Hi all,
One of the first steps we have taken is to create
a Python port of a popular benchmark for IDL (time_test3) which measures performance for a variety of (primarily matrix) operations. In our initial attempt, however, Python performs significantly poorer than IDL for several of the tests. I have attached a graph which shows the results for one machine: the x-axis is the test # being compared, and the y-axis is the time it took to complete the test, in milliseconds. While it is possible that this is simply due to limitations in Python/Numpy, I suspect that this is due at least in part to our lack in familiarity with NumPy and SciPy.
So my question is, does anyone see any places where we are doing things very inefficiently in Python?
In order to try and ensure a fair comparison between IDL and Python there are some things (e.g. the style of timing and output) which we have deliberately chosen to do a certain way. In other cases, however, it is likely that we just didn't know a better method.
Any feedback or suggestions people have would be greatly appreciated. Unfortunately, due to the proprietary nature of IDL, we cannot share the original version of time_test3, but hopefully the comments in time_test3.py will be clear enough.