dream-textures VS ZLUDA

Compare dream-textures vs ZLUDA and see what are their differences.

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dream-textures ZLUDA
72 35
7,584 7,544
- -
5.8 6.1
19 days ago 10 days ago
Python Rust
GNU General Public License v3.0 only Apache License 2.0
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.

dream-textures

Posts with mentions or reviews of dream-textures. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-05-17.

ZLUDA

Posts with mentions or reviews of ZLUDA. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-03-05.
  • Open-source project ZLUDA lets CUDA apps run on AMD GPUs
    5 projects | news.ycombinator.com | 5 Mar 2024
    It now supports AMD GPUs since 3 weeks ago, check the latest commit at the repo:

    https://github.com/vosen/ZLUDA

    The article also mentions exactly this fact.

  • Nvidia bans using translation layers for CUDA software
    1 project | news.ycombinator.com | 5 Mar 2024
    Looks like nvidia is trying to keep the lynchpin of their entire business model from crumbling underneath them. ZLUDA lets you run unmodified CUDA applications with near-native performance on AMD GPUs.

    https://github.com/vosen/ZLUDA

    With Triton looking to eclipse CUDA entirely, im not sure this prohibition does anything more than placate casual shareholders.

  • Nvidia bans using translation layers for CUDA software to run on other chips
    2 projects | news.ycombinator.com | 4 Mar 2024
    >Dark API functions are reverse-engineered and implemented by ZLUDA on a case-by-case basis once we observe an application making use of it.

    https://github.com/vosen/ZLUDA/blob/master/ARCHITECTURE.md

  • Nvidia hits $2T valuation as AI frenzy grips Wall Street
    2 projects | news.ycombinator.com | 23 Feb 2024
    > I know AMD have their competition, but their GPU software division keeps tripping over itself.

    They are actively stepping on every rake there is. Eg they just stopped supporting the drop-in-cuda project everyone is waiting for, due to there being "no business-case for CUDA on AMD GPUs" [0].

    [0] https://github.com/vosen/ZLUDA?tab=readme-ov-file#faq

  • Nvidia Is Now More Valuable Than Amazon and Google
    3 projects | news.ycombinator.com | 12 Feb 2024
    https://github.com/vosen/ZLUDA

    They still funded it and it was created.

  • Debian on Apple hardware (M1 and later)
    1 project | news.ycombinator.com | 12 Feb 2024
  • AMD Funded a Drop-In CUDA Implementation Built on ROCm: It's Open-Source
    23 projects | news.ycombinator.com | 12 Feb 2024
    From the same repo, I found this excellent, well-written architecture document: https://github.com/vosen/ZLUDA/blob/master/ARCHITECTURE.md

    I love the direct, "no bullshit" style of writing.

    Some gems:

    > Anyone familiar with C++ will instantly understand that compiling it is a complicated affair.

    > Additionally CUDA allows, to a large degree, mixing CPU code and GPU code. What does all this complexity mean for ZLUDA? Absolutely nothing

    > Since an application can dynamically link to either Driver API or Runtime API, it would seem that ZLUDA needs to provide both. In reality very few applications dynamically link to Runtime API. For the vast majority of applications it's sufficient to provide Driver API for dynamic (runtime) linking.

  • Intel CEO: 'The entire industry is motivated to eliminate the CUDA market'
    13 projects | news.ycombinator.com | 14 Dec 2023
    CUDA is huge and nvidia spent a ton in a lot of "dead end" use cases optimizing it. There have been experiments with CUDA translation layers with decent performance[1]. There are two things that most projects hit:

    1. The CUDA API is huge; I'm sure Intel/AMD will focus on what they need to implement pytorch and ignore every other use case ensuring that CUDA always has the leg up in any new frontier

    2. Nvidia actually cares about developer experience. The most prominent example is Geohotz with tinygrad - where AMD examples didn't even work or had glaring compiler bugs. You will find nvidia engineer in github issues for CUDA projects. Intel/AMD hasn't made that level of investment and thats important because GPUs tend to be more fickle than CPUs.

    [1] https://github.com/vosen/ZLUDA

  • Why Nvidia Keeps Winning: The Rise of an AI Giant
    3 projects | news.ycombinator.com | 6 Jul 2023
    > I don't think you understand just how insanely difficult it is to break into that market.

    You're right, I have no clue nor have I ever tried myself.

    > Even with apple money or something like that, it's a losing prospect because in the time it'll take you to get up and off the ground (which is FOREVER) your competition will crush you.

    This I find hard to believe, do you have a source or reference for that claim? Companies with that amount of cash are hardly going to be crushed by competition be it direct or indirect. Anyway, I'm talking more about the Intels and AMDs of this world.

    We have very lacklustre efforts from players I won't name with their Zluda library (https://github.com/vosen/ZLUDA) which I got REALLY excited about, until I read the README.txt. Four contributors, last commit early 2021.

    Why, oh why, is it this bad?

  • Intel Arc Graphics Driver Change Leads To A Big Speed-Up Under Linux
    3 projects | /r/linux | 24 Jun 2023

What are some alternatives?

When comparing dream-textures and ZLUDA you can also consider the following projects:

stable-diffusion-webui - Stable Diffusion web UI

InvokeAI - InvokeAI is a leading creative engine for Stable Diffusion models, empowering professionals, artists, and enthusiasts to generate and create visual media using the latest AI-driven technologies. The solution offers an industry leading WebUI, supports terminal use through a CLI, and serves as the foundation for multiple commercial products.

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]

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

stable-diffusion - Optimized Stable Diffusion modified to run on lower GPU VRAM

ROCm - AMD ROCm™ Software - GitHub Home [Moved to: https://github.com/ROCm/ROCm]

stable-diffusion-nvidia-docker - GPU-ready Dockerfile to run Stability.AI stable-diffusion model v2 with a simple web interface. Includes multi-GPUs support.

HIPIFY - HIPIFY: Convert CUDA to Portable C++ Code

DeepBump - Normal & height maps generation from single pictures

HIP - HIP: C++ Heterogeneous-Compute Interface for Portability

stable-diffusion-webui - Stable Diffusion web UI [Moved to: https://github.com/Sygil-Dev/sygil-webui]

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