3 ms·
Might very well be true. I don't blame anyone for not diving deeper into figuring out why this stuff doesn't work. But this is one of the great strengths of CU
by KeplerBoy 3y ago
Might very well be true. I don't blame anyone for not diving deeper into figuring out why this stuff doesn't work.
But this is one of the great strengths of CUDA: I can develop a kernel on my workstation, my boss can demo it on his laptop and we can deploy it on Jetsons or the multi-gpu cluster with minimal changes and i can be sure that everything runs everywhere.
- brutus1213 3y agoThere is indeed something excellent about CUDA from a user perspective that is hard to beat. I do high-level DNN and it is not clear to me what it is or why that is. Anytime I have worked on optimizing to mobile hardware (not Jetson, but actual phones or accelerators), it is just a world of hurt and incompatibilities. This notion that operators or subgraphs can be accelerated by lower level closed blobs .. I wonder if that is part of the issue. But then why doesn't OpenCL not just work? I thought it gave a CUDA kernel like general purpose abstraction. I just don't understand the details enough to understand why things are problematic without CUDA :(
- iopq 3y agoSorry, still trying to install some dependencies for DNN and CUDA, not sure why it says my Clang version is too new (!)