cuda-api-wrappers VS conan

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.

> 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?

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.

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.

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

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.

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.

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

Silly question: What's the difference between C++20 modules and https://conan.io? (Google was vague, and ChatGPT, you know, sometimes makes things up so I rather ask fellow humans...)

Conan is a package manager for C/C++. See: https://conan.io/.

The way it works is that you can provide "recipes", which are Python scripts, that automate the process of collecting source code (usually from a remote Git repository, or a remote source tarball), patching it, making its dependencies and transitive dependencies available, building for specific platform and architecture (via any number of build systems), then packaging up and serving binaries. There's a lot of complexity involved.

Here are the two recipes I mentioned:

libcurl: https://github.com/conan-io/conan-center-index/blob/master/r...

OpenSSL v3: https://github.com/conan-io/conan-center-index/blob/master/r...

Now, for the sake of this thread I want to highlight three things here:

- Conan recipes are usually made by people unaffiliated with the libraries they're packaging;

- The recipes are fully Turing-complete, do a lot of work, have their own bugs - therefore they should really be treated as software comonents themselves, for the purpose of OSS clearing/supply chain verification, except as far as I know, nobody does it;

- The recipes can, and do, patch source code and build scripts. There's supporting infrastruture for this built into Conan, and of course one can also do it by brute-force search and replace. See e.g. ZLib recipe that does it both at the same time:

https://github.com/conan-io/conan-center-index/blob/7b0ac710... -- `_patch_sources` does both direct search-and-replace in source files, and applies the patches from https://github.com/conan-io/conan-center-index/tree/master/r....

Now, good luck keeping track of what's going on there.

There were various approaches recommended depending on our language and ecosystem. My classmates who developed using Node.js were recommended npm, and PyPI or poetry for Python. Since my program is written in C++, I was recommended to look into one of vcpkg or conan, but I ultimately did not use either package manager.

Hi u/instinkt900, Conan maintainer here. Thanks for your feedback! Please remember that we actively monitor and respond to our issue tracker on GitHub (https://github.com/conan-io/conan/issues/new/choose), we’d love to hear about your specific use cases or pain points, so that we can improve your experience and that of other users. The motivation behind most of the updates in Conan 2.0 was precisely feedback from the community, and to improve our ability to continue delivering features in the constantly changing C++ ecosystem. We can certainly do this at a quicker pace, with some exciting new features recently released and in the pipeline: package metadata, transparent backup of downloaded package sources, cache least-recently-used cleanup, etc. A lot of the big decisions that we took for Conan 2.0 were taken with consensus from expert users and contributors (https://conan.io/tribe) and https://github.com/conan-io/tribe. Some specific workflows may not have 1:1 replacements in Conan 2.0, and are likely to affect some of the “less travelled roads” of Conan 1.x, including some features that were always marked as experimental. We are happy to hear feedback so that we can best satisfy these use cases. Conan 2.0 also includes a more sophisticated API to cover cases where the built-in integrations may not satisfy users needs. For what it’s worth - we have also heard very positive feedback from users about how Conan 2.0 simplifies their workflows when compared to Conan 1.x. The C++ tooling ecosystem is fragmented and moves at different speeds, including our users. So it’s always a fine balancing act, but we don’t want to leave anyone behind! An example is Conan Center - over 90% (~1200) of all recipes have been migrated to support Conan 2.0, while still maintaining compatibility with Conan 1.x, precisely to avoid breaking users that are still on Conan 1.x.

Solution: don't use git submodules - use a package manager like Conan or vcpkg.

The closest thing we have at the moment is conan[1]. It’s a cross platform package manager that attempts to implement “toolchains”, whereby different build systems can be integrated[2]. This is a big problem with package management in C/C++, there’s no single, standardised build system that most projects use. There isn’t even a standardised compiler! So when hosting your own packages using Conan, often you need to make sure you build your application for three different compilers, for three different platforms. Sometimes (for modern MacOS) also for two different architectures each.

If you control the compiler AND build system you can get away with just one package for most cases. This true for Microsoft’s C/C++ package manager, NuGet[3]

Historically, the convention has been to use the package manager of the underlying system to install packages, as there are so many different build configurations to worry about when packaging the libraries. The other advantage of using the system package manager is that dependencies (shared libraries) that are common can be shared between many applications, saving space.

[1] https://conan.io/

Anyway, the problems are today starting to get fewer, as more an more adopt standard cross-platform portable build systems, a.k.a. CMake and package managers such as vcpkg or Conan. Together this will take care of building, installing, linking and using the entire dependency tree.

Simply use a package manager: Crypto++ is available on both vcpkg and Conan.

If you want a specific version or provide a more integrated workflow that is easier to use across platforms and among many developers, use a package manager like vcpkg or Conan.

I do however always recommend using a package manager: vcpkg or Conan to install and integrate third party libraries (together with CMake). This normally solves all the typical problems with dependencies.