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Comment by BrandonS113 | Hacker News Reader

Yes, well no gradients. It a simple parametric function (6 parameters) applied to a vector of lengths 10 to 20. All vectorizes in the language of R. All powers, logs, exponentials, ratios, and sums. Large number of local maxima, and places where function cannot be evaluated. So probabilistic optimizer is very important.

Come to think of it, for this sort of calculations, R and Julia should take the same time.

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Of course, this is piques one's curiosity. It might be, if the function is simple enough, that there is little advantage to Julia here.

But if you are combining multiple operations on a vector, there could be opportunities for Julia, in-place operations, fusing, simd. Maybe even StaticArrays.

Any chance of sharing that little piece of code?

sure, for parameters par (what is optimized for), data vector x (typical length from 10 to 20), constants n and n2, a typical function is

  if((1 - par[3]^2)<0 ) return(100)
  if(par[1] + par[2] \* par[5] \* sqrt(1 - par[3]^2)<0) 
  return(500 )
  tmp <- (x - par[4])^2 + par[5]^2
  tmp2 <- par[1] + par[2] \* (par[3] \* (x - par[4]) + 
  sqrt(tmp))
  result <- ((sqrt(tmp2) - Ce) / n2)^2
  result <- sqrt(sum(n \* result) / n)
  if(is.na(result)) return(1111)
  return(result)

I'm not that good at reading R. But if the Julia code is similar, then this code is type unstable, sometimes returning an Int, sometimes a Float. That harms performance.

Generally, it looks like a function where Julia could have a significant performance advantage.

R looks pretty much the same as Julia here. Don't think its unstable. Its all float. Nlopt passes parameters as float, data is float. Can't see how it could return int.

But I'll take a second look at the julia version of it. We optimised R as much as possible. might have missed a julia trick. simd perhaps. Except we also run it on ARM

Maybe it's all floats in R, but in Julia, `return 500` means an Int is returned. But it's really hard to determine whether the Julia code is unstable based only on the R code.

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