Pavan Yalamanchili

@arrayfire/core-devel thoughts ?

@9prady9 We need to have consistent behavior for accuracy reasons. We can't promote to fp32 in one backend while we use use native fp16 in others. We can perhaps, at...

@9prady9 The problem isn't algorithm specific, it has to do with hardware. In the other issue, @umar456 linked to the nvidia docs regarding performance. Everything other than the P100 has...

@WilliamTambellini It can be enabled as an option that user can toggle.

@WilliamTambellini definitely possible, that's what I was suggesting.

@WilliamTambellini @velhaco20000 I am going to work on run-time compilation of most (if not all) CUDA kernels (similar to what is happening in OpenCL). This should make it easier to...

@velhaco20000 > The future of heterogeneous computing is in C/C++ standard, a solution similar as you are working here. But This solution will not be in the market before 2020-21....

@WilliamTambellini @velhaco20000 also drop by slack: https://join.slack.com/t/arrayfire-org/shared_invite/MjI4MjIzMDMzMTczLTE1MDI5ODg4NzYtN2QwNGE3ODA5OQ if you want to chat about this.

These functions error out in 3.0. Pushing the feature request for a later release.

It is most definitely not supported in the open source version. We were not throwing errors before. I changed this behavior couple of days ago. We will add support for...