Search Results for "gpu process" - Page 3
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Showing 67 open source projects for "gpu process"
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Rio
A hardware-accelerated GPU terminal emulator powered by WebGPU.
Rio is a terminal application that’s built with Rust, WebGPU, Tokio runtime. It targets to have the best frame per second experience as long you want, but is also configurable to use as minimal from GPU. It also relies on Rust memory behavior, since Rust is a memory-safe language that employs The terminal renderer is based on redux state machine, lines that has not updated will not suffer a redraw. Looking for the minimal rendering process in most of the time. Rio is also designed to support WebAssembly runtime so in the future you will be able to define how a tab system will work with a WASM plugin written in your favorite language. ... -
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Stable Diffusion
A latent text-to-image diffusion model
Stable Diffusion is a widely used open-source latent text-to-image diffusion model developed by the CompVis group for generating high-quality images from natural language prompts. The model operates by conditioning a diffusion process on text embeddings produced by a CLIP text encoder, enabling detailed and controllable image synthesis. It was trained on large-scale image datasets and later fine-tuned to produce 512×512 images with strong visual fidelity. Because the system runs efficiently... -
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Diffusers-Interpret
Model explainability for Diffusers
...To analyze how a token in the input prompt influenced the generation, you can study the token attribution scores. You can also check all the images that the diffusion process generated at the end of each step. Gradient checkpointing also reduces GPU usage, but makes computations a bit slower. -
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What happens when
What happens when you type google into your browser and press enter?
What happens when is a large collaborative documentation-style project that aims to answer in exhaustive detail the canonical interview/thought experiment question, “What happens when you type google into your browser and press Enter?” Rather than giving a high-level overview, the repository tries to break down every step in the process, from low-level events (keyboard press, OS events, keyboard interrupts), through OS-level handling (keyboard scan codes, key events), parsing, DNS lookup, networking (ARP, socket creation, TCP/TLS handshake), HTTP requests, browser behavior, HTML/CSS/JS parsing, rendering engine, GPU rendering, layout, to final drawing and user-visible output. ... -
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Robust Video Matting (RVM)
Robust Video Matting in PyTorch, TensorFlow, TensorFlow.js, ONNX
We introduce a robust, real-time, high-resolution human video matting method that achieves new state-of-the-art performance. Our method is much lighter than previous approaches and can process 4K at 76 FPS and HD at 104 FPS on an Nvidia GTX 1080Ti GPU. Unlike most existing methods that perform video matting frame-by-frame as independent images, our method uses a recurrent architecture to exploit temporal information in videos and achieves significant improvements in temporal coherence and matting quality. Furthermore, we propose a novel training strategy that enforces our network on both matting and segmentation objectives. ... -
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The intellectual system of Eidos
http://lc.kubagro.ru/
http://lc.kubagro.ru/ http://lc.kubagro.ru/aidos/index.htm http://lc.kubagro.ru/aidos/_Aidos-X.htm On the IBM PC, the Eidos system started working in 1992. MS Windows has been running since 2012. Implemented in Alaska+Express. I want to try to translate some modes, and maybe all of them, to the Harbor. The full source text in a single file is here: http://lc.kubagro.ru/__AIDOS-X.txt Responsible Secretary Kubgau scientific journal, Professor of computer science Department Kubgau... -
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YouTube-8M
Starter code for working with the YouTube-8M dataset
youtube-8m is Google’s open source starter code and reference implementation for training and evaluating machine learning models on the YouTube-8M dataset, one of the largest video understanding datasets publicly released. The repository provides a complete pipeline for video-level and frame-level modeling using TensorFlow, including data reading, model training, evaluation, and inference. It was developed to support the YouTube-8M Video Understanding Challenge (hosted on Kaggle and featured... -
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LUMINOTH
Deep Learning toolkit for Computer Vision
LUMINOTH is an open-source deep learning toolkit designed for computer vision tasks, particularly object detection. The framework is implemented in Python and built on top of TensorFlow and the Sonnet neural network library, providing a modular environment for training and deploying detection models. It was created to simplify the process of building and experimenting with deep learning models capable of identifying objects within images. Luminoth includes support for popular object... -
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Caffe Framework
Caffe, a fast open framework for deep learning
Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR) and by community contributors. Yangqing Jia created the project during his PhD at UC Berkeley. Caffe is released under the BSD 2-Clause license. Expressive architecture encourages application and innovation. Models and optimization are defined by configuration without hard-coding. Switch between CPU and GPU by setting a single flag to train on a GPU machine... -
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Otil
All in one system diagnostics utility
...Update (23/12/15): Small fixes and UI suggestions implemented. Added network summary to right-hand tab. Added minimize to tray with temp/util info on right-click. Added process icon to Processes. Fixed Net summary text placement. Fixed 1px line at bottom of app. Added animations to transition between main screens (up/down). Added animations to transition between simple and detailed screens (left/right). What Otil does: Fetches System, CPU, GPU, RAM, HDD, Network, Processes, Services, and Startup information about your machine. ... -
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Accelerated Feature Extraction Tool
A fast GPU accelerated feature extraction software for speech analysis
A fast feature extraction software tool for speech analysis and processing. It incorporates standard MFCC, PLP, and TRAPS features. The tool is a specially designed to process very large audio data sets. It uses GPU acceleration if compatible GPU available (CUDA as weel as OpenCL, NVIDIA, AMD, and Intel GPUs are supported). CPU SSE intrinsic instruction set is used in cases where no compatible GPU present. The output files are stored in HTK format. The software is developed at Department of Cybernetics at University of West Bohemia in Pilsen. -
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DynaSys
An easy-to-use dynamical systems modeler with great visualizations.
Just type in your difference equations, parameters, and variables and watch your dynamical system evolve. Examine a single path or an entire vector field. Change parameters and watch the effects in real time. Load and save models and data. Enter nullclines and Jacobians identification and classification of equilibria. Auto-generate fast C implementations of your model and fit them to data using Matlab, with optional GPU support. The long-term goal is to incorporate this into software... -
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openExposureFusion
HDR images generation from bracketed LDR images
Create HDR images from a series of images taken with different exposures. Use your GPU to accelerate the process and view the results in real time. OpenCL support is REQUIRED. -
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reg_stack
For registering stacks of 2D images.
reg_stack is an extension to the open source project, NiftyReg, for the coregistration of a series of 2D images representing a 3D block tissue subjected to histological serial sectioning. The software performs a series of nonlinear image transformations across a kernel of user-specified size to restore data continuity, as the sectioning process results in misalignments and distortions. The NiftyReg package also includes optimizations for parallelization on either the CPU or GPU. reg_stack leverages this feature and extends it to include support for running simultaneous instances of reg_f3d (NiftyReg) on multiple GPUs. -
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Cognitive Stability and Flexibility FIT
GPU Accelerated Fitting of Behavioral Data by a Physiological Model
Using the NVIDIA-CUDA framework, mcmc_min is able to efficiently sample the Bayesian posterior distribution over the parameters of a physiologically derived model of a task-switching and distractor inhibition paradigm. The model features a working-memory module, implementing the currently active task rule in terms of a two-dimensional stochastic dynamical system with three attractor states (rule 1, rule 2, spontaneous). The working memory module is given inputs representing the task cue in... -
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Open Broadcaster Software
Free, open source software for live streaming and recording
NOTE: Please visit our website for downloads. Open Broadcaster Software is free and open source software for the purposes of streaming live media content to the internet or to video files. Originally I made Open Broadcaster Software for myself because I thought "why should I pay a subscription for software I could probably write?" And so, I did and Open Broadcaster Software evolved into somewhat of a monster of a project. That's pretty much the Open Broadcaster Software story. I hope... -
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Ministral 3 8B Reasoning 2512
Efficient 8B multimodal model tuned for advanced reasoning tasks.
Ministral 3 8B Reasoning 2512 is a balanced midsize model in the Ministral 3 family, delivering strong multimodal reasoning capabilities within an efficient footprint. It combines an 8.4B-parameter language model with a 0.4B vision encoder, enabling it to process both text and images for advanced reasoning tasks. This version is specifically post-trained for reasoning, making it well-suited for math, coding, and STEM applications requiring multi-step logic and problem-solving. Despite its reasoning-focused training, the model remains edge-optimized and can run locally on a single 24GB GPU in BF16, or under 12GB when quantized. ...
