In order to get maximum capability of these utilities, you should be running with a kernel that provides support of the GPUs you have installed. If using AMD GPUs, installing the latest amdgpu driver package or the latest ROCm release, may provide additional capabilities. If you have Nvidia GPUs installed, you should have nvidia-smi installed in order for the utility reading of the cards to be possible. Writing to GPUs is currently only possible for AMD GPUs.
A generative adversarial network that takes images and re-does them in various anime studios' styles. GPU enabled. Download the pre-trained model to get a jumpstart.
Nyuzi is an experimental GPGPU processor hardware design focused on compute intensive tasks. It is optimized for use cases like deep learning and image processing.
This project includes a synthesizable hardware design written in System Verilog, an instruction set emulator, an LLVM based C/C++ compiler, software libraries, and tests. It can be used to experiment with microarchitectural and instruction set design tradeoffs.
The Nouveau project is developing opensource drivers for nVidia graphics cards that support both 2d and 3d acceleration. While it's nifty, it's still in the very early stages of development.
Hashkill is a FOSS password cracker that uses the OpenSSL libraries as its back end. It uses plugins to implement different password types, hashes, and even file types (like passworded .zip files). It's even CUDA aware and can use Nvidia GPUs to accelerate password cracking.
Broadcom opensourced the GPU drivers for the RaspberryPi under a three-clause BSD license. The code is fully functional, hasn't been reverse engineered, and can be compiled and used imediately on the RasPi.
Can be used with audio files and probably a hot mic to transcribe speech into text for later processing. Uses git Large File Storage for the neural network objects. GPU acceleration enabled. Includes trained models as well as source code. Available in PyPy as deepspeech and deepspeech-gpu. Supports the RasPi explicitly as a platform, interestingly.
Looking at the releases page is a good way to keep up with the project: https://github.com/mozilla/DeepSpeech/releases
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