Hello Mr. Torben
Even though the library is in the initial stages of development, I would keep developing it and work on it extensively during GSOC. Octave is meant for scientific computing which would include machine learning algorithms, many of which can be accelerated on the GPU. Therefore I believe it is relevant to Octave as it would be good to have a dedicated ML library with GPU acceleration.
Also, I am really interested in HPC, and I had another idea, which is to provide hardware acceleration to the scientific algorithms already present. For example, write a kernel for FFT in both Cuda as well as SYCL (so that we could cover all the devices) and dynamically dispatch it to the target device. This way octave would have strong hardware acceleration support. This would however be a big project, as most of the BLAS would have to be rewritten for SYCL. For Nvidia GPUs, we could use cuBLAS/ NvBLAS.
Thanks and Regards,
Atharva Dubey