Re:APL deserves its renaissance too
by Athas on Monday May 28, 2018 @03:46PM
(#17174409)
How is Co-dfns not what you want? It is by far the best attempt I know of for bringing the full power of APL to accelerators like GPUs[0].
...however, it is not easy. Full APL has a lot of features (like nested arrays) that are incredibly difficult to map to GPU execution. And in general, APL is not easier to map to GPUs than your bog standard Numpy-style matrix library (in fact it's harder, since Numpy only has regular arrays and simple operations).
...however, it is not easy. Full APL has a lot of features (like nested arrays) that are incredibly difficult to map to GPU execution. And in general, APL is not easier to map to GPUs than your bog standard Numpy-style matrix library (in fact it's harder, since Numpy only has regular arrays and simple operations).
[0]: I was involved in a project that targeted only a small well-behaved subset of APL, which was hard enough: https://github.com/henrikurms/tail2futhark