pool) to >>>>> > reach around 3.9A resolution. For this we have been >>>>> using a cluster but we >>>>> > wonder if, with the new Relion version, it would be >>>>> possible to move the >>>>> > task to a single workstation. There are different options: >>>>> > >>>>> > a) gaming computer with an I7 (10 cores) and up to 128GB >>>>> of RAM; this >>>>> > machine would have 4 GTX 1080 cards. This option would >>>>> be the cheapest, >>>>> > something like 5 o 6K should do it, but we cannot >>>>> increase the RAM any >>>>> > further, in fact, 128GB is already a bit over the top. >>>>> > >>>>> > b) workstation with a single xeon or a couple of CPUs. >>>>> With this we could >>>>> > go up to 36 cores, 1TB of RAM and the same 4 cards or >>>>> higher. However, it >>>>> > would be expensive. Actually, the starting configuration >>>>> with a single 16 >>>>> > core xeon and 128GB of RAM plus the cards would go for >>>>> around 10K >>>>> > >>>>> > c) we could continue using a cluster and try to >>>>> something like Amazon >>>>> > cloud, or a similar solution that offers GPU >>>>> acceleration. Has anybody >>>>> > tried this? >>>>> > >>>>> > d) We could go for any other approach that you >>>>> recommend, like pilling a >>>>> > few gaming computers and build our own cluster from them. >>>>> > >>>>> > Any advice will be much appreciated! >>>>> > >>>>> > Thanks, >>>>> > >>>>> > Alberto >>>>> > >>>>> >>>>> >>>>> -- >>>>> Sjors Scheres >>>>> MRC Laboratory of Molecular Biology >>>>> Francis Crick Avenue, Cambridge Biomedical Campus >>>>> Cambridge CB2 0QH, U.K. >>>>> tel: +44 (0)1223 267061 <tel:%2B44%20%280%291223%20267061> >>>>> http://www2.mrc-lmb.cam.ac.uk/groups/scheres >>>>> >>>>> >> >> -- >> Alberto Riera PhD >> Imperial College London >> Faculty of Medicine >> Institute of Clinical Sciences (CRB room 3006) >> Hammersmith Hospital Campus >> Du Cane Road >> London W12 0NN >> >> [log in to unmask] <mailto:[log in to unmask]> >> >> >> >> >> -- >> -- >> Erik Lindahl <[log in to unmask] <mailto:[log in to unmask]>> >> Professor of Biophysics, Dept. Biochemistry & Biophysics, Stockholm >> University >> Science for Life Laboratory, Box 1031, 17121 Solna, Sweden > > -- > Alberto Riera PhD > Imperial College London > Faculty of Medicine > Institute of Clinical Sciences (CRB room 3006) > Hammersmith Hospital Campus > Du Cane Road > London W12 0NN > > [log in to unmask] -- Hugo Muñoz Hernández, PhD student Centro de Investigaciones Biológicas CIB-CSIC Consejo Superior de Investigaciones Científicas C/ Ramiro de Maeztu, 9 28040 Madrid (Spain) http://www.cib.csic.es/es/grupo.php?idgrupo=47 Tel: +34 91 8373112 ext 4436, Lab.B-47