Thanks Freddie. This clears up a lot.

On Thursday, June 13, 2019 at 4:54:04 PM UTC-7, Freddie Witherden wrote:
>
> Hi Joshua, 
>
> On 13/06/2019 18:29, Joshua Brinkerhoff wrote: 
> > /Question 1: How does the polynomial order affect the time step required 
> > for solution stability?/ 
>
> In a very broad sense dt ~ 1/p^2 and so if you increase the polynomial 
> order you will need to decrease the time-step accordingly. 
>
> > /Question 2: How does the polynomial order relate to the residuals 
> > produced in the tutorial and their convergence rate?/ 
>
> The polynomial order has no substantial impact on the rate of 
> convergence per-se.  However, it does have an impact on the minimum 
> residual which can be obtained (for a higher polynomial order enables 
> you to get closer to the true solution). 
>
> > /Question 3: Why do I see non-monotonic variation in the solution time 
> > for different polynomial orders?/ 
>
> The Couette flow test case is pathological in the sense it is extremely 
> small.  Run-times are therefore dominated by overhead from Python rather 
> than actually doing real work.  Indeed, you will quite possibly even see 
> an improvement if you restrict PyFR to a single thread/CPU core. 
>
> For a real-world problem the run-time will increase greatly as the 
> polynomial order is increased.  Of course, in the real-world, as you 
> increase the polynomial order you typically coarsen your mesh accordingly. 
>
> Regards, Freddie. 
>

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