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by abhimanyuaryan 1196 days ago
As package developers we need to optimize our packages for 1.9. It's quite a task but I am excited what's ahead in Julia. Matlab(is not open-source, R is slow and not really a general purpose language, Python is great but same issue 2-lang problem...why should I implement CUDA in C++ or Numpy in C. I want to be able to modify lower back-end code but with Python it's not possible. Julia fixes all of these problems and I am quite happy I invested my time in Julia. Present/Future is bright :)
1 comments
pjmlp 1196 days ago
Thankfully my GPU programming is shadet related, thus I don't have to deal with all the compute issues, however a good decision of CUDA from early on was to have PTX.

GPGPU needs more languages that make it easier to do compute with feeling like doing Assembly.

Basically the productivity that can be understood by reading stuff about StarLisp and the connection machine.

Julia seems a nice addition to this idea.

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