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It's still early days for Vcc, I outline the caveats in the landing page. While I'm confident the control-flow bits and whatnot will work robustly, there's a bi

by g0b 3y ago

It's still early days for Vcc, I outline the caveats in the landing page. While I'm confident the control-flow bits and whatnot will work robustly, there's a big open question when it comes to the fate of standard libraries, the likes of libstdc++ were not designed for this use-case. We'll be working hard on it all the way to Vulkanized, if you have some applications you can get up and running by then, feel free to get in touch. I think the driver ecosystem for Vulkan is rather high-quality but that's more my (biased!) opinion that something I have hard data on. The Mesa/NIR-based drivers in particular are very nice to work with!

mathiasgredal 3y ago
Will C++17 parallel algorithms be supported? https://on-demand.gputechconf.com/supercomputing/2019/pdf/sc1936-gpu-programming-with-standard-c++17.pdf https://on-demand.gputechconf.com/supercomputing/2019/pdf/sc... Edit: Nevermind, I think I have misunderstood the purpose of this project. I thought it was a CUDA competitor, but it seems like it is just a shading language compiler for graphics.
- pjmlp 3y ago
  SYCL/DPC++ are the only viable CUDA competitors I would say, assuming that the tooling gets feature parity.
cloudhan 3y ago
Thoes "existing libraries" does not necessary mean stdc++, but some parallel primitive, and are essential to performance portability. For example, cub for scan and reduction, cutlass for dense linear algebra[1]. > I think the driver ecosystem for Vulkan is rather high-quality Sorry, I meant OpenGL. At the time of evaluation, the market shared of vulkan on Android deivces is too small and been out of consideration at very early stage. I'd assume the state has changed a lot thereafter. It is really good to see more projects take a shot on compiling C++ to GPU natively. [1] cutlass itself is not portable, but the recently added cute is well portable as I evaluated. It provides a unified abstraction for hierarchical layout decomposition along with copy primitive and gemm primitive.
cloudhan 3y ago
circle lang is also very worth to check out.

by g0b 3y ago

mathiasgredal 3y ago

Will C++17 parallel algorithms be supported? https://on-demand.gputechconf.com/supercomputing/2019/pdf/sc1936-gpu-programming-with-standard-c++17.pdf https://on-demand.gputechconf.com/supercomputing/2019/pdf/sc... Edit: Nevermind, I think I have misunderstood the purpose of this project. I thought it was a CUDA competitor, but it seems like it is just a shading language compiler for graphics.

pjmlp 3y ago
SYCL/DPC++ are the only viable CUDA competitors I would say, assuming that the tooling gets feature parity.

cloudhan 3y ago

Thoes "existing libraries" does not necessary mean stdc++, but some parallel primitive, and are essential to performance portability. For example, cub for scan and reduction, cutlass for dense linear algebra[1]. > I think the driver ecosystem for Vulkan is rather high-quality Sorry, I meant OpenGL. At the time of evaluation, the market shared of vulkan on Android deivces is too small and been out of consideration at very early stage. I'd assume the state has changed a lot thereafter. It is really good to see more projects take a shot on compiling C++ to GPU natively. [1] cutlass itself is not portable, but the recently added cute is well portable as I evaluated. It provides a unified abstraction for hierarchical layout decomposition along with copy primitive and gemm primitive.

cloudhan 3y ago

circle lang is also very worth to check out.