Search Results for "gpu"
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Showing 723 open source projects for "gpu"
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NVIDIA GPU Exporter
Nvidia GPU exporter for prometheus using nvidia-smi binary
Nvidia GPU exporter for prometheus, using nvidia-smi binary to gather metrics. There are many Nvidia GPU exporters out there however they have problems such as not being maintained, not providing pre-built binaries, having a dependency to Linux and/or Docker, targeting enterprise setups (DCGM) and so on. -
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NVIDIA GPU Operator
NVIDIA GPU Operator creates/configures/manages GPUs atop Kubernetes
...However, configuring and managing nodes with these hardware resources requires the configuration of multiple software components such as drivers, container runtimes or other libraries which are difficult and prone to errors. The NVIDIA GPU Operator uses the operator framework within Kubernetes to automate the management of all NVIDIA software components needed to provision GPU. These components include the NVIDIA drivers (to enable CUDA), Kubernetes device plugin for GPUs, the NVIDIA Container Runtime, automatic node labeling, DCGM-based monitoring, and others. -
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Ricks-Lab GPU Utilities
A set of utilities for monitoring and customizing GPU performance
A set of utilities for monitoring GPU performance and modifying control settings. In order to get the maximum capability of these utilities, you should be running with a kernel that provides support for the GPUs you have installed. If using AMD GPUs, installing the latest AMD GPU driver or ROCm package 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. ... -
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AGI (Android GPU Inspector)
Android GPU Inspector
Android GPU Inspector (AGI) is a desktop tool for profiling, tracing, and debugging graphics workloads running on Android devices. It helps developers analyze Vulkan and OpenGL ES applications at the system, frame, and draw-call levels to uncover GPU and CPU bottlenecks. AGI captures detailed performance counters, timelines, and pipeline state to reveal stalls, overdraw, shader hotspots, and inefficient resource usage. -
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Upscayl
Free and Open Source AI Image Upscaler for Linux, MacOS and Windows
...Upscayl is a cross-platform application built with the Linux-first philosophy. This means that we prioritize Linux builds over others but that doesn't mean we'll break things for other OSes. Upscayl does not work without a GPU, sorry. You'll need a Vulkan-compatible GPU to upscale images. CPU or iGPU won't work. You can also download the flatpak version and double-click the flatpak file to install via Store but wait for the full release, we'll be pushing it to Flathub for easy access. Upscayl uses AI models to enhance your images by guessing what the details could be. ... -
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Kompute
General purpose GPU compute framework built on Vulkan
General purpose GPU compute framework built on Vulkan to support 1000s of cross-vendor graphics cards (AMD, Qualcomm, NVIDIA & friends). Blazing fast, mobile-enabled, asynchronous, and optimized for advanced GPU data processing use cases. Backed by the Linux Foundation. -
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KonaBess
A GPU overclock & undervolt tool for various Snapdragon chips
KonaBess is a straightforward application designed to customize GPU frequency and voltage tables without the need for kernel recompilation. The application achieves customization by unpacking the Boot/Vendor Boot image, decompiling and editing relevant dtb (device tree binary) files, and finally repacking and flashing the modified image. The extent of improvement varies, with some users reporting a 25% reduction in power consumption in the graphics benchmark (4.2w->3.2w) after undervolting the Snapdragon 865. ... -
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GPUArrays
Reusable array functionality for Julia's various GPU backends
Reusable GPU array functionality for Julia's various GPU backends. This package is the counterpart of Julia's AbstractArray interface, but for GPU array types: It provides functionality and tooling to speed-up development of new GPU array types. This package is not intended for end users! Instead, you should use one of the packages that builds on GPUArrays.jl, such as CUDA.jl, oneAPI.jl, AMDGPU.jl, or Metal.jl. -
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nviwatch
A blazingly fast rust based TUI for managing and monitoring NVIDIA GPU
NviWatch is an interactive terminal user interface (TUI) application for monitoring NVIDIA GPU devices and processes. Built with Rust, it provides real-time insights into GPU performance metrics, including temperature, utilization, memory usage, and power consumption. -
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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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XMRig
RandomX, KawPow, CryptoNight, AstroBWT and GhostRider unified miner
High performance, open-source, cross-platform RandomX, KawPow, CryptoNight, and AstroBWT CPU/GPU miner, RandomX benchmark, and stratum proxy. XMRig is a high-performance, open-source, cross-platform RandomX, KawPow, CryptoNight, and AstroBWT unified CPU/GPU miner and RandomX benchmark. Official binaries are available for Windows, Linux, macOS, and FreeBSD. The preferred way to configure the miner is the JSON config file as it is more flexible and human-friendly. -
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Gupax
GUI Uniting P2Pool And XMRig
A versatile tool designed for managing and analyzing GPU performance across tasks. -
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Kitty
Fast, Featureful, GPU based terminal emulator
Kitty is a fast GPU based terminal editor that allows you to offload rendering to the GPU for lower system load. Kitty works on Linux and macOS and uses OpenGL for rendering which makes it portable to other platforms similar to Unix. -
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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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Alacritty
A cross-platform, GPU-accelerated terminal emulator
...With such a strong focus on simplicity and performance, Alacritty’s included features are very carefully considered, ensuring that it remains blazingly fast. It’s got a GPU for rendering that makes a whole lot of optimizations possible. In various benchmarked terminals, Alacritty has shown to be either faster, or way faster than others. Alacritty requires no additional setup, but still allows configuration of many aspects of the terminal. It supports Windows, macOS, Linux and BSD. -
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CuPy
A NumPy-compatible array library accelerated by CUDA
CuPy is an open source implementation of NumPy-compatible multi-dimensional array accelerated with NVIDIA CUDA. It consists of cupy.ndarray, a core multi-dimensional array class and many functions on it. CuPy offers GPU accelerated computing with Python, using CUDA-related libraries to fully utilize the GPU architecture. According to benchmarks, it can even speed up some operations by more than 100X. CuPy is highly compatible with NumPy, serving as a drop-in replacement in most cases. CuPy is very easy to install through pip or through precompiled binary packages called wheels for recommended environments. ... -
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Video2X
A lossless video/GIF/image upscaler achieved with waifu2x, Anime4K
...Go to the GUI page to see the basic usage of the GUI. Try the mirror if you can't download releases directly from GitHub. You can use Video2X on Google Colab for free if you don't have a powerful GPU of your own. You can borrow a powerful GPU (Tesla K80, T4, P4, or P100) on Google's server for free for a maximum of 12 hours per session. Please use the free resource fairly and do not create sessions back-to-back and run upscaling 24/7. This might result in you getting banned. You can get Colab Pro/Pro+ if you'd like to use better GPUs and get longer runtimes. ... -
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LocalAI
Self-hosted, community-driven, local OpenAI compatible API
...Does not require GPU. -
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Flux.jl
Relax! Flux is the ML library that doesn't make you tensor
...Cutting-edge models such as Neural ODEs are first class, and Zygote enables overhead-free gradients. GPU kernels can be written directly in Julia via CUDA.jl. Flux is uniquely hackable and any part can be tweaked, from GPU code to custom gradients and layers. -
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GPUCompiler.jl
Reusable compiler infrastructure for Julia GPU backends
Reusable compiler infrastructure for Julia GPU backends. This package offers reusable compiler infrastructure and tooling for implementing GPU compilers in Julia. It is not intended for end users! Instead, you should use one of the packages that builds on GPUCompiler.jl, such as CUDA.jl or AMDGPU.jl. -
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Beta9
Run serverless GPU workloads with fast cold starts on bare-metal
beta9 is a platform that enables running serverless GPU workloads with fast cold starts on bare-metal servers globally. It allows developers to deploy and scale GPU-accelerated applications without managing underlying infrastructure, offering flexibility and efficiency for AI and high-performance computing tasks. beta9 supports various frameworks and provides tools for monitoring and managing deployments effectively. -
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Zenith
Sort of like top or htop but with zoom-able charts, CPU, GPU
...If one needs to build with NVIDIA support in a virtual environment, then it requires some more setup since typically the VM software is unable to directly expose NVIDIA GPU. Unlike the runtime zenith script, the Makefile has been setup to detect only the presence of required NVIDIA libraries, so it is possible to build with NVIDIA support even when without NVIDIA GPU. -
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CatBoost
High-performance library for gradient boosting on decision trees
...CatBoost offers superior performance over other GBDT libraries on many datasets, and has several superb features. It has best in class prediction speed, supports both numerical and categorical features, has a fast and scalable GPU version, and readily comes with visualization tools. CatBoost was developed by Yandex and is used in various areas including search, self-driving cars, personal assistance, weather prediction and more. -
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SwiftShader
SwiftShader is a high-performance CPU-based implementation
SwiftShader is Google’s high-performance CPU-based implementation of the Vulkan 1.3 graphics API, designed to provide a hardware-independent rendering solution for 3D graphics. Unlike traditional GPU drivers, SwiftShader executes graphics commands entirely on the CPU, making it ideal for environments where dedicated graphics hardware is unavailable or unsuitable. It acts as a drop-in replacement for Vulkan drivers, allowing existing applications to run seamlessly by redirecting API calls through its software-based rendering engine. ... -
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ImplicitGlobalGrid.jl
Distributed parallelization of stencil-based GPU and CPU applications
...Samuel Omlin) with Stanford University (Dr. Ludovic Räss) and the Swiss Geocomputing Centre (Prof. Yuri Podladchikov). It renders the distributed parallelization of stencil-based GPU and CPU applications on a regular staggered grid almost trivial and enables close to ideal weak scaling of real-world applications on thousands of GPUs [1, 2, 3]. ImplicitGlobalGrid relies on the Julia MPI wrapper (MPI.jl) to perform halo updates close to hardware limit and leverages CUDA-aware or ROCm-aware MPI for GPU-applications. ...
