[roel_v]

Yeah, really tiny... At first I thought 'wow this is a game changer', but then I looked at your link and thought 'what's the point?'. Can someone explain what real problems you can solve with just the headers in the link above?

[jpz]

I guess that the point is that when writing CUDA code (which looks like C++), you can use these libraries which are homogenous with CPU code.

Looking at the functions, chrono/barrier etc require CPU level abstractions, so using the STL versions (which are for the CPU) aren't going to work really.

[happyweasel]

It runs on the GPU?

[roel_v]

What runs on the gpu?

[jcelerier]

this library

[blelbach]

https://youtu.be/75LcDvlEIYw

https://youtu.be/VogqOscJYvk

[TillE]

I would have expected the <algorithm> header, but instead...synchronization primitives? std::chrono? I'm completely baffled about how that would be useful, but that's probably because I know very little about CUDA.

[blelbach]

GPUs are parallel processors. So, yes, synchronization primitives are the highest priority.

We focused on things that require /different/ implementations in host and device code.

The way you implement std::binary_search is the same in host and device code. Sure, we can stick `__host__ __device__` on it for you, but it's not really high value.

Synchronization primitives? Clocks? They are completely different. In fact, the machinery that we use to implement both the synchronization primitives and clocks has not previously been exposed in CUDA C++.