julia-challenge

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Extra challenge: Sliced/non-contiguous tensor broadcasting.

2

The current challenge is great to stress the extensibility of a language (lifting functions on variadic container inputs) but it does not really stress performance as a naïve for loop...

mratsim

Tips for a Haskell version

1

After reading this challenge (and the nice Medium post about a C++ implementation), I immediately thought back to the paper [APLicative programming with Naperian Functors](https://www.cs.ox.ac.uk/people/jeremy.gibbons/publications/aplicative.pdf), which talks about how you...

Qqwy

Minimal broadcasting engine for c++

7

This is somehow simpler (but probably less generic) than @wolfv solution. Probably a good starter before eating wolv's one :-)

serge-sans-paille

Confusion over what exactly to implement

1

A [comment on Reddit](https://www.reddit.com/r/Clojure/comments/9i5wij/the_julia_challenge/e6jsasf/) recently appeared where someone felt like the article wasn't explicit enough about what you actually wanted them to implement. I don't know how valid that is,...

MasonProtter

Inspired by #6 by @serge-sans-paille, I think the [TRIOT: Faster tensor manipulation in C++11](Faster tensor manipulation in C++11) paper would be a great fit for this challenge. TRIOT stands for...

mratsim

Pythran version

7

serge-sans-paille