[petsc-users] Slow speed when using PETSc multigrid

TAY wee-beng zonexo at gmail.com
Fri Jun 8 14:35:29 CDT 2012


On 8/6/2012 12:06 AM, Jed Brown wrote:
> On Thu, Jun 7, 2012 at 4:56 PM, TAY wee-beng <zonexo at gmail.com 
> <mailto:zonexo at gmail.com>> wrote:
>
>     I looked at the manual but I'm not sure how to get better performance.
>
> *      ##########################################################*
> *      #                                                        #*
> *      #                          WARNING!!!                    #*
> *      #                                                        #*
> *      #   This code was compiled with a debugging option,      #*
> *      #   To get timing results run ./configure                #*
> *      #   using --with-debugging=no, the performance will      #*
> *      #   be generally two or three times faster.              #*
> *      #                                                        #*
> *      ##########################################################*
>
> I wonder if making this text bigger, red, bold, and blinking (which I 
> can't seem to do in this email) would increase the chances that you 
> read it.

Thanks for the reminder Jed, I was having segmentation fault earlier and 
hence I compile in debug mode to detect the error. I'll try out 
different options to determine the best options.
>
>       Also, what are the more common options to start with. Is there an appropriate C example? Some options are:
>
>     *PCMGSetLevels*   - how many lvls are appropriate?
>
>     PCMGSetCycleType -
>
>     PCMGSetNumberSmoothUp/down etc
>
> 1. Control this stuff using command line options. Recompiling to run a 
> different method was obsolete decades ago.
>
> 2. You need to understand a little about the math and a little about 
> the performance of each component in isolation. I recommend seeing how 
> time moves between different operations as you modify the algorithm.
>
> 3. Experiment with your machine and the methods. Learn which 
> configurations have good algorithmic performance (few iterations) and 
> which execute most efficiently.
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