Hi Cory,

I'm using a Windows 64bit version that was built from the binary installer 
option on the Paraview downloads page.


The grids can be upwards of 20 million cells.  One timestep worth of data is 
about 100MB.


I'm running on a system with 16GB of RAM.


In terms of optimization I'm inclined to believe that my script isn't written 
very well and that it is the source of the slowdown that I'm seeing when 
running it. I CC'd you on my reply to Andy's email where we identified some 
areas of the script that were particularly slow during execution.


Best regards,


Christopher R. Neal
Graduate Student
Center for Compressible Multiphase Turbulence
Mechanical and Aerospace Engineering Department
University of Florida
Cell: (863)-697-1958
E-mail:  [email protected]


________________________________
From: Cory Quammen <[email protected]>
Sent: Wednesday, October 21, 2015 11:18 PM
To: Andy Bauer
Cc: Neal,Christopher R; [email protected]
Subject: Re: [Paraview] Help with optimizing Paraview Python script

A few questions:

* How did you obtain the ParaView executable? (download, build)? If you built 
ParaView in Debug mode, that could slow things down.

* How big are your data files, both in terms of disk size and grid elements?

* How much RAM is on your system?

- Cory

On Wed, Oct 21, 2015 at 8:50 PM, Andy Bauer 
<[email protected]<mailto:[email protected]>> wrote:
Did you profile this at all to see where most of the time being spent?

Looking at this, I don't see anything really bad. I think you can take out the 
time.sleep(1.0) part though. Also, replacing the Calculator filter with the 
PythonCalculator filter should help some. If you're running this in parallel, 
the fetch is probably hurting performance as well.

On Wed, Oct 21, 2015 at 4:02 PM, Neal,Christopher R 
<[email protected]<mailto:[email protected]>> wrote:

Hello,


I have written a python script that loads in an Ensight data file which has 
multiple solution times associated with it and performs a set of fairly simple 
operations on it. It is running very slow, and I'm wondering if there are any 
experts who use Python to control Paraview that could help me to optimize the 
script.  In a nutshell the script does the following.


1.) Go to a timestep

2.) Generate a series of 2D slices in the 3D domain

3.) Compute some values of the solution variables on those slices

4.) Write data to a file

5.) Delete the entire pipeline except the original data

6.) Go back to 1.)


This process is painfully slow(2+days just to run the script on a modest size 
data set).  I believe that the script having to delete the pipeline and then 
re-create it for every timestep is contributing to the slowdown. My  trouble is 
that I do not know how to selectively activate certain elements in the pipeline 
if I want to extract information from them, so I have to add them sequentially 
so that the newest one is the active one.  The script may also be rendering 
each step, which is unnecessary for me, but I do not know how to disable that 
as well.


I have attached a copy of the script. I have a minimal working example that 
contains the data set with only 3 timesteps worth of data.


I am even willing to pay  $100 for an expert to help me out with this.


Thank you,


Christopher R. Neal
Graduate Student
Center for Compressible Multiphase Turbulence
Mechanical and Aerospace Engineering Department
University of Florida
Cell: (863)-697-1958<tel:%28863%29-697-1958>
E-mail:  [email protected]<mailto:[email protected]>

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--
Cory Quammen
R&D Engineer
Kitware, Inc.
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