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
|