Search Results for "gpu process"
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Showing 77 open source projects for "gpu process"
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GPU Hot
Real-time NVIDIA GPU dashboard
GPU Hot is an open-source, lightweight monitoring dashboard designed to provide real-time visibility into NVIDIA GPU performance across single machines or entire clusters. The project offers a self-hosted web interface that streams hardware metrics directly from GPU servers, enabling developers, ML engineers, and system administrators to observe GPU utilization and system behavior in real time through a browser. The dashboard collects and displays a wide range of performance metrics... -
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Nvitop
An interactive NVIDIA-GPU process viewer and beyond
nvitop is an interactive NVIDIA device and process monitoring tool. It has a colorful and informative interface that continuously updates the status of the devices and processes. As a resource monitor, it includes many features and options, such as tree-view, environment variable viewing, process filtering, process metrics monitoring, etc. Beyond that, the package also ships a CUDA device selection tool nvisel for deep learning researchers. It also provides handy APIs that allow developers... -
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Zenith
Sort of like top or htop but with zoom-able charts, CPU, GPU
In terminal graphical metrics for your *nix system written in Rust. The make file provides for building fully static versions on Linux against the musl C library. It requires musl-gcc to be installed on the system. Install "musl-tools" package on debian/ubuntu derivatives, "musl-gcc" on fedora and equivalent on other distributions from their standard repos. If one needs to build with NVIDIA support in a virtual environment, then it requires some more setup since typically the VM software is... -
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Genv
GPU environment management and cluster orchestration
Genv is an open-source environment and cluster management system for GPUs. Genv lets you easily control, configure, monitor and enforce the GPU resources that you are using in a GPU machine or cluster. It is intended to ease up the process of GPU allocation for data scientists without code changes. -
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GameMode
Optimise Linux system performance on demand
GameMode is a daemon/lib combo for Linux that allows games to request a set of optimizations be temporarily applied to the host OS and/or a game process. GameMode was designed primarily as a stop-gap solution to problems with the Intel and AMD CPU power save or on-demand governors but is now host to a range of optimization features and configurations. -
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NVTOP
GPU & Accelerator process monitoring for AMD, Apple, Huawei, Intel
NVTOP stands for Neat Video card TOP, a (h) top-like task monitor for GPUs and accelerators. It can handle multiple GPUs and print information about them in a htop-familiar way. Currently supported vendors are AMD (Linux AMD GPU driver), Apple (limited M1 & M2 support), Huawei (Ascend), Intel (Linux i915 driver), NVIDIA (Linux proprietary divers), and Qualcomm Adreno (Linux MSM driver). -
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btop
A monitor of resources
btop is a cross-platform, C++ resource monitor featuring a terminal-based UI, rich visuals, and live stats for CPU, RAM, disks, networks, and processes. It supports mouse controls, filters, signal sending (SIGTERM/KILL), theme customization, GPU, battery support, and runs on Linux, macOS, BSD (with specific builds), via static binaries linked with musl. -
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AlphaFold 3
AlphaFold 3 inference pipeline
...The system is designed for scientific research applications in structural biology, biochemistry, and bioinformatics, enabling accurate modeling of proteins, ligands, and covalent modifications. Users can perform local predictions via Docker containers, integrating AlphaFold 3’s inference process with provided JSON input configurations. The software includes flexible options for running both data preprocessing and GPU-accelerated inference, allowing users to adapt to available computational resources. -
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Axolotl
Go ahead and axolotl questions
Axolotl is a powerful and flexible framework for fine-tuning large language models on custom datasets. Built for researchers and developers, Axolotl simplifies the process of adapting LLMs for specific tasks, including chat, code generation, and instruction following. It supports a wide variety of model architectures and offers out-of-the-box optimization strategies for efficient training. -
Award-Winning Medical Office Software Designed for Your SpecialtyRXNT is an ambulatory healthcare technology pioneer that empowers medical practices and healthcare organizations to succeed and scale through innovative, data-backed, AI-powered software.
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autoresearch
AI agents autonomously run and improve ML experiments overnight
...Designed to run on a single GPU, it keeps the research loop minimal and self-contained to make autonomous experimentation practical. Over time, the agent logs experiments, evaluates improvements, and gradually evolves the model through automated trial-and-error. -
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SGE_GPU
Patch to SGE 2011.p1,Son of Grid Engine, multiple GPU, Linux
...Here, "-l ngpus=1" request 1 GPU for 1 process. It supports multiple GPU scheduling on nodes as well. For example, if node001 has 4 GPUs installed. JobA uses GPU0, JobB uses GPU2, and then JobC requestes 2 GPUs, it can dispatch GPU1 and GPU3 to JobC, and set the environment for the job on node001: CUDA_VISIBLE_DEVICES=1,3 For non-GPU jobs, it is set to empty. -
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autoresearch-macos
AI agents running research on single-GPU nanochat training
...The system follows a structured loop in which an agent modifies a training script, executes a fixed-duration experiment, evaluates performance metrics, and decides whether to keep or revert changes. It is designed to operate efficiently within macOS environments, making it accessible for developers working outside traditional high-performance GPU clusters. The project typically includes components such as data preparation scripts, a training loop, and an instruction file that guides the agent’s behavior. By automating experimentation and optimization, it allows continuous improvement without manual intervention, effectively turning research into a self-improving process. -
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Matcha-TTS
A fast TTS architecture with conditional flow matching
...Users can train on standard datasets like LJSpeech or plug in their own corpora, with helper tools for computing dataset statistics, extracting phoneme durations, and running multi-GPU training. -
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Halide
A language for fast, portable data-parallel computation
...It was designed to make writing high-performance image and array processing code much easier on modern machines. It works on all major operating systems and with several CPU architectures (X86, ARM, MIPS, Hexagon, PowerPC) and GPU Compute APIs (CUDA, OpenCL, OpenGL, among others). It isn't a standalone programming language however; rather it is embedded in C++ which means that you write C++ code, building an in-memory representation of a Halide pipeline using Halide's C++ API. This representation can then be compiled to an object file, or a JIT-compile and run in the same process. ... -
15
GPT4All
Run Local LLMs on Any Device. Open-source
GPT4All is an open-source project that allows users to run large language models (LLMs) locally on their desktops or laptops, eliminating the need for API calls or GPUs. The software provides a simple, user-friendly application that can be downloaded and run on various platforms, including Windows, macOS, and Ubuntu, without requiring specialized hardware. It integrates with the llama.cpp implementation and supports multiple LLMs, allowing users to interact with AI models privately. This... -
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Face Alignment
2D and 3D Face alignment library build using pytorch
Detect facial landmarks from Python using the world's most accurate face alignment network, capable of detecting points in both 2D and 3D coordinates. Build using FAN's state-of-the-art deep learning-based face alignment method. For numerical evaluations, it is highly recommended to use the lua version which uses identical models with the ones evaluated in the paper. More models will be added soon. By default, the package will use the SFD face detector. However, the users can alternatively... -
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MESHROOM
3D reconstruction software
...Take advantage of motorized-head file. Easy to integrate in your Renderfarm System. Add specific rules to select the most suitable machines regarding CPU, RAM, GPU requirements of each Node. -
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QtScrcpy
Android real-time display control software
QtScrcpy connects to Android devices via USB (or via TCP/IP) for display and control. It does NOT require the root privileges. It supports three major platforms: GNU/Linux, Windows and MacOS. You can write your own script to map keyboard and mouse actions to touches and clicks of the mobile phone according to your needs. A script for "PUBG mobile" and TikTok mapping is provided by default. Once enabled, you can play the game with your keyboard and mouse as the PC version. or you can use... -
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AI YouTube Shorts Generator
A python tool that uses GPT-4, FFmpeg, and OpenCV
AI-YouTube-Shorts-Generator is a Python-based tool that automates the creation of short-form vertical video clips (“shorts”) from longer source videos — ideal for adapting content for platforms like YouTube Shorts, Instagram Reels, or TikTok. It analyzes input video (whether a local file or a YouTube URL), transcribes audio (with optional GPU-accelerated speech-to-text), uses an AI model to identify the most compelling or engaging segments, and then crops/resizes the video and applies... -
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X-AnyLabeling
Effortless data labeling with AI support from Segment Anything
X-AnyLabeling is an open-source data annotation platform designed to streamline the process of labeling datasets for computer vision and multimodal AI applications. The software integrates an AI-powered labeling engine that allows users to generate annotations automatically with the assistance of modern vision models such as Segment Anything and various object detection frameworks. It supports labeling tasks across images and videos and enables developers to prepare training datasets for... -
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higgsfield
Fault-tolerant, highly scalable GPU orchestration
Higgsfield is an open-source, fault-tolerant, highly scalable GPU orchestration, and a machine learning framework designed for training models with billions to trillions of parameters, such as Large Language Models (LLMs). -
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Cog
Package and deploy machine learning models using Docker containers
...Cog also resolves compatibility issues between frameworks and GPU libraries by automatically selecting compatible combinations of CUDA, cuDNN, and machine learning frameworks such as PyTorch or TensorFlow. Cog automatically generates a RESTful HTTP API for running predictions, enabling models to be accessed programmatically through a built-in prediction server. -
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Tracy Profiler
Frame profiler
A real-time, nanosecond resolution, remote telemetry, hybrid frame, and sampling profiler for games and other applications. Tracy supports profiling CPU (Direct support is provided for C, C++, Lua and Python integration. At the same time, third-party bindings to many other languages exist on the internet, such as Rust, Zig, C#, OCaml, Odin, etc.), GPU (All major graphic APIs: OpenGL, Vulkan, Direct3D 11/12, OpenCL.), memory allocations, locks, context switches, automatically attribute... -
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OpenShell
OpenShell is the safe, private runtime for autonomous AI agents.
OpenShell is an open-source runtime designed to safely run autonomous AI agents in isolated environments. Developed by NVIDIA, it provides sandboxed execution spaces that protect system resources, credentials, and data from unauthorized access. Each agent runs inside a containerized sandbox governed by declarative YAML security policies that control network access, file permissions, and process behavior. The platform includes a gateway service that manages sandbox lifecycles and routes AI... -
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Insanely Fast Whisper
An opinionated CLI to transcribe Audio files w/ Whisper on-device
...It leverages modern optimizations such as batch processing, mixed precision, and advanced attention mechanisms like Flash Attention to significantly reduce inference time while maintaining high transcription accuracy. The project is built on top of the Transformers ecosystem and integrates with libraries such as Optimum to maximize GPU efficiency. It is specifically engineered for environments with CUDA-enabled GPUs or Apple Silicon devices, allowing users to process hours of audio in minutes or even seconds depending on hardware capabilities. The tool provides a streamlined CLI interface, making it easy to run transcription tasks on local files or URLs without needing to write custom code. ...
