in reply to Re^2: Perl in data science: could a grant from Perl foundation be useful?
in thread Perl in data science: could a grant from Perl foundation be useful?

Agree that researchers are not forced to use one particular language. The choice of programming language and tools is almost free when working alone. However, when working in groups that share code it is more difficult to freely choose. Nowadays, it can be almost impossible be the only one using Perl while all others code in Python or R, unless the particular workflow and local culture allows it. For example if only exchanging data chunks in some standard format, instead of code. I believe that the major barrier to widespread use of Perl is that it has largely been displaced by Python and R in the general culture of scientific circles. Technical details or idiosyncrasies are weak arguments often used in discussions, but I believe the real thing is just cultural.
  • Comment on Re^3: Perl in data science: could a grant from Perl foundation be useful?

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Re^4: Perl in data science: could a grant from Perl foundation be useful?
by etj (Priest) on Jul 27, 2024 at 17:22 UTC
[reply]
      I think https://chrisarg.github.io/Killing-It-with-PERL/2024/07/07/The-Quest-For-Performance-Part-II-PerlVsPython.md.html et al make a powerful argument that Perl (especially with PDL) can be a powerful, and high-performance, adjunct to other programming languages or tools in data science, and other science.

      I created complementary demonstrations for the article on the web, running on the CPU or GPU.

      CPU results captured on AMD Threadripper 3970X.

      $ perl pdl_cpu.pl
==================================================
In place in (Perl PDL - CPU multi-threaded)
==================================================
   33974.886 µs
   37286.043 µs
   36175.966 µs
   32786.131 µs
   34714.937 µs
   32924.175 µs
   33201.933 µs
   33097.029 µs
   33265.114 µs
   33904.076 µs

$ python numba_prange.py 
==================================================
In place in (Python Numba - CPU multi-threaded)
==================================================
   30696.392 µs
   37623.167 µs
   32857.656 µs
   26406.765 µs
   26831.150 µs
   26624.441 µs
   26728.153 µs
   26698.828 µs
   26748.657 µs
   26932.001 µs

$ python taichi_cpu.py 
[Taichi] version 1.8.0, llvm 15.0.4, commit 37a05638, linux, python 3.
+10.13
==================================================
In place in (Python Taichi - CPU multi-threaded)
==================================================
[Taichi] Starting on arch=x64
   76603.651 µs
   45389.175 µs
   37540.913 µs
   29339.075 µs
   28975.725 µs
   29037.952 µs
   30524.731 µs
   29897.928 µs
   30224.562 µs
   28925.419 µs

      [download]

      GPU results captured on NVIDIA GeForce RTX 3070.

      $ python cupy_blas.py 
==================================================
In place in (Python CuPy - GPU cuBLAS)
==================================================
    6246.805 µs
      24.557 µs
      17.881 µs
      17.643 µs
      17.643 µs
      17.643 µs
      17.643 µs
      17.405 µs
      17.405 µs
      17.405 µs

$ python numba_cuda.py 
==================================================
In place in (Python Numba - GPU CUDA)
==================================================
     182.629 µs
      40.054 µs
      30.279 µs
      28.133 µs
      27.895 µs
      27.657 µs
      27.418 µs
      26.941 µs
      26.941 µs
      26.703 µs

$ python taichi_cuda.py 
[Taichi] version 1.8.0, llvm 15.0.4, commit 37a05638, linux, python 3.
+10.13
==================================================
In place in (Python Taichi - GPU CUDA)
==================================================
[Taichi] Starting on arch=cuda
   15263.557 µs
      51.975 µs
      28.133 µs
      25.034 µs
      24.080 µs
      26.464 µs
      26.226 µs
      24.557 µs
      24.080 µs
      28.133 µs

      [download]
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Re^4: Perl in data science: could a grant from Perl foundation be useful?
by Anonymous Monk on Mar 14, 2020 at 15:06 UTC
    I believe that the major barrier to widespread use of Perl is that it has largely been displaced

    There is only one book left on the shelf...

[reply]

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