Very interesting. If I understand correctly, this article is mainly focused on bioinformatics and performance of high level languages in that area.
I wonder why BioPerl (https://bioperl.org/, https://en.wikipedia.org/wiki/BioPerl) has not been included, it would have been interesting. Perl is considered surprisingly fast for certain classes of tasks (for an interpreted language of course, no point in comparing to C for example).
Perl isn't really an interpreted language. It's compiled to a sort of bytecode when you run the program, and executed on a sort of virtual machine. Similar to Java or C#, but much faster to compile. So fast that most people don't even know it's happening.
As for performance, it really helps if you write idiomatic Perl code. There may be more than one way to do it, but some ways are better. For example, an explicit for loop over a list has to be compiled to byte code that steps through the looping, but if you use map or grep the byte code calls a pre-written optimized function that loops as fast as code written in C would be. The more idiomatic your code is, the more optimized calls like that you get, and the faster your code will run.
'Interpreted' is often used to mean 'not compiled to machine code'. Perl fits that bill. So do, say, CPython and Lua, in contrast to JIT-compiling runtime systems like PyPy or LuaJIT or AOT-compiled languages like C or Rust.
I wonder why BioPerl (https://bioperl.org/, https://en.wikipedia.org/wiki/BioPerl) has not been included, it would have been interesting. Perl is considered surprisingly fast for certain classes of tasks (for an interpreted language of course, no point in comparing to C for example).
My info could be outdated of course.