# TGV performance

**URL:** <https://pyfr.discourse.group/t/tgv-performance/248>\
**Category:** General\
**Created:** [8 August 2019 21:09 UTC](https://pyfr.discourse.group/t/tgv-performance/248 "2019-08-08T21:09:50Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![Stefan\_K](https://avatars.discourse-cdn.com/v4/letter/s/90ced4/32.png) [@Stefan\_K](https://pyfr.discourse.group/u/Stefan_K)\
**Post date:** [8 August 2019 21:09 UTC](https://pyfr.discourse.group/t/tgv-performance/248/1 "2019-08-08T21:09:50Z")

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I am wondering if someone can comment on the TGV results (case2) in Loppi et al. Computer Physics Communications 233 (2018). It looks like the wall-clock time is quite high compared to incompressible flow solvers. Is this because of the method to handle low Mach number flows with a compressible code?

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**Author:** ![Loppi\_Niki](https://avatars.discourse-cdn.com/v4/letter/l/2bfe46/32.png) [@Loppi\_Niki](https://pyfr.discourse.group/u/Loppi_Niki)\
**Post date:** [8 August 2019 23:20 UTC](https://pyfr.discourse.group/t/tgv-performance/248/2 "2019-08-08T23:20:09Z")

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It is difficult to answer as you are not giving any details. What are you comparing against (resolution, hardware, wall-time, discretisation, time-integration etc…)?

I think our 3h38min wall-time is fine. For example here [https://arxiv.org/pdf/1802.01439.pdf](https://arxiv.org/pdf/1802.01439.pdf) similar setup with an incompressible solver took 4h.

Here are few things to consider:

- The number of elements is 52^3 but the number of solution points is 260^3 (P=4 polynomials)
- Since the geometry is just a box, purely spectral / high-order finite difference schemes have an advantage.
- You could strong scale. Double the number of GPUs and cut the wall-time in half.
- We have made the solver faster since by adding other convergence acceleration techniques. Latest release should be ~2-3x faster.

Niki