> On Apr 28, 2017, at 11:40 AM, Roy Stogner <royst...@ices.utexas.edu> wrote:
> 
> 
> On Thu, 27 Apr 2017, Rossi, Simone wrote:
> 
>> The run times for 100 timesteps using AMR can be more than 10 times slower 
>> than when using a fine uniform grid.
>> For example, with a 16 x 16 x 16 uniform grid, 100 iterations take about 18 
>> seconds with a single processor.
> 
>> With AMR, using a 2 x 2 x 2 grid and 3 levels of refinement, 100 iterations 
>> take about 800 seconds.
> 
> I didn't really understand this sentence until I started to run your
> code to test possible libMesh optimizations - you're running 3 levels
> of refinement *per timestep*!?  That's pretty much guaranteed to be
> inefficient; for nearly any transient PDE solve, the solution is never
> going to change so much within a single time step that you'll want to
> use more than one AMR step.
> 
> We probably violate this rule of thumb in the examples, which we
> should fix to avoid misleading others, but in most cases you want to
> think "time steps per adaptive step", not the other way around.
> 
> (there are exceptions, but in those cases you have to also be
> exceptionally careful about how you do AMR; e.g. saving your previous
> time step's error indicator so you don't accidentally coarsen too
> soon)

I think what Simone wants is a "three level AMR grid", so that he is getting 
the same effective fine grid resolution with a 2x2x2 base grid as in the 
uniformly fine case.

What is the correct way to initialize such a mesh and maintain it in a 
time-dependent model?

Thanks,

-- Boyce

> I'm not complaining, though; your code really hammers the AMR code in
> libMesh, which is exactly what we need for optimization purposes.
> ---
> Roy
> 
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