Showing 4 open source projects for "amd overclock linux"

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  • 1
    Apollo

    Apollo

    The easiest way to stream with the native resolution of your client

    Apollo is a self-hosted desktop streaming host designed to enable low-latency game streaming from a personal computer to remote clients using protocols compatible with Moonlight and Artemis. It acts as a server that captures, encodes, and streams desktop or game sessions while supporting hardware acceleration across AMD, Intel, and NVIDIA GPUs. The project includes a web-based interface that allows users to configure streaming settings, manage connected clients, and control application...
    Downloads: 156 This Week
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  • 2
    OptiScaler

    OptiScaler

    OptiScaler bridges upscaling/frame gen across GPUs

    OptiScaler is an open-source modding tool designed to enhance graphics performance and flexibility in modern PC games by allowing users to replace or modify built-in upscaling technologies. Instead of relying on the upscaling method originally integrated by a game developer, the software intercepts the game’s rendering pipeline and redirects it to alternative technologies chosen by the user. This makes it possible to swap technologies such as NVIDIA DLSS, AMD FSR, or Intel XeSS even if the...
    Downloads: 293 This Week
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  • 3
    enhancr

    enhancr

    Video Frame Interpolation & Super Resolution using NVIDIA's TensorRT

    ...It features blazing-fast TensorRT inference by NVIDIA, which can speed up AI processes significantly. Pre-packaged, without the need to install Docker or WSL (Windows Subsystem for Linux) - and NCNN inference by Tencent which is lightweight and runs on NVIDIA, AMD and even Apple Silicon - in contrast to the mammoth of an inference PyTorch is, which only runs on NVIDIA GPUs.
    Downloads: 12 This Week
    Last Update:
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  • 4
    Super-résolution via CNN

    Super-résolution via CNN

    Super resolution using a CNN, based on the work of the DGtal team

    Super-resolution using a CNN, based on the work of the DGtal team. First of all, an Nvidia graphics card (neither AMD nor Intel integrated) is highly recommended to parallelize the CNN. You will then need to install CUDA. No CUDA = dozens of times slower. This program will generate "model_epoch_ .pth" files corresponding to the model at epoch n, in a folder saved_model_u t_bs bs_tbs tbs_lr lr, where corresponds to the scale factor, bsthe size of the training batch, tbsthe size of the test...
    Downloads: 0 This Week
    Last Update:
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