11–20 of 48 posts
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Or the Web Ontology Language (OWL) [1] whose inconsistent acronym is not in fact a tribute to the spelling-challenged Owl character in Winnie-the-Pooh [2] [1] https://en.wikipedia.org/wiki/Web_Ontology_Language [2] https://en.wikipedia.org/wiki/List_of_Winnie-the-Pooh_charac...
Or the OWL region in Germany: https://en.wikipedia.org/wiki/Ostwestfalen-Lippe TLAs tend to be horribly overloaded and confusing without a very obvious context.
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Or the OWL region in Germany: https://en.wikipedia.org/wiki/Ostwestfalen-Lippe TLAs tend to be horribly overloaded and confusing without a very obvious context.
Or the nocturnal bird.
Wow, this even supports Algorithmic Differentiation! https://github.com/ryanrhymes/owl/wiki/Tutorial:-Algorithmic... (although "only" forward and reverse mode)
I looked at OCaml a few years back for scientific computing, but was turned off by the global lock GC for multithreading (similar to python). Anyone know if this has been changed yet? Edit: doesn't look like this has changed, but there's an effort at https://github.com/ocamllabs/ocaml-multicore that is slowly making progress
IIRC, there was a PR preparing upstream ocaml for multicore. I think multicore capabilities will be here soon. Would things like LWT or async help you in any way?
Just a word of caution to set expectations. The "will be here soon" status has been there for a while, to the extent that it now evokes memories of GNU Hurd, Duke Nukem Forever. It will be ready whenever it will be ready, its in good hands, but don't hold your breath, try to work around it for now.
Earlier quoted context omitted.
IIRC, there was a PR preparing upstream ocaml for multicore. I think multicore capabilities will be here soon. Would things like LWT or async help you in any way?
> I think multicore capabilities will be here soon. Just a word of caution to set expectations. The "will be here soon" status has been there for a while, to the extent that it now evokes memories of GNU Hurd, Duke Nukem Forever. It will be ready whenever it will be ready, its in good hands, but don't hold your breath, try to work around it for now.
There are a series of milestones to hit: the runtime GC, the memory model, the low-level programming model using one-shot continuations, and how it affects libraries running over it (e.g. algebraic effects). Each of these have associated papers and talks (see the ocamllabs.ionews section), so it's not quite fair to compare it to Duke Nukem Forever :-)
Some quick links to recent papers: - memory model: http://kcsrk.info/papers/memory_model_ocaml17.pdf - programming model: http://kcsrk.info/papers/awkward_effects_ml17.pdf
Wow, this even supports Algorithmic Differentiation! https://github.com/ryanrhymes/owl/wiki/Tutorial:-Algorithmic... (although "only" forward and reverse mode)
Slightly off topic sorry, but how Algorithm Differentiation usually implemented? Do you just apply the chain rule to an AST, or is there something more complex you have to do?
Wikipedia explains it properly, if a bit tersely: https://en.wikipedia.org/wiki/Automatic_differentiation
In the case of Owl, it would appear that you have to write your functions using a set of overloaded operators contained in module Maths here: https://github.com/ryanrhymes/owl/blob/master/lib/owl_algodi...
Those operators, as explained in the Wikipedia page, manipulate "dual numbers," which are pairs of (number, epsilon) with their own specific algebra.
Wow, this even supports Algorithmic Differentiation! https://github.com/ryanrhymes/owl/wiki/Tutorial:-Algorithmic... (although "only" forward and reverse mode)
Slightly off topic sorry, but how Algorithm Differentiation usually implemented? Do you just apply the chain rule to an AST, or is there something more complex you have to do?
I was actually looking for a good numerical library, supporting complex numbers, matrix operations, and multi-dimensional arrays. I'm looking forward to using and contributing to this one!