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. 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 <[email protected]> wrote:
On Fri, May 18, 2012 at 7:06 PM, Mohammad Mirzadeh <[email protected]>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