As quick googling shows, default data type for numpy is 32-bit "single precision" "float"

Are you really sure? I was surprised by your claim that numpy use a default C float. I am a longtime Perl and C hacker and no python expert. But I view the C float type as kind of archaic I use many math libs and the trend is to go past the C double. It would be surprising for a modern lib like numpy to use such a default. Also float() in python means floating point not C float.

Note that I do not really care if tool X is faster that tool Y when the sun, jupiter and the moon are aligned. But I did a bit of web search and could not _quickly_ come up with a definite answer! so I decided to check. Seems that numpy default is a C double:

% steph@kerangi (/tmp/cpanm_t.d) %
% python3.8 -c 'import math as m; print(m.sin(float(1)))'
0.8414709848078965

% steph@kerangi (/tmp/cpanm_t.d) %
% python3.7
Python 3.7.7 (default, Apr 10 2020, 07:59:19)
[GCC 9.3.0] on cygwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import numpy as np
>>> np.float
<class 'float'>
>>> np.float64
<class 'numpy.float64'>
>>> np.float32
<class 'numpy.float32'>
>>> print(np.sin(float(1)))
0.8414709848078965
>>> print(np.sin(np.float64(1)))
0.8414709848078965
>>> print(np.sin(np.float32(1)))
0.84147096
>>>
[download]

I think that PDL is really a fantastic piece of software and that it is pretty fast. One possible pitfall, common to all C extensions to Perl, is to go back and forth too many times between Perl and C as that can make a computation much slower. It is often possible to avoid it.