6 ms·
I'd love for this to get more mainstream attention! J, Futhark, Accelerate all have very neat stuff under the hood.
by vmchale 6y ago
I'd love for this to get more mainstream attention! J, Futhark, Accelerate all have very neat stuff under the hood.
- eggy 6y agoI second J and Futhark. I love J, and I wish there was a way to use the GPU with J. I have looked briefly at APL -> TAIL -> Futhark, but I don't know enough to do something useful with that particular toolchain or wow myself enough to keep going. More studying...
- smabie 6y agoHow about co-dfns? CUDA accelerated APL! https://github.com/Co-dfns/Co-dfns https://github.com/Co-dfns/Co-dfns
- eggy 6y agoYes that is Aaron Hsu's work for APL on the GPU. I was hoping for a J on the GPU toolchain.
- the_optimist 6y agohow about: https://github.com/Pascal-J/Jfire https://github.com/Pascal-J/Jfire
- eggy 6y agoThanks! I had heard of ArrayFire, but I didn't know about this J implementation. There goes my week!
- teleforce 6y agoLesser known Single Assignment C (SAC) is using array based functional programming as well [1],[2]. As the name implied it uses C/Algol based syntax for parallel programming of multi-core and GPU. Similar to Haskell it's originated in academic research. It utilizes static single assignment (SSA) concept that can be used for both imperative and functional programming [3]. Neat stuff. Hopefully someone can emulate this with a modern open source hybrid functional language like Scala or D. [1]http://www.sac-home.org/doku.php http://www.sac-home.org/doku.php [2]https://www.microsoft.com/en-us/research/video/sac-off-the-shelf-support-for-data-parallelism-on-multicores/ https://www.microsoft.com/en-us/research/video/sac-off-the-s... [3]https://www.cs.princeton.edu/~appel/papers/ssafun.pdf https://www.cs.princeton.edu/~appel/papers/ssafun.pdf