cuda-api-wrappers VS soui

cuda-api-wrappers

• VUDA: A Vulkan Implementation of CUDA
  3 projects | news.ycombinator.com | 1 Jul 2023

  1. This implements the clunky C-ish API; there's also the Modern-C++ API wrappers, with automatic error checking, RAII resource control etc.; see: https://github.com/eyalroz/cuda-api-wrappers (due disclosure: I'm the author)

  2. Implementing the _runtime_ API is not the right choice; it's important to implement the _driver_ API, otherwise you can't isolate contexts, dynamically add newly-compiled JIT kernels via modules etc.

  3. This is less than 3000 lines of code. Wrapping all of the core CUDA APIs (driver, runtime, NVTX, JIT compilation of CUDA-C++ and of PTX) took me > 14,000 LoC.

• WezTerm is a GPU-accelerated cross-platform terminal emulator
  4 projects | news.ycombinator.com | 13 Mar 2023

  > since the underlying API's are still C/C++,

  If the use of GPUs is via CUDA, there are my https://github.com/eyalroz/cuda-api-wrappers/ which are RAII/CADRe, and therefore less unsafe. And on the Rust side - don't you need a bunch of unsafe code in the library enabling GPU support?

• GNU Octave
  4 projects | news.ycombinator.com | 21 Jan 2023

  Given your criteria, you might want to consider (modern) C++.

  * Fast - in many cases faster than Rust, although the difference is inconsequential relative to Python-to-Rust improvement I guess.

  * _Really_ utilize CUDA, OpenCL, Vulcan etc. Specifically, Rust GPU is limited in its supported features, see: https://github.com/Rust-GPU/Rust-CUDA/blob/master/guide/src/... ...

  * Host-side use of CUDA is at least as nice, and probably nicer, than what you'll get with Rust. That is, provided you use my own Modern C++ wrappers for the CUDA APIs: https://github.com/eyalroz/cuda-api-wrappers/ :-) ... sorry for the shameless self-plug.

  * ... which brings me to another point: Richer offering of libraries for various needs than Rust, for you to possibly utilize.

  * Easier to share than Rust. A target system is less likely to have an appropriate version of Rust and the surrounding ecosystem.

  There are downsides, of course, but I was just applying your criteria.

• How CUDA Programming Works
  1 project | news.ycombinator.com | 5 Jul 2022

  https://github.com/eyalroz/cuda-api-wrappers

  I try to address these and some other issues.

  We should also remember that NVIDIA artificially prevents its profiling tools from supporting OpenCL kernels - with no good reason.

• are there communities for cuda devs so we can talk and grow together?
  1 project | /r/CUDA | 24 Jun 2022

  On the host side however - the API you use to orchestrate execution of kernels on GPUs, data transfers etc. - the official API is very C'ish, annoying and confusing. I have written C++'ish wrappers for it which many enjoy but are of course not officially supported or endorsed: https://github.com/eyalroz/cuda-api-wrappers

• Thin C++-Flavored Wrappers for the CUDA APIs: Runtime, Driver, Nvrtc and NVTX
  1 project | news.ycombinator.com | 22 Jun 2022
• Integrating the CUDA APIs (Driver, Runtime, JIT) in pleasant modern-C++ wrappers
  1 project | news.ycombinator.com | 26 Mar 2022
• Cybercriminals who breached Nvidia issue one of the most unusual demands ever
  3 projects | news.ycombinator.com | 4 Mar 2022

  Oh, I really wish those hackers would release the sources rather than pursue their dumbass crypto-mining demands... "We decided to help mining and gaming community" - hurting the gaming community, helping the get-rich-quick "community".

  My own C++ wrappers for the CUDA APIs (shameless self-plug: https://github.com/eyalroz/cuda-api-wrappers/) would really benefit a lot from behind-the-curtains access to the driver; and even if I just know how the internal logic of the driver and the runtime works, without actually being able to hook into that logic - I would already be able to leverage this somewhat in my design considerations.

• AMD’s Lisa Su Breaks Through the Silicon Ceiling
  1 project | news.ycombinator.com | 25 Sep 2021

  As a person making a living from being the "GPU guy" - I definitely agree.

  The ecosystem around AMD GPUs is quite small - and now that they seem to have abandoned OpenCL (possibly not their own fault though) - even that is put into question.

  But things are bad even on the NVIDIA side. Example of how bad: I had to write my own C++ bindings for the CUDA runtime API (https://github.com/eyalroz/cuda-api-wrappers/). You'd think they would have that after 13 years of CUDA being available, right? Wrong. I repeatedly tried to pitch this to them, but they seem to suffer from the "Not Invented Here" syndrome (https://learnosity.com/not-invented-here-syndrome-explained/). This despite me having a lot of respect for people like Mark Harris, Bryce Lelbach, Duane Merrill et alia, and their work.

  You're also rights about the "two kinds of brains" - or rather, it's not clear to me that the brains creating the silicon and the brains creating the software are in close enough cooperation.

  By the way - it is possible to extract a pretty distribution of CUDA to justify run 20 lines of GPGPU code, from their installer. But they won't be bothered to package this nicely for you.

• How do I use gpus (c++)
  1 project | /r/learnprogramming | 2 May 2021

  Try Vulcan, or OpenCL. There are tons of wrappers for CUDA to make coding simpler ie https://github.com/eyalroz/cuda-api-wrappers

soui

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