Already in 2020,
https://developer.nvidia.com/blog/cuda-refresher-the-gpu-com...
This, so much. Other platforms continue to ignore developer UX, but it's one of the main things that get's new users onboard and keeps old users around.
Then I guess all the best.
Here is a tip, you don't always need to suffer from FOMO and get the very latest model card.
In fact, contrary to the competition, one can play with CUDA even on laptops, go figure.
If you were to guess, when do you think your Nsight Compute alternative might be ready with your own toolchain?
While performance improvements will always remain a target, we're soon at full coverage of the core CUDA APIs and will be shifting an increasing amount of effort towards developer tooling.
SYCL, as well as AdaptiveCpp, is a relatively active project though and has been for several years, feeding into the C++ standards committee work and is supported by several large organisations, including US national labs and several European universities. I suppose it’s worth keeping track of for people in related fields.
I suppose it’s just really hard to beat the head start and ecosystem integration NVIDIA has with CUDA.
Neocloud customers just want plug-and-play CUDA. It works, it's tested, it adapts faster, and has known performance. Alternatives give no significant benefits.
Things can change, but they are not changing now.
No reason to tie yourself to Nvidia's moat.
Needless to say, I'd never ever pick Vulkan for any project after that experience. It's just way to needlessly overengineered and bloated.
Vulkan ended up being the same extension spaghetti as its predecessor, and Khronos was only able to come up with something thanks to AMD offering Mantle, C++ bindings and a GLSL successor only came to be thanks to NVidia (Vulkan-hpp and Slang started at NVidia).
The "we build the specification", and then "the community builds the tools", leads to very poor experiences, and if it wasn't for LunarG own interests, there wouldn't even exist any kind of Vulkan SDK.
What they have going is naturally the vendor independence, however we can achieve the same with middleware with the benefit of much better developer experience.
CUDA is no different, in fact, often worse. Nvidia is bad at documenting which hardware does what things, and CUDA users often have to use third party tables to figure out what hardware can't do what and disappoint customers who unwisely invested into it.
Profiles and API versions are much better approaches.
It is no accident than the ongoing efforts to make Vulkan more friendly are moving away from extension spaghetti into profiles.
Having to deal with closed source opaque poorly documented stacks sucks.
One of the biggest complaints we hear from the industry is "we tried to port to X and we could never complete it".
An established codebase can have years of refinement. It will take time to achieve the same with the port.
And with our compiler, just using cuda is no longer putting urself inside the moat :)
Should be real simple if the HN AI echochamber is right, right?