Hi Oliver,
We do 400x400 box size refinements and classifications perfectly fine on
our (older) cluster nodes with 64Gb of RAM. However, I wouldn't buy a
machine with less than 128Gb of RAM nowadays. It's hardly saving you any
money, and pre-reading particles into RAM will help in reducing load on
the hard disk.
HTH,
Sjors

> 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
>> http://www2.mrc-lmb.cam.ac.uk/groups/scheres
>>
>


-- 
Sjors Scheres
MRC Laboratory of Molecular Biology
Francis Crick Avenue, Cambridge Biomedical Campus
Cambridge CB2 0QH, U.K.
tel: +44 (0)1223 267061
http://www2.mrc-lmb.cam.ac.uk/groups/scheres