A member of NAG made the following comments and I thought it might be of interest if someone more knowledgeable than myself from the Julia community could provide a response (the comments they made were in response to a recent Julia Computing announcement Seed Funding ) I would definitely question …

[image] ExpandingMan: That said, I would agree that the statement about Fortran is probably misleading. I know nothing about the source of the quote in question, but let me give you a real-world example in which I’ve often found that Julia code can be faster than comparable algorithms in prod…

For what it’s worth, I think that the explanation you just gave is infinitely preferable to what appears in that post.

[image] ExpandingMan: For what it’s worth, I think that the explanation you just gave is infinitely preferable to what appears in that post. I don’t think the original quote was that problematic if read in a reasonable way. Obviously, it was a situation in which someone ported some low-level…

It could also be a case where Julia was able to figure out optimizations based on specializing on types, that didn’t happen automatically in the original language (Fortran, or in my case, C). The moment that I really fell in love with the Julia language was when I saw it take some string handling c…

Also, the BLAS and LAPACK kernels that Julia uses are, in the important cases, not the reference BLAS written in Fortran but rather the multi-threaded BLAS/LAPACK in OpenBLAS and MKL. Indeed the big problem with reference BLAS and LAPACK is that they need to be written in Fortran 77. I can say from…

I would encourage people interested in this topic to attend the Celeste keynote at JuliaCon on Thursday. I’ll be talking a bit about how julia enables really high performance applications. I think there’s two major aspects to performance here that is easily missed: How efficient is the code that…

As for the performance claims in the blog post. I understand where the uneasiness with those quotes comes from. I’ve had the same discussion with our marketing folks. However, they are real quotes from our actual customers that have replaced their legacy code bases with julia implementations. That…

I think changing “Julia provides” to “Julia has provided” fixes most of the problem here. The quotes from customers are of course valuable.

Sharing another experience. Cuba.jl is a package for numerical integration, a wrapper around the C library Cuba . Here is a comparison between runtimes of Julia, C, and Fortran programs calling the same library and integrating the same 11-element vectorial function in three dimensions with four dif…

[image] giordano: Unfortunately, Cuba.jl cannot take advantage of parallelization capability of Cuba library because Julia doesn’t support fork. Would be cool to see how Cuba.jl performs in that case. OT: Cubature.jl (similar to the Cuhre algorithm in Cuba) can give you a vector of points at…

Also Cuba supports vectorization (see Welcome to Read the Docs — Cuba.jl stable documentation ), in addition it has parallelization. Your suggestion is interesting, thanks!

Julia vs Fortran complaint

General Usage

ihnorton June 21, 2017, 3:13pm 22

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Julia vs Fortran complaint

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