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The final installment in the series:
"The-Quest-For-Performance" from my blog, discussing #python #numpy #numba, #rstats @openmp_arb #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 & pragmas ?
The Quest for Performance Part IV : May the SIMD Force be with you
At this point one may wonder how numba, the Python compiler around numpy Python code, delivers a performance premium over numpy.Killing-It-with-PERL
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 ?
submitted by /u/ReplacementSlight413
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The Quest for Performance Part IV : May the SIMD Force be with you
At this point one may wonder how numba, the Python compiler around numpy Python code, delivers a performance premium over numpy.Killing-It-with-PERL
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.
submitted by /u/ReplacementSlight413
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The Quest for Performance Part I : Inline C, OpenMP and PDL
Sometimes, one’s code must simply perform and principles, such as aeasthetics, “cleverness” or commitment to a single language solution simply go out of the window.Killing-It-with-PERL
