Search Results for "gpu hardware"
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Showing 267 open source projects for "gpu hardware"
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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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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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Libre Hardware Monitor
Monitor temperature sensors, fan speed, voltage, load & clock speeds
...LibreHardwareMonitor supports modern Intel and AMD CPUs, major GPU vendors, storage devices, and network adapters. Built on modern .NET versions, it continues to evolve with frequent updates and broad community contributions. Licensed under MPL 2.0, it offers a transparent and extensible alternative to proprietary hardware monitoring tools. -
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Easy GPU PV
A Project dedicated to making GPU Partitioning on Windows easier
Easy-GPU-PV is an open-source project that automates the relatively complex steps required to set up GPU Paravirtualization (GPU-PV) on Windows Hyper-V, letting you partition a physical GPU and assign slices to virtual machines for low-latency remote use. It creates and installs a Windows VM, copies the necessary GPU-PV driver files into the VM, and helps install Parsec (an ultra-low-latency remote-desktop client) so you can connect to the VM at high framerates. ... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Open Hardware Monitor
Monitor temperature sensors, fan speeds, voltages, load & clock speeds
...It can also read Intel and AMD processor temperature sensors, GPU sensors from ATI and Nvidia cards, and SMART hard drive temperatures. Users can view monitored values in the main window, system tray, or a customizable desktop gadget. Open Hardware Monitor runs on 32-bit and 64-bit Windows systems as well as x86-based Linux operating systems without requiring installation. -
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NVIDIA GPU Operator
NVIDIA GPU Operator creates/configures/manages GPUs atop Kubernetes
Kubernetes provides access to special hardware resources such as NVIDIA GPUs, NICs, Infiniband adapters and other devices through the device plugin framework. 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. -
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Fan Control
Highly customizable fan controlling software for Windows
Fan Control is a Windows utility designed to give users fine-grained, customizable control over system fans (CPU, GPU, case, etc.) based on temperature and sensor inputs. Rather than relying solely on BIOS fan curves, it allows dynamic adjustment of fan behaviour at the operating-system level — letting you react to real-time load, mix multiple sensors (CPU, GPU, motherboard, drives, etc.), and define custom fan-speed curves for different situations. The tool supports both manual mode (user... -
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GPU-Z
Lightweight GPU information and diagnostics tool.
GPU-Z is a specialized and lightweight system utility designed to provide in-depth information about your video card and graphics processor. It offers comprehensive support for a wide range of graphics devices from NVIDIA, AMD, ATI, and Intel. The application delivers detailed data on the adapter, GPU specifications, and display information. It accurately reports clock speeds, including default, overclocked, 3D, and boost clocks. Furthermore, it provides a detailed analysis of the memory... -
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jamesob's guide to running SOTA LLMs
Everything I know about running LLMs locally
jamesob's guide to running SOTA LLMs is a practical guide and configuration repository for running high-end language models on local hardware. It documents one developer’s local LLM setup, including hardware choices, GPU layout, storage, PCIe switches, kernel settings, and serving workflows. The repository compares budget levels ranging from dual RTX 3090 systems to high-end multi-GPU workstations with very large VRAM pools. It includes ready-to-run serving configurations for selected models and local speech-to-text workloads. ... -
Host LLMs in Production With On-Demand GPUsDeploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
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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. -
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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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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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TrafficMonitor
Floating window used to display current network speed, CPU & memory
...There are two versions of TrafficMonitor, the standard version and the Lite version. The standard version includes all the functions, while the Lite version does not include hardware monitoring functions such as temperature monitoring, GPU usage, and hard disk usage. The standard version requires administrator privilege to run, while the Lite version does not. -
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Rio Terminal
A hardware-accelerated GPU terminal emulator
Rio is a hardware-accelerated GPU terminal emulator built with Rust and WebGPU. It is designed to run across desktops and browser-oriented environments while keeping performance and usability at the center of the experience. The project supports modern terminal expectations such as 24-bit true color, tabs, split panes, font ligatures, and terminal graphics. -
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llmfit
157 models, 30 providers, one command to find what runs on hardware
llmfit is a terminal-based utility that helps developers determine which large language models can realistically run on their local hardware by analyzing system resources and model requirements. The tool automatically detects CPU, RAM, GPU, and VRAM specifications, then ranks available models based on performance factors such as speed, quality, and memory fit. It provides both an interactive terminal user interface and a traditional CLI mode, enabling flexible workflows for different user preferences. llmfit also supports advanced configurations including multi-GPU setups, mixture-of-experts architectures, and dynamic quantization recommendations. ... -
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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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Stats
macOS system monitor in your menu bar
Stats currently supported on macOS 10.13 (High Sierra) and higher. Stats is an application that allows you to monitor your macOS system. CPU utilization, GPU utilization, memory usage, disk utilization, sensors information (Temperature/Voltage/Power), battery level, network usage, fans speed, fan control, and Bluetooth devices. Supports many languages, such as English, Polski, Українська, Русский, and many more. You can help by adding a new language or improve existing translation. -
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Hardware Serial Spoofer
An open-source tool for managing and modifying hardware ID
Hardware Identity Manager (HIM) is a powerful utility designed for advanced users, developers, and security researchers to manage the hardware identification values of their Windows-based systems. -
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CubeCL
Multi-platform high-performance compute language extension for Rust
CubeCL is a low-level compute language and compiler framework designed to simplify and optimize GPU programming for high-performance workloads, particularly in machine learning and numerical computing. It provides an abstraction layer that allows developers to write portable, hardware-efficient compute kernels without directly dealing with complex GPU APIs such as CUDA or OpenCL. CubeCL focuses on delivering predictable performance and composability by exposing explicit control over memory layouts, parallelism, and execution patterns while still maintaining a developer-friendly syntax. ... -
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FlexLLMGen
Running large language models on a single GPU
FlexLLMGen is an open-source inference engine designed to run large language models efficiently on limited hardware resources such as a single GPU. The system focuses on high-throughput generation workloads where large batches of text must be processed quickly, such as large-scale data extraction or document analysis tasks. Instead of requiring expensive multi-GPU systems, the framework uses techniques such as memory offloading, compression, and optimized batching to run large models on commodity hardware. -
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GPUStack
Performance-optimized AI inference on your GPUs
GPUStack is an open-source GPU cluster management platform designed to simplify the deployment and operation of artificial intelligence models across heterogeneous hardware environments. The system aggregates GPU resources from multiple machines into a unified cluster so developers and administrators can run large language models and other AI workloads efficiently across distributed infrastructure. -
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CUDA-Q
C++ and Python support for the CUDA Quantum programming model
...It provides a full toolchain that includes compilers, runtimes, and libraries for writing quantum programs in both C++ and Python. The platform is designed to be hardware-agnostic, allowing developers to run applications on different quantum backends or simulate them efficiently using GPU acceleration when physical quantum hardware is unavailable. It enables complex workflows where classical and quantum computations are tightly integrated, supporting advanced research and real-world applications in quantum computing. ... -
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NumPy
The fundamental package for scientific computing with Python
...NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more. NumPy supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and sparse array libraries. The core of NumPy is well-optimized C code. Enjoy the flexibility of Python with the speed of compiled code. NumPy’s high level syntax makes it accessible and productive for programmers from any background or experience level. Distributed under a liberal BSD license, NumPy is developed and maintained publicly on GitHub by a vibrant, responsive, and diverse community. ... -
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HeavyDB
HeavyDB (formerly MapD/OmniSciDB)
...HeavyDB was originally developed as part of the OmniSci platform (formerly MapD) and is commonly used for large-scale analytics and geospatial data processing. The database compiles queries into optimized machine code that executes efficiently on GPU hardware, significantly accelerating analytical workloads. It supports hybrid deployment environments where queries can run on both CPU and GPU architectures depending on the available resources. -
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Parallax
Parallax is a distributed model serving framework
Parallax is a decentralized inference framework designed to run large language models across distributed computing resources. Instead of relying on centralized GPU clusters in data centers, the system allows multiple heterogeneous machines to collaborate in serving AI inference workloads. Parallax divides model layers across different nodes and dynamically coordinates them to form a complete inference pipeline. A two-stage scheduling architecture determines how model layers are allocated to available hardware and how requests are routed across nodes during execution. ...