chipStar
ncnn
| chipStar | ncnn | |
|---|---|---|
| 4 | 12 | |
| 147 | 19,310 | |
| 4.8% | 1.4% | |
| 9.7 | 9.4 | |
| 7 days ago | 4 days ago | |
| C++ | C++ | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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.
chipStar
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AMD Funded a Drop-In CUDA Implementation Built on ROCm: It's Open-Source
There is already a work-in-progress implementation of HIP on top of OpenCL https://github.com/CHIP-SPV/chipStar and the Mesa RustiCL folks are quite interested in getting that to run on top of Vulkan.
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Vcc – The Vulkan Clang Compiler
chipStar (formerly CHIP-SPV) might also be worth checking out: https://github.com/CHIP-SPV/chipStar
It compiles CUDA/HIP C++ to SPIR-V that can run on top of OpenCL or Level Zero. (It does require OpenCL's compute flavored SPIR-V, instead of graphics flavored SPIR-V as seen in OpenGL or Vulkan. I also think it requires some OpenCL extensions that are currently exclusive to Intel NEO, but should on paper be coming to Mesa's rusticl implementation too.
- ChipStar: Run CUDA/Hip on SPIR-V via OpenCL/Level Zero
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In the next 5 years, what do you think can push OpenCL adoption?
Regarding the second item (CUDA to OpenCL), have a look at hipstar: https://github.com/CHIP-SPV/hipstar
ncnn
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AMD Funded a Drop-In CUDA Implementation Built on ROCm: It's Open-Source
ncnn uses Vulkan for GPU acceleration, I've seen it used in a few projects to get AMD hardware support.
https://github.com/Tencent/ncnn
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[D] Best way to package Pytorch models as a standalone application
They're using NCNN to package the model. Have a look. https://github.com/Tencent/NCNN
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Realtime object detection android app
Hi. Here is my prefered android app for realtime objet detection: https://github.com/nihui/ncnn-android-nanodet ; https://github.com/Tencent/ncnn contains a lot of android demo app for a lot of models.
- ncnn: High-performance neural network inference framework optimized for mobile
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Esp32 tensorflow lite
ncnn home page: https://github.com/Tencent/ncnn
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MMDeploy: Deploy All the Algorithms of OpenMMLab
ncnn
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Draw Things, Stable Diffusion in your pocket, 100% offline and free
Yes, Android devices tend to have bigger RAMs, making running 1024x1024 possible (this is not possible at all on iPhones, which could peak around 5GiB memory with my current implementation, some serious engineering required to bring that down on iPhone devices). The problem is I am not sure about speed. I would likely switch to NCNN (https://github.com/Tencent/ncnn) as the backend which have a decent Vulkan computing kernel support. It is definitely a possibility and there is a path to do that.
- What’s New in TensorFlow 2.10?
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[Technical Article] OCR Upgrade
As the leading open-source inference framework in China and in the world, what we like are its almost zero cost cross-platform capability, high inference speed, and minimal deployment volume. (Project address: https://github.com/Tencent/ncnn)
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Is there a functioning neural netowork or backbone written in pure C language only?
If you’re not planning on training the neural net on an embedded device and just do inference, this might interest you: https://github.com/Tencent/ncnn
What are some alternatives?
FluidX3D - The fastest and most memory efficient lattice Boltzmann CFD software, running on all GPUs via OpenCL.
XNNPACK - High-efficiency floating-point neural network inference operators for mobile, server, and Web
OpenCL-Wrapper - OpenCL is the most powerful programming language ever created. Yet the OpenCL C++ bindings are cumbersome and the code overhead prevents many people from getting started. I created this lightweight OpenCL-Wrapper to greatly simplify OpenCL software development with C++ while keeping functionality and performance.
rife-ncnn-vulkan - RIFE, Real-Time Intermediate Flow Estimation for Video Frame Interpolation implemented with ncnn library
Cgml - GPU-targeted vendor-agnostic AI library for Windows, and Mistral model implementation.
deepdetect - Deep Learning API and Server in C++14 support for Caffe, PyTorch,TensorRT, Dlib, NCNN, Tensorflow, XGBoost and TSNE
hipDNN - A thin wrapper around miOpen and cuDNN
netron - Visualizer for neural network, deep learning and machine learning models
llvm - Intel staging area for llvm.org contribution. Home for Intel LLVM-based projects.
darknet - Convolutional Neural Networks
RPi_64-bit_Zero-2-image - Raspberry Pi Zero 2 W 64-bit OS image with OpenCV, TensorFlow Lite and ncnn Framework.
torch-mlir - The Torch-MLIR project aims to provide first class support from the PyTorch ecosystem to the MLIR ecosystem.