gpufort
CLIP-Mesh
| gpufort | CLIP-Mesh | |
|---|---|---|
| 2 | 4 | |
| 158 | 416 | |
| 0.0% | - | |
| 0.0 | 3.9 | |
| 5 months ago | 5 months ago | |
| Fortran | Python | |
| MIT License | MIT License |
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.
gpufort
-
(Tutorial) Porting a simple Fortran application to GPUs with HIPFort
There is a gpufort project that provides something a bit more like what you're suggesting, but I'm not sure how useful it is in its current state.
-
AI Seamless Texture Generator Built-In to Blender
https://rocmdocs.amd.com/en/latest/Deep_learning/Deep-learni...
RadeonOpenCompute/ROCm_Documentation: https://github.com/RadeonOpenCompute/ROCm_Documentation
ROCm-Developer-Tools/HIPIFYhttps://github.com/ROCm-Developer-Tools/HIPIFY :
> hipify-clang is a clang-based tool for translating CUDA sources into HIP sources. It translates CUDA source into an abstract syntax tree, which is traversed by transformation matchers. After applying all the matchers, the output HIP source is produced.
ROCmSoftwarePlatform/gpufort: https://github.com/ROCmSoftwarePlatform/gpufort :
> GPUFORT: S2S translation tool for CUDA Fortran and Fortran+X in the spirit of hipify
ROCm-Developer-Tools/HIP https://github.com/ROCm-Developer-Tools/HIP:
> HIP is a C++ Runtime API and Kernel Language that allows developers to create portable applications for AMD and NVIDIA GPUs from single source code. [...] Key features include:
> - HIP is very thin and has little or no performance impact over coding directly in CUDA mode.
> - HIP allows coding in a single-source C++ programming language including features such as templates, C++11 lambdas, classes, namespaces, and more.
> - HIP allows developers to use the "best" development environment and tools on each target platform.
> - The [HIPIFY] tools automatically convert source from CUDA to HIP.
> - * Developers can specialize for the platform (CUDA or AMD) to tune for performance or handle tricky cases.*
CLIP-Mesh
-
New AI Can Procedurally Produce 3D Models From Text Input
I found a similar program called CLIP-Mesh that appears to be self-hosted.
- AI Seamless Texture Generator Built-In to Blender
-
[R] CLIP-Mesh: Generating textured meshes from text using pretrained image-text models
Code: Github
- Clip-Mesh: Generating textured meshes from text with pretrained image-text model
What are some alternatives?
stable_diffusion.openvino
HIPIFY - HIPIFY: Convert CUDA to Portable C++ Code [Moved to: https://github.com/ROCm/HIPIFY]
ZLUDA - CUDA on AMD GPUs
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]
aomp - AOMP is an open source Clang/LLVM based compiler with added support for the OpenMP® API on Radeon™ GPUs. Use this repository for releases, issues, documentation, packaging, and examples.
dream-textures - Stable Diffusion built-in to Blender
clang-ocl - OpenCL compilation with clang compiler.
CLIP - CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
i-love-compute
stable-diffusion-webui - Stable Diffusion web UI