On Fri, May 18, 2012 at 8:02 PM, Mohammad Mirzadeh <mirzadeh at gmail.com>wrote:
> Yes, I'm looking at weak scalability right now. I'm using BiCGSTAB with > BoomerAMG (all default options except for rtol = 1e-12). I've not looked > into MF/s yet but I'll surely do to see if I'm having any problem there. So > far, just timing the KSPSolve, I get [0.231, 0.238, 0.296, 0.451, 0.599] > seconds/KSP iteration for p=[1, 4, 16, 64, 256] with almost 93K nodes > (matrix-row) per proc. Which is not bad I guess but still increased by a > factor of 3 for 256 proc. Problem is, I don't know how good/bad this is. In > fact I'm not even sure that is a valid question to ask since it may be very > problem dependent. > > Something I just though about, how crucial is the matrix structure for KSP > solvers? The nodes have bad numbering and I do partitioning to get a better > one here. > Did you look at the number of iterates? Matt > > On Fri, May 18, 2012 at 4:47 PM, Matthew Knepley <knepley at gmail.com>wrote: > >> On Fri, May 18, 2012 at 7:43 PM, Mohammad Mirzadeh <mirzadeh at >> gmail.com>wrote: >> >>> I see; well that's a fair point. So i have my timing results obtained >>> via -log_summary; what should I be looking into for MatMult? Should I be >>> looking at wall timings? Or do I need to look into MFlops/s? I'm sorry but >>> I'm not sure what measure I should be looking into to determine scalability. >>> >> >> Time is only meaningful in isolation if I know how big your matrix is, >> but you obviously take the ratio to look how it is scaling. I am >> assuming you are looking at weak scalability so it should remain >> constant. MF/s will let you know how the routine is performing >> independent of size, and thus is an easy way to see what is happening. It >> should scale like P, and when that drops off you have >> insufficient bandwidth. VecMDot is a good way to look at the latency of >> reductions (assuming you use GMRES). There is indeed no >> good guide to this. Barry should write one. >> >> Matt >> >> >>> Also, is there any general meaningful advice one could give? in terms >>> of using the resources, compiler flags (beyond -O3), etc? >>> >>> Thanks, >>> Mohammad >>> >>> On Fri, May 18, 2012 at 4:18 PM, Matthew Knepley <knepley at >>> gmail.com>wrote: >>> >>>> On Fri, May 18, 2012 at 7:06 PM, Mohammad Mirzadeh <mirzadeh at >>>> gmail.com>wrote: >>>> >>>>> Hi guys, >>>>> >>>>> I'm trying to generate scalability plots for my code and do profiling >>>>> and fine tuning. In doing so I have noticed that some of the factors >>>>> affecting my results are sort of subtle. For example, I figured, the other >>>>> day, that using all of the cores on a single node is somewhat (50-60%) >>>>> slower when compared to using only half of the cores which I suspect is >>>>> due >>>>> to memory bandwidth and/or other hardware-related issues. >>>>> >>>>> So I thought to ask and see if there is any example in petsc that has >>>>> been tested for scalability and has been documented? Basically I want to >>>>> use this test example as a benchmark to compare my results with. My own >>>>> test code is currently a linear Poisson solver on an adaptive quadtree >>>>> grid >>>>> and involves non-trivial geometry (well basically a circle for the >>>>> boundary >>>>> but still not a simple box). >>>>> >>>> >>>> Unfortunately, I do not even know what that means. We can't guarantee a >>>> certain level of performance because it not >>>> only depends on the hardware, but how you use it (as evident in your >>>> case). In a perfect world, we would have an abstract >>>> model of the computation (available for MatMult) and your machine (not >>>> available anywhere) and we would automatically >>>> work out the consequences and tell you what to expect. Instead today, >>>> we tell you to look at a few key indicators like the >>>> MatMult event, to see what is going on. When MatMult stops scaling, you >>>> have run out of bandwidth. >>>> >>>> Matt >>>> >>>> >>>>> Thanks, >>>>> Mohammad >>>>> >>>> >>>> >>>> >>>> -- >>>> What most experimenters take for granted before they begin their >>>> experiments is infinitely more interesting than any results to which their >>>> experiments lead. >>>> -- Norbert Wiener >>>> >>> >>> >> >> >> -- >> What most experimenters take for granted before they begin their >> experiments is infinitely more interesting than any results to which their >> experiments lead. >> -- Norbert Wiener >> > > -- What most experimenters take for granted before they begin their experiments is infinitely more interesting than any results to which their experiments lead. -- Norbert Wiener -------------- next part -------------- An HTML attachment was scrubbed... URL: <http://lists.mcs.anl.gov/pipermail/petsc-users/attachments/20120518/64764d49/attachment.htm>
