ArrayFire VS HPX

Loads of people have stated why easy GPU interfaces are difficult to create, but we solve many difficult things all the time.

Ultimately I think CPUs are just satisfactory for the vast vast majority of workloads. Servers rarely come with any GPUs to speak of. The ecosystem around GPUs is unattractive. CPUs have SIMD instructions that can help. There are so many reasons not to use GPUs. By the time anyone seriously considers using GPUs they're, in my imagination, typically seriously starved for performance, and looking to control as much of the execution details as possible. GPU programmers don't want an automagic solution.

So I think the demand for easy GPU interfaces is just very weak, and therefore no effort has taken off. The amount of work needed to make it as easy to use as CPUs is massive, and the only reason anyone would even attempt to take this on is to lock you in to expensive hardware (see CUDA).

For a practical suggestion, have you taken a look at https://arrayfire.com/ ? It can run on both CUDA and OpenCL, and it has C++, Rust and Python bindings.

Low-overhead — not our goal, but Flashlight is on par with or outperforming most other ML/DL frameworks with its ArrayFire reference tensor implementation, especially on nonstandard setups where framework overhead matters

Looking for frameworks with Julia + OpenCL I found array fire. It seems quite good, bonus points for rust bindings. I will keep looking for more, Julia completely fell off my radar.

https://github.com/STEllAR-GROUP/hpx Modern C++ concepts incorporated in a threading library. Lots of useful techniques used in there and we are trying to keep our code base very tidy. Feel free to chime in our libera channel #ste||ar if you have any questions.

https://github.com/STEllAR-GROUP/hpx Welcoming community + we have been part of GSoC for 4-5 years now so feel free to apply there when it opens ;)

I found this interesting library that might fit your goal.

I personally like the ideas in Parallelism v2 TS, which is available in for libstdc++ 11 onwards. The reference implementation is a library named Vc (afaik Vc is the most popular SIMD library for C++), and this has also been implemented in recent versions of HPX.

I am aware of DAGs of task based threading library like Taskflow and HPX however the benefit they have is not obvious to me, as the following sequential section depends on the parallel part being completed fully. If you want to suggest elaboration on the benefits of this approach would be welcome.

Github: https://github.com/STEllAR-GROUP/hpx

We're working on something similar, but based on sender/receiver in HPX (a lightweight threading runtime) and DLA-Future (distributed linear algebra currently based on (HPX) futures; based on sender/receiver in the future). With senders-as-awaitables this would also get you coroutine support for asynchronous MPI calls for free. We don't have that yet, but it's planned. In the meantime libunifex should be able to fill in the gaps.

I come from a group called STE||AR where we develop HPX, "a C++ Standard Library for Parallelism and Concurrency".