HIPIFY VS OpenRAND

Compare HIPIFY vs OpenRAND and see what are their differences.

HIPIFY

HIPIFY: Convert CUDA to Portable C++ Code (by ROCm)

OpenRAND

Reproducible random number generation for parallel computations (by msu-sparta)
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HIPIFY OpenRAND
5 1
417 24
4.1% -
9.8 7.3
4 days ago 3 months ago
C++ C++
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

HIPIFY

Posts with mentions or reviews of HIPIFY. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-02-23.

OpenRAND

Posts with mentions or reviews of OpenRAND. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-12-14.
  • Intel CEO: 'The entire industry is motivated to eliminate the CUDA market'
    13 projects | news.ycombinator.com | 14 Dec 2023
    > Generating random numbers is a bit complicated!

    I know! I just wrote a whole paper and published a library on this!

    But really, perhaps not as much as many from outside might think. The core of a Philox implementation can be around 50 lines of C++ [1], with all the bells and whistles maybe around 300-400. That implementation's performance equals CuRAND's , sometimes even surpasses it! (the API is designed to avoid maintaining any rng states on device memory, something curand forces you to do).

    > running the same PRNG with the same seed on all your cores will produce the same result

    You're right. Solution here is to utilize multiple generator objects, one per thread, ensuring each produces statistically independent random streams. Some good algorithms (Philox for example), allow you to use any set of unique values as seeds for your threads (e.g. thread id).

    [1] https://github.com/msu-sparta/OpenRAND/blob/main/include/ope...

What are some alternatives?

When comparing HIPIFY and OpenRAND you can also consider the following projects:

ZLUDA - CUDA on AMD GPUs

Cgml - GPU-targeted vendor-agnostic AI library for Windows, and Mistral model implementation.

llama-cpp-python - Python bindings for llama.cpp

stable-diffusion - This version of CompVis/stable-diffusion features an interactive command-line script that combines text2img and img2img functionality in a "dream bot" style interface, a WebGUI, and multiple features and other enhancements. [Moved to: https://github.com/invoke-ai/InvokeAI]

stable-diffusion-webui - Stable Diffusion web UI

HIPIFY - HIPIFY: Convert CUDA to Portable C++ Code [Moved to: https://github.com/ROCm/HIPIFY]

ROCm - ROCm Website [Moved to: https://github.com/ROCm/ROCm.github.io]