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The final installment in the series:

"The-Quest-For-Performance" from my blog Killing It with #perl

Discussing #python #numpy #numba, #rstats #openMP enhancements of Perl code and #simd

Bottom line: I will not be migrating to Python anytime soon.

Food for thought: The Perl interpreter (and many of the modules) are deep down massive C programs. Perhaps one can squeeze real performance kicks by looking into alternative compilers, compiler flags and pragmas ?

https://chrisarg.github.io/Killing-It-with-PERL/2024/07/09/The-Quest-For-Performance-Part-IV-May-the-SIMD-Force-Be-With-You.html

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A couple of data/compute intensive examples using Perl Data Language (#PDL), #OpenMP, #Perl, Inline and #Python (base, #numpy, #numba). Kind of interesting to see Python eat Perl's dust and PDL being equal to numpy.

OpenMP and Perl's multithreaded #PDL array language were the clear winners here.


https://chrisarg.github.io/Killing-It-with-PERL/2024/07/06/The-Quest-For-Performance-Part-I-InlineC-OpenMP-PDL.html

https://chrisarg.github.io/Killing-It-with-PERL/2024/07/07/The-Quest-For-Performance-Part-II-PerlVsPython.md.html

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