On Mon, Sep 29, 2014 at 10:33 PM, xueqiaoup.gmail.com <xueqiaoup.gmail.com>
wrote:
> Dear Jason M. Swails:
> Thanks very much!
> I use AMBER12 and AMBERTOOLS12. The second GPU wokrs. I submit a 20ns job
> to the second GPU. It can run the job for short time (maybe stopped at 2ns
> or 3ns) without any error message. May it be the problem of the compiler?
>
No. It's most likely a problem with the GPU.
>
> I wonder whether there are some methods to submit 2 or more jobs to one
> GPU without evident speed
>
> decrease. One job just cost 500M of the total 5000M GPU memory. This may
> be a little waste of the
>
> computing resources.
>
No. You are equating total RAM with "computational power" and that is
just not true (as I said before). If a program makes efficient use of the
clock cycles of ANY processor (be it a GPU or a CPU) then forcing that
program to share clock cycles with another running program will ALWAYS hurt
performance.
Like I said before, total RAM has almost no impact on computational
performance -- it's the memory bus speed, processor speed, and available
instruction set that actually matters when it comes to performance.
HTH,
Jason
--
Jason M. Swails
BioMaPS,
Rutgers University
Postdoctoral Researcher
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Received on Tue Sep 30 2014 - 04:30:02 PDT
