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One of the reasons I keep dropping hints about #perlffi , #pdl and #openmp is that one can literally have five multithreading frameworks in the same #perl application of a master process: 1) PDL, and FFI intefacing with 2) #Fortran coarrays, 3) Fortran openmp, 4) #c openmp and 5) #cplusplus #openmp. All these frameworks can share memory addresses for array and vector objects, and #perl aided by #PerlAlien makes the authoring of the high-level code a pleasure ! https://hgpu.org/?p=29403

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@oalders No, I have not. This is on my to-do list for the #bioinformatics and signal processing projects. Those involve a substantial amount of object creation and destruction targeting the #edge (the objects being used for safe memory management for low-level code and MOP for said code). I have a couple of #openmp #perl #c examples lined up for the blog , perhaps I should run them with that one as well).


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 ?

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


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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Enhancing non-Perl #bioinformatics applications with #Perl by #bioinformatics #openmp https://www.slideshare.net/slideshow/enhancing-non-perl-bioinformatic-applications-with-perl/269925371 Slides for my #tprc2024 talk discussing component based development using @PerlAlien , @PerlFFI , and
@openmp_arb

Preprint https://arxiv.org/abs/2406.10271
(v2 based on feedback by Mario Roy and @mdperry will be uploaded during the weekend!)
@Perl


Hey you #Perl programmers, enjoy this video on the options available for including #OpenMP into your Perl programs for computationally intensive applications.

https://www.youtube.com/watch?v=lMRjdpygVFM