Best approach for GPGPU/CUDA/OpenCL in Java?

Question

General-purpose computing on graphics processing units (GPGPU) is a very attractive concept to harness the power of the GPU for any kind of computing.

I\'d love to

Answer 1

I've been using JOCL and I'm very happy with it.

The main disadvantage of OpenCL over CUDA (at least for me) is the lack of available libraries (Thrust, CUDPP, etc). However CUDA can be easily ported to OpenCL, and by looking at how those libraries work (algorithms, strategies, etc) is actually very nice as you learn a lot with it.

Answer 2

If you want to do some image processing or geometric operations, you may want a linear algebra library with gpu support (with CUDA for instance). I would suggest you ND4J witch is the linear algrebra with CUDA GPU support on which DeepLearning4J is built. With that you don't have to deal with CUDA directly and have to low level code in c. Plus if you want to do more stuff with image with DL4J you will have access to specific image processing operations such as convolution.