Search Results for "gpu process" - Page 3
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Showing 57 open source projects for "gpu process"
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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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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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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. ...
