This is the Linux app named Tiny CUDA Neural Networks whose latest release can be downloaded as Version2.0sourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
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Tiny CUDA Neural Networks
DESCRIPTION
This is a small, self-contained framework for training and querying neural networks. Most notably, it contains a lightning-fast "fully fused" multi-layer perceptron (technical paper), a versatile multiresolution hash encoding (technical paper), as well as support for various other input encodings, losses, and optimizers. We provide a sample application where an image function (x,y) -> (R,G,B) is learned. The fully fused MLP component of this framework requires a very large amount of shared memory in its default configuration. It will likely only work on an RTX 3090, an RTX 2080 Ti, or high-end enterprise GPUs. Lower-end cards must reduce the n_neurons parameter or use the CutlassMLP (better compatibility but slower) instead. tiny-cuda-nn comes with a PyTorch extension that allows using the fast MLPs and input encodings from within a Python context. These bindings can be significantly faster than full Python implementations; in particular for the multiresolution hash encoding.
Features
- Tiny CUDA neural networks have a simple C++/CUDA API
- Learn a 2D image
- Requires an NVIDIA GPU
- Requires Windows: Visual Studio 2019
- Requires Linux: GCC/G++ 7.5 or higher
- Requires CUDA v10.2 or higher and CMake v3.21 or higher.
Programming Language
C++
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/tiny-cuda-neural-netw.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
