Thank you for that. I now incorporate this benchmarks into my seminar. Thank you again, I was unable to even realize that problems were in plots and DelimitedFiles.
It is good to know that Julia speed fluctuate up and down between the versions, but all the time it is very high. I hope that in newer version it regain some speed from 0.6.
That is a good question, but it’ll take someone with a better understanding of compiler internals and assembly language than me to answer it.
The thing to do would be to compare the x86-64 assembly language produced by LLVM from the Julia code to the assembly produced by gcc on the Fortran code. But that’s a lot of assemby language.
Running @code_llvm ksintegrateUnrolled(u,Lx, dt, Nt) produces about a thousand lines of LLVM internal representation code, and @code_native produces several times that of assembly.
It’s possible to dig through the LLVM IR or assembly and focus on code for the time-stepping loop, but it’s still beyond my understanding.
But still, the ksintegratorUnrolled function in Julia-1.2.0 is only 15% slower than the equivalent Fortran code.