Making efficient some small subroutines

General Usage Performance
21

After fixing the line D[i,p] = ldiv!(lu!(B), Dl) and changing your program to use in-place functions, I’d think further optimizations would be microscopic.

I don’t know if you’ll get any speedup, but in the function H(i,n,X,Y,p,γ,sh), you could move the square root in the assignment of c to the exponents within D(c, _, 2,γ,sh).

22

Once you’re satisfied with the performance, it would be interesting to see some kind of comparison with the python version of your program.

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23

In original full version of my program the timings were as follows:

Julia->34 seconds
Python+Numpy->28 seconds

After improvements in Julia codes, I get

BenchmarkTools.Trial: 
  memory estimate:  6.57 GiB
  allocs estimate:  5684639
  --------------
  minimum time:     4.599 s (2.48% GC)
  median time:      4.636 s (3.40% GC)
  mean time:        4.636 s (3.40% GC)
  maximum time:     4.673 s (4.30% GC)
  --------------
  samples:          2
  evals/sample:     1

This is much better. Thanks to everyone who contributed once again.

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