Thanks for the informative reply Jason. :)
On 2 June 2013 05:21, Jason Swails <jason.swails.gmail.com> wrote:
> On Sat, Jun 1, 2013 at 11:47 PM, ET <sketchfoot.gmail.com> wrote:
>
> > Hi,
> >
> > Apologies if this question has been asked before, but I could not find an
> > answer when I searched.
> >
> > I wanted to know which compiler gives the best code performance for AMBER
> > 12. I have compiled with both intel C++ & Fortran and GNU.
> >
> > There are less variations in the diff file using Gnu. I assume because
> the
> >
> > benchmark was run on an installation compiled with GNU?
> >
>
> Yes and no. I always use the Intel compilers, since the Fortran compiler
> was known to provide faster executables (this is most apparent for pmemd on
> CPUs, where the code was written to take advantage of vectorization
> instructions that ifort tends to catch pretty well). I'm not sure if
> anybody has done a test on recent gfortran vs. recent ifort: my instinct is
> that the difference is not very pronounced.
>
> There are a couple failures we 'know' about with the Intel compiler (those
> should be going away for the next version of Amber, but we've just kind of
> accepted them as innocuous). But both the Intel and GNU compilers get
> tested thoroughly with released code.
>
>
> >
> > I am specifically interested in CUDA optimisation. Is there any benefit
> to
> >
> > using compilers from the Portland group?
> >
>
> No. In fact, I don't know that the Amber build supports CUDA + PGI. All
> of the cuda performance comes from nvcc, so the choice of compiler is
> irrelevant here. CPU compilers don't build code that runs on the GPU, and
> with pmemd.cuda everything is run on the GPU. You could just as easily
> rewrite the CPU part in Python or bash with minimal loss of performance ;).
>
> HTH,
> Jason
>
> --
> Jason M. Swails
> Quantum Theory Project,
> University of Florida
> Ph.D. Candidate
> 352-392-4032
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Received on Sat Jun 01 2013 - 21:30:02 PDT
