[Python] Need help in optimizing Dry Etching Model in Python for Performance

I am working with a dry etching simulation model taken from a Github repository, which was originally developed in Python 3.6 (version 0). I modified the code so that it runs in Python 3.11, but I am facing performance issues. Currently, the code takes around 22-24 seconds to process a single image, which seems quite slow for my machine. I am wondering if this processing time is typical for this model or if there are any optimization techniques that I could apply to improve the performance.

My machine specifications are:

• Intel(R) Core(TM) i5-4440 CPU @ 3.10GHz
• 8GB RAM
• Windows 10

Is the processing time I am experiencing normal for this kind of simulation, or should it be faster?

Are there any specific optimizations or hardware requirements that could help speed up the performance?

I have tried modifying the code to run in Python 3.11, as it was originally designed for Python 3.6. I was expecting that the code would run with similar or slightly improved performance since I am using a more recent version of Python. However, the processing time remains quite long, and I am unsure if this is expected behavior for the model or if there are potential optimizations that I haven’t considered.

I also wondered if there are any specific machine specifications or software dependencies that could be affecting the speed. Any insights or suggestions on how to improve the processing speed would be greatly appreciated.

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