Search Results for "gpu"
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Showing 1017 open source projects for "gpu"
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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. -
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GPU Puzzles
Solve puzzles. Learn CUDA
GPU Puzzles is an educational project designed to teach GPU programming concepts through interactive coding exercises and puzzles. Instead of presenting traditional lecture-style explanations, the project immerses learners directly in hands-on programming tasks that demonstrate how GPU computation works. The exercises are implemented using Python with the Numba CUDA interface, which allows Python code to compile into GPU kernels that run on CUDA-enabled hardware. ... -
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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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NVIDIA Linux Open GPU Kernel Module
NVIDIA Linux open GPU kernel module source
This is the source release of the NVIDIA Linux open GPU kernel modules, version 530.41.03. Note that the kernel modules built here must be used with GSP firmware and user-space NVIDIA GPU driver components from a corresponding 530.41.03 driver release. Currently, the kernel modules can be built for x86_64 or aarch64. If cross-compiling, set these variables on the make command line. Any reasonably modern version of GCC or Clang can be used to build the kernel modules. -
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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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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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QualityScaler
Image/video AI upscaler app (BSRGAN)
...QualityScaler is completely written in Python, from the backend to the front end. Image/list of images upscale. Video upscale. Drag&drop files [image / multiple images/video] Automatic image tiling and merging to avoid gpu VRAM limitation. Resize image/video before upscaling. Multiple Gpu support. Compatible images - png, jpeg, bmp, webp, tif. Compatible video - mp4, wemb, gif, mkv, flv, avi, mov, qt. -
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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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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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MangoHud
A Vulkan and OpenGL overlay for monitoring FPS, temperatures, CPU/GPU
A Vulkan and OpenGL overlay for monitoring FPS, temperatures, CPU/GPU load and more. mangoplot is a plotting script that is shipped with MangoHud: on a given folder, it takes each log file, makes a 1D heatmap of its framerates, then stacks the heat maps vertically to form a 2D graph for easy visual comparison between benchmarks. -
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Numbast
Build an automated pipeline that converts CUDA APIs into Numba
Numbast is an automated toolchain that bridges CUDA C++ and Python by generating Numba-compatible bindings directly from CUDA header files. Its primary goal is to eliminate the manual effort required to expose CUDA libraries to Python, enabling developers to use GPU-accelerated functionality in Python environments more easily. The system parses CUDA C++ declarations and converts them into Python bindings that can be used within Numba, allowing seamless integration with Python-based GPU workflows. This approach significantly improves developer productivity by reducing boilerplate code and ensuring consistency between C++ and Python interfaces. ... -
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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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Numba CUDA Target
The CUDA target for Numba
Numba CUDA Target is NVIDIA’s maintained CUDA backend for the Numba JIT compiler, enabling developers to write GPU-accelerated code directly in Python. It allows users to define CUDA kernels using Python syntax, which are then compiled into efficient GPU code at runtime using LLVM-based toolchains. This approach significantly lowers the barrier to entry for GPU programming by eliminating the need to write CUDA C++ while still delivering high performance. -
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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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ChefKiss Inferno
Emulating Apple Silicon devices
Inferno by ChefKissInc is a low-level systems project focused on enabling hardware acceleration and advanced graphics compatibility on Apple Silicon devices, particularly within unsupported or experimental environments. It is designed to bridge gaps between macOS hardware capabilities and software ecosystems that traditionally rely on different GPU architectures, such as those found in Linux or Windows environments. The project typically operates at the intersection of kernel extensions, GPU drivers, and virtualization layers, aiming to unlock performance features that are otherwise restricted or unavailable. Inferno is especially relevant for developers working on emulation, virtualization, or cross-platform graphics stacks, as it attempts to expose native GPU functionality in unconventional contexts. ... -
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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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XenosRecomp
A tool for converting Xbox 360 shaders to HLSL
XenosRecomp is a specialized project within the Hedge-dev ecosystem that focuses on recompiling and reconstructing the Xenos GPU pipeline used in the Xbox 360, enabling accurate rendering when porting games to modern platforms. It works alongside CPU recompilation tools by translating GPU-specific instructions and behaviors into equivalents that can be executed on modern graphics APIs such as DirectX or Vulkan. This allows recompiled games to maintain visual fidelity while benefiting from modern hardware acceleration. ... -
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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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AirLLM
AirLLM 70B inference with single 4GB GPU
AirLLM is an open source Python library that enables extremely large language models to run on consumer hardware with very limited GPU memory. The project addresses one of the main barriers to local LLM experimentation by introducing a memory-efficient inference technique that loads model layers sequentially rather than storing the entire model in GPU memory. This layer-wise inference approach allows models with tens of billions of parameters to run on devices with only a few gigabytes of VRAM. ... -
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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).
