Search Results for "hardware configuration"
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78 projects for "hardware configuration" with 1 filter applied:
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Full-stack observability with actually useful AI | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
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8 Monitoring Tools in One APM. Install in 5 Minutes.AppSignal works out of the box for Ruby, Elixir, Node.js, Python, and more. 30-day free trial, no credit card required.
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Minecraft server optimization guide
Minecraft server optimization guide
Minecraft Optimization Guide is an open-source documentation project that provides practical guidance for improving the performance of Minecraft servers. Rather than offering a single universal configuration, the guide explains how different server settings, software choices, and infrastructure decisions affect server performance and stability. It covers a wide range of topics including server software selection, configuration tuning, JVM parameters, hardware considerations, and common mistakes that can cause lag or instability. ... -
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OpenCorePkg
OpenCore bootloader
OpenCorePkg is an open-source, modular UEFI (Unified Extensible Firmware Interface) bootloader and development framework, primarily designed to enable macOS booting on non-Apple hardware (Hackintosh). It includes Apple-specific UEFI drivers, utilities for macOS installation support, and shared libraries used across Acidanthera projects. Apple disk image loading support. Apple keyboard input aggregation. Apple PE image signature verification. Apple UEFI secure boot supplemental code. Audio... -
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NetherSX2
Continuation of NetherSX2 based on AetherSX2 4248
NetherSX2-patch is a community-driven continuation and enhancement of the NetherSX2 Android PlayStation 2 emulator, itself a modded fork of the open-source AetherSX2 project originally based on PCSX2. It focuses on providing a more complete and feature-rich experience by applying patches to the upstream emulator build and removing ad-related bloat, fixing notification issues, and exposing many internal settings so users have finer control over performance and compatibility on mobile devices.... -
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Steam Deck Guide
Learn all about the Tools, Accessories, Games, Emulators
The Steam Deck Guide repository is a community-driven resource aimed at helping users get the most out of their Valve Steam Deck — covering everything from initial configuration and system tweaks to performance optimization, emulation workflows, game compatibility, and hardware customization. It begins with basic setup topics like installing updates, connecting peripherals, and configuring SteamOS settings, then progresses into intermediate skills such as managing storage, optimizing battery life, and fine-tuning performance profiles for demanding titles. ... -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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OSX Serial Generator
Generate complete sets of Serial Numbers for OSX-KVM, Docker-OSX
OSX Serial Generator is a shell-based toolkit for generating valid-looking macOS serial numbers, hardware UUIDs, and board serials for use in virtualized macOS environments such as OSX-KVM, Docker-OSX, and OpenCore-based Hackintosh setups. It is positioned for good-faith security and Apple bug bounty research, where having realistic device identifiers is necessary to reproduce issues or test services that validate Apple hardware details. -
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CoreNet
CoreNet: A library for training deep neural networks
CoreNet is Apple’s internal deep learning framework for distributed neural network training, designed for high scalability, low-latency communication, and strong hardware efficiency. It focuses on enabling large-scale model training across clusters of GPUs and accelerators by optimizing data flow and parallelism strategies. CoreNet provides abstractions for data, tensor, and pipeline parallelism, allowing models to scale without code duplication or heavy manual configuration. Its distributed runtime manages synchronization, load balancing, and mixed-precision computation to maximize throughput while minimizing communication bottlenecks. ... -
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mergekit
Tools for merging pretrained large language models
...This approach allows researchers to combine specialized models into a more versatile system capable of performing multiple tasks. mergekit implements a variety of merging algorithms and strategies that control how model parameters are blended together during the merging process. The library is designed to operate efficiently even in environments with limited hardware resources by using memory-efficient processing methods that can run entirely on CPUs. It also provides configuration-driven workflows that allow users to experiment with different merging strategies without modifying source code. -
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lmstudio.js
LM Studio TypeScript SDK
...The library exposes the same capabilities used internally by the LM Studio desktop application, allowing external apps to load models, run inference, and build autonomous AI workflows. It is designed to simplify the creation of local AI tools by handling complex concerns such as dependency management, hardware compatibility, and model configuration. The SDK introduces an agent-style API that can execute multi-step tool-using workflows through a single call, enabling more advanced automation scenarios. Applications built with the SDK can run anywhere LM Studio is available, whether in foreground or headless mode. Overall, lmstudio-js acts as a developer bridge between local LLM infrastructure and modern JavaScript applications. -
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kokoro-onnx
TTS with kokoro and onnx runtime
kokoro-onnx is a text-to-speech toolkit that wraps the Kokoro neural TTS model in an easy-to-use ONNX Runtime interface, so you can generate speech from Python with minimal setup. It focuses on running efficiently on commodity hardware, including macOS with Apple Silicon, while still delivering near real-time performance for many use cases. The project ships prebuilt model files and a simple example script, so you can go from installation to producing an audio.wav file in just a few steps. It supports multiple languages and voices, with a curated voice list and configuration via a VOICES file hosted alongside the models. ... -
Gemini 3 and 200+ AI Models on One PlatformBuild generative AI apps with Vertex AI. Switch between models without switching platforms.
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AI Runner
Offline inference engine for art, real-time voice conversations
AI Runner is an offline inference engine designed to run a collection of AI workloads on your own machine, including image generation for art, real-time voice conversations, LLM-powered chatbots and automated workflows. It is implemented as a desktop-oriented Python application and emphasizes privacy and self-hosting, allowing users to work with text-to-speech, speech-to-text, text-to-image and multimodal models without sending data to external services. At the core of its LLM stack is a... -
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Humanoid-Gym
Reinforcement Learning for Humanoid Robot with Zero-Shot Sim2Real
Humanoid-Gym is a reinforcement learning framework designed to train locomotion and control policies for humanoid robots using high-performance simulation environments. The system is built on top of NVIDIA Isaac Gym, which allows large-scale parallel simulation of robotic environments directly on GPU hardware. Its primary goal is to enable efficient training of humanoid robots in simulation while enabling policies to transfer effectively to real-world hardware without additional training.... -
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ESPectre
Motion detection system based on Wi-Fi spectre analysis (CSI)
ESPectre is an open-source motion detection system that transforms ordinary Wi-Fi signals into an ambient sensor capable of detecting movement without using cameras, microphones, or additional radio hardware, making it a privacy-preserving and cost-effective alternative for presence sensing and smart home automation. At its core, it analyzes Wi-Fi Channel State Information (CSI) — detailed measurements of how Wi-Fi waves change as they propagate — to mathematically detect disturbances caused... -
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uzu
A high-performance inference engine for AI models
...By utilizing Apple’s unified memory architecture, uzu reduces memory copying overhead and improves inference throughput for local AI workloads. The system includes a simple high-level API that enables developers to run models, create inference sessions, and generate outputs with minimal configuration. -
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OuteTTS
Interface for OuteTTS models
OuteTTS is an interface library for running OuteTTS text-to-speech models across a range of backends, making it easier to deploy the same model on different hardware and runtimes. It provides a high-level Interface API that wraps model configuration, speaker handling, and audio generation so you can focus on integrating speech into your application rather than wiring up low-level engines. The project supports multiple backends including llama.cpp (Python bindings and server), Hugging Face Transformers, ExLlamaV2, VLLM and a JavaScript interface via Transformers.js, allowing it to run on CPUs, NVIDIA CUDA GPUs, AMD ROCm, Vulkan-capable GPUs, and Apple Metal. ... -
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shimmy
Python-free Rust inference server
The shimmy project is a lightweight local inference server designed to run large language models with minimal overhead. Written primarily in Rust, the tool provides a small standalone binary that exposes an API compatible with the OpenAI interface, allowing existing applications to interact with local models without significant code changes. This compatibility enables developers to replace remote AI services with locally hosted models while keeping their existing software architecture... -
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Moltworker
Run OpenClaw on Cloudflare Workers
...The project includes web UIs, Cloudflare configuration files, and scripts to authenticate devices, manage environment secrets, and enable optional services like persistent R2 storage for chat history. -
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EPLB
Expert Parallelism Load Balancer
EPLB is DeepSeek’s open implementation of a load balancing algorithm designed for expert parallelism (EP) settings in MoE architectures. In EP, different “experts” are mapped to different GPUs or nodes, so load imbalance becomes a performance bottleneck if certain experts are invoked much more often. EPLB solves this by duplicating heavily used experts (redundancy) and then placing those duplicates across GPUs to even out computational load. It uses policies like hierarchical load balancing... -
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llama.vscode
VS Code extension for LLM-assisted code/text completion
llama.vscode is a Visual Studio Code extension that provides AI-assisted coding features powered primarily by locally running language models. The extension is designed to be lightweight and efficient, enabling developers to use AI tools even on consumer-grade hardware. It integrates with the llama.cpp runtime to run language models locally, eliminating the need to rely entirely on external APIs or cloud providers. The extension supports common AI development features such as code completion, conversational chat assistance, and AI-assisted code editing directly within the IDE. Developers can select and manage models through a configuration interface that automatically downloads and runs the required models locally. ... -
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memconf - memory configuration on UNIX
Identify sizes of memory modules installed on most UNIX-based systems
Identify sizes of memory modules installed on a Solaris, Linux, FreeBSD or HP-UX workstation or server. memconf reports the size of each SIMM/DIMM memory module installed in a system. It also reports the system type and any empty memory sockets. In verbose mode, it also reports the following information if available: - banner name, model and CPU/system frequencies - address range and bank numbers for each module -
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gpu_poor
Calculate token/s & GPU memory requirement for any LLM
gpu_poor is an open-source tool designed to help developers determine whether their hardware is capable of running a specific large language model and to estimate the performance they can expect from it. The project focuses on calculating GPU memory requirements and predicted inference speed for different models, hardware configurations, and quantization strategies. By analyzing factors such as model size, context length, batch size, and GPU specifications, the system estimates how much VRAM... -
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State of Open Source AI
Clarity in the current fast-paced mess of Open Source innovation
...Because the AI domain moves quickly, part of the aim is to make the content maintainable and updateable by the community. The structure includes chapters or sections about model formats, evaluation benchmarks, hardware/backends, MLOps systems, alignment and safety issues, and open datasets. The repository contains the text (in Markdown or similar), configuration for build or publishing (static site or e-book), and contributor guidelines. -
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WireGuard for Ubiquiti
WireGuard for Ubiquiti Devices
...The project provides scripts and packaging that allow administrators to deploy WireGuard tunnels on supported Ubiquiti routers, extending modern VPN capabilities to network edge hardware. It focuses on enabling secure site-to-site and remote access connectivity within environments that rely on Ubiquiti’s networking ecosystem. Because many embedded router platforms have unique constraints, the repository includes device-specific configuration logic and automation tailored to these systems. The project helps bridge the gap between WireGuard’s core protocol and real-world network appliance deployments, especially in small business and prosumer infrastructure. ... -
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Racktables is a nifty and robust solution for datacenter and server room asset management. It helps document hardware assets, network addresses, space in racks, networks configuration and much much more!
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YOLOv4-large
Scaled-YOLOv4: Scaling Cross Stage Partial Network
...Unlike earlier object detection systems that only scale depth or width, this architecture scales multiple aspects of the neural network including structure, resolution, and channel configuration. This scaling strategy enables the model to adapt to different hardware environments while maintaining a strong balance between speed and detection accuracy. The repository includes multiple model variants such as YOLOv4-tiny, YOLOv4-CSP, and large-scale configurations designed for high-performance detection tasks. -
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WMBars is a Window-Maker compatible dockapp that can monitor certain things dependant upon the XML-format configuration file. It displays up to three bar graphs with a title and value, but can monitor many more things.
