Numerical computing is hard ( even when all of your instincts suggest otherwise) and when someone demonstrably does it right, it makes good sense to reuse rather than reinvent." if it wasn't for the fact that sizeable percentages of foundational data science platforms such as R and SciPy are written in Fortran.Ĭroucher argues that "More modern systems, such as R, make direct use of a lot of this code because it is highly performant and, perhaps more importantly, has been battle tested in production for decades. You could be forgiven for thinking that this doesn't matter to most users. At the time of writing this is the only Fortran compiler publicly available for Apple Silicon although that will likely change soon as open source Fortran compilers get updated."Īn anonymous Slashdot reader offers this analysis:Īpple Silicon currently has no open source Fortran compiler and Apple themselves are one of the few silicon manufacturers who don't have their own Fortran compiler. "Simultaneously, The Numerical Algorithms Group announced that they had ported their Fortran Compiler to the new platform. "Earlier this week Apple announced their new, ARM-based 'Apple Silicon' machines to the world in a slick marketing event that had many of us reaching for our credit cards," writes Mike Croucher, technical evangelist at The Numerical Algorithms Group.
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