OpenCL-examples VS neanderthal

In the link provided, the CUDA example only show the compute kernel itself and not the boilerplate required to run it. On the other hand, your OpenCL example only show the boilerplate.

This is the OpenCL kernel from the same repo, for a more fair comparison: https://github.com/rsnemmen/OpenCL-examples/blob/master/mand...

This is much more readable. OpenCL-C the language is fine: it's how you deploy the program on the cards that is complicated with opencl.

There is the official Hello World https://github.com/uncomplicate/neanderthal/tree/master/examples/hello-world

Did you have any occasion to evaluate neanderthal during your research? People seem to prefer it over core.matrix because it focus on primitive speed and sticking to BLAS idioms (as well as offering a decent api for working with GPU backends via cuda and opencl). I am curious to see if you did and found anything lacking there. I have a project on the backburner to try and target neanderthal for local search stuff, expressing problems in a high-level API that can then be baked into some numerically-friendly representation for efficient execution. It's often easier (trivial) to express solution representations, neighborhood functions, and objectives/constraints in a general purpose language, of which none of the things we like (sparse data structures, dynamically allocated stuff) are amenable to the contiguous memory, primitive numeric model that the hardware wants.

Do clojure as a side gig or in free time. Let day job pay the bills. If you can, maybe incorporate clojure into work job to solve small problems (https://github.com/clj-python/libpython-clj and https://github.com/scicloj/clojisr provide bridges to/from python and r). There is a lot of effort going into the data science side as well; the scicloj effort has resulted in a lot of growth over the last 2 years. tech.ml.dataset, tech.ml (now scicloj.ml). Dragan has a bunch of excellent stuff in neanderthal and deep diamond. There are also bindings to other jvm libraries from multiple languages.