@haesleinhuepf suggested I post my thoughts/questions about development of clEsperanto on the forum which can hopefully initiate discussions. I did post this on github, but it should gain more visibility here. For those not familiar, info on clEsperanto can be found here. The idea is to provide GPU-accelerated image processing across languages and platforms using the same workflow commands.
Details on the Proposed Roadmap
Following on from the roadmap in regard to core development and the two approaches:
I like the idea of translating ClearCL to Python by exploiting PyOpenCl and/or gputools. I am assuming that this means all other platforms would have to adopt a similar approach where they use platform specific libraries?
However, if ClearCL was translated to C++, is it easier to write wrappers around this in different platforms (Python, Matlab…)? Would it be easier to troubleshoot as it will be working from a common C++ code? Or would it be difficult if developers in each platform are not as familiar with C++, i.e., will it be harder to troubleshoot? Also, how does this approach maintenance and development in the long run?
Disclaimer: I am not experienced with software development,so pardon my naivety and I am more than happy to hear criticisms/thoughts on the below…