Hi CharlesAs long as you have amber 18 along with amber tools 19, cuda 10 or greater and apply the latest updates when you run configure you should get an executable that works equally well on RTX20xx and GTX10xx cards.Gtx1660 I see no reason why it wouldn't work but haven't tried myself yet so no word on performance.All the bestRoss
-------- Original message --------From: Charles-Alexandre Mattelaer <camattelaer01.gmail.com> Date: 10/5/19 17:11 (GMT-05:00) To: AMBER Mailing List <amber.ambermd.org> Subject: Re: [AMBER] RTX 2080 slower then 1080 Ti with pmemd 18 ? Hi RossSorry to pick this old thread up, but does the statement '... so you willneed multiple executables if you have mixed hardware.' still hold for CUDA10? I've read CUDA 10 supports both Turing and Pascal (and othersobviously) but without any concern or warning that patching is required. Weonly have gtx cards, but would like to expand and since gtx has becomerather scarce are looking towards rtx cards (or the newer gtx 1660 butstill no word on compatibility).Thanks in advance and kind regards!Charles-Alexandre MattelaerOp wo 21 nov. 2018 21:37 schreef Ross Walker <ross.rosswalker.co.uk>:> Hi Alain,>> You will need a patched version of AMBER to get full performance on RTX> cards. That is still being worked on. In the meantime edit the following> line in $AMBERHOME/src/pmemd/src/cuda/gpu_types.h>> static const int PMENONBONDFORCES_THREADS_PER_BLOCK = 640;>> Change to>> static const int PMENONBONDFORCES_THREADS_PER_BLOCK = 512;>> Then recompile. Note this will run slower on non RTX2080(TI) cards so you> will need multiple executables if you have mixed hardware.>> Also use CUDA 9.2 for the RTX cards.>> All the best> Ross>> > On Nov 21, 2018, at 14:24, Alain Chaumont <chaumont.unistra.fr> wrote:> >> > Dear all,> > we currently are testing our new RTX 2080 cards (MSI Geforce Seahawk RTX> 2080). However it seems that they are about 2% slower then our GTX 1080Ti> Cards (Similar model).> > However from the benchmarks on the AMBER webpage I find that the RTX> 2080 should be about 10 - 20 % faster then GTX 1080Ti. Is this correct? If> so any ideas why this is not the case for us? Is there some “trick” to use> during compilation or so? Or are they done with some patches of AMBER which> are not yet public?> >> > Thanks a lot in advance> >> > Alain Chaumont> >> > P.S. We are currently using CUDA 9.0 . The size of the systems is about> 130 000 atoms.> >> >> >> > Universite de Strasbourg> > 4, rue B. Pascal> > 67000 Strasbourg> > France> >> >> >> > _______________________________________________> > AMBER mailing list> > AMBER.ambermd.org> > http://lists.ambermd.org/mailman/listinfo/amber>> _______________________________________________> AMBER mailing list> AMBER.ambermd.org> http://lists.ambermd.org/mailman/listinfo/amber>_______________________________________________AMBER mailing listAMBER.ambermd.orghttp://lists.ambermd.org/mailman/listinfo/amber
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Received on Sun Oct 06 2019 - 13:30:02 PDT
