Search Results for "computer system optimization" - Page 4
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Showing 3215 open source projects for "computer system optimization"
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ArrayFire
ArrayFire, a general purpose GPU library
ArrayFire is a general-purpose tensor library that simplifies the process of software development for the parallel architectures found in CPUs, GPUs, and other hardware acceleration devices. The library serves users in every technical computing market. Data structures in ArrayFire are smartly managed to avoid costly memory transfers and to take advantage of each performance feature provided by the underlying hardware. The community of ArrayFire developers invites you to build with us if... -
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Catlab.jl
A framework for applied category theory in the Julia language
Catlab.jl is a framework for applied and computational category theory, written in the Julia language. Catlab provides a programming library and interactive interface for applications of category theory to scientific and engineering fields. It emphasizes monoidal categories due to their wide applicability but can support any categorical structure that is formalizable as a generalized algebraic theory. First and foremost, Catlab provides data structures, algorithms, and serialization for... -
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All-in-RAG
Big Model Application Development Practice 1
...It explains the full development pipeline required to create knowledge-aware AI assistants, including data preparation, document indexing, vector embedding generation, and retrieval strategies. The project also explores advanced topics such as hybrid retrieval methods, query optimization, and evaluation techniques for improving system accuracy. Alongside theoretical explanations, the repository includes hands-on exercises and example projects that demonstrate how to build production-ready RAG systems. These projects guide developers through the process of integrating vector databases, embedding models, and large language models into a unified application. -
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MuJoCo
Multi-Joint dynamics with Contact. A general purpose physics simulator
MuJoCo, developed and maintained by Google DeepMind, is a high-performance physics engine designed for simulating complex, articulated systems that interact through contact. It is widely used in research fields such as robotics, biomechanics, computer graphics, animation, and machine learning, where fast and accurate physics simulations are essential. The engine provides a robust C API optimized for real-time computation, making it suitable for scientific research and advanced simulation... -
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ComfyUI-Copilot
AI assistant for ComfyUI workflow generation, debugging, and tuning
ComfyUI-Copilot is an AI-powered assistant designed to extend the capabilities of ComfyUI by simplifying and automating complex workflow development tasks. It functions as a custom node integrated directly into the ComfyUI environment, allowing users to interact with workflows through natural language and intelligent suggestions. ComfyUI-Copilot focuses on reducing the complexity of building node-based pipelines for generative AI tasks such as image generation, making it more accessible to... -
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Cradle framework
The Cradle framework is a first attempt at General Computer Control
Cradle is an open-source framework designed to enable AI agents to perform complex computer tasks by interacting with software environments in a way similar to human users. The system introduces the concept of General Computer Control, where AI agents receive screenshots as input and perform actions through simulated keyboard and mouse operations. This approach allows agents to interact with any software interface without relying on specialized APIs or predefined automation scripts. ... -
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CUDA Agent
Large-Scale Agentic RL for High-Performance CUDA Kernel Generation
CUDA Agent is a research-driven agentic reinforcement learning system designed to automatically generate and optimize high-performance CUDA kernels for GPU workloads. The project addresses the long-standing challenge that efficient CUDA programming typically requires deep hardware expertise by training an autonomous coding agent capable of iterative improvement through execution feedback. Its architecture combines large-scale data synthesis, a skill-augmented CUDA development environment, and long-horizon reinforcement learning to build intrinsic optimization capability rather than relying on simple post-hoc tuning. ... -
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SEO GEO Content Engine
Professional SEO and GEO content workflows for brands, SaaS teams
SEO GEO Content Engine is a comprehensive system designed to combine content generation, optimization, and analysis into a single AI-driven pipeline. It builds on tools like GEO Content Writer and SEO GEO Audit to create an end-to-end workflow for producing and refining search-optimized content. The system automates the process of identifying opportunities, generating content, and validating its effectiveness based on modern search criteria. -
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HFS (HTTP File Server)
HFS is a web file server to run on your computer
HFS is a lightweight HTTP file server for Windows that allows users to share files over the web easily, turning their local machine into a file server. -
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gpt-prompt-engineer
Experimental prompt optimization toolkit built around notebooks
gpt-prompt-engineer is an experimental prompt optimization toolkit built around notebooks and LLM-assisted evaluation. It lets users describe a task, provide test cases, and generate many candidate prompts automatically. The system then tests those prompts against the examples and ranks their performance through an ELO-style scoring process. The repository includes versions for general prompt generation, classification tasks, Claude-based workflows, and model-to-model prompt conversion. ... -
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SwiftUI Agent Skill
SwiftUI agent skill for Claude Code, Codex, and other AI tools
...It provides structured guidance that helps AI tools generate more accurate, modern, and maintainable SwiftUI code by addressing common mistakes such as misuse of APIs, poor performance patterns, and accessibility oversights. The system includes a comprehensive review process that evaluates code across multiple dimensions, including navigation, data flow, design compliance, and performance optimization. It is specifically tailored to align with current Apple development standards, including modern Swift versions and accessibility requirements like VoiceOver support. ... -
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Booster
Optimizer for mobile applications
Booster is an easy-to-use, lightweight, powerful and extensible quality optimization toolkit designed specially for mobile applications. The primary goal is to solve quality problems with the increase of APP complexity, such as performance, stability, and package size, etc. Booster provides a collection of modules for performance detection, multithreading optimization, resources index inline, redundant resources reduction, resources compression, system bug fixing, etc. ... -
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Agent S
Agent S: an open agentic framework that uses computers like a human
Agent S is an open-source agentic framework designed to enable autonomous computer use through an Agent-Computer Interface (ACI). Built to operate graphical user interfaces like a human, it allows AI agents to perceive screens, reason about tasks, and execute actions across macOS, Windows, and Linux systems. The latest version, Agent S3, surpasses human-level performance on the OSWorld benchmark, demonstrating state-of-the-art results in complex multi-step computer tasks. Agent S combines... -
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Win Debloat Tools
Re-imagining Windows like a minimal OS install
Win Debloat Tools is an open-source PowerShell-based toolkit designed to strip away unnecessary components, preinstalled apps, and services from modern Windows installations to create a leaner, more responsive operating system. It aims to re-imagine Windows as if it were installed in a minimal state, removing bloatware and optional features with minimal impact on core functionality, though it warns users to proceed with caution since changes can be extensive. The project supports both... -
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DeepSpeed
Deep learning optimization library: makes distributed training easy
DeepSpeed is an easy-to-use deep learning optimization software suite that enables unprecedented scale and speed for Deep Learning Training and Inference. With DeepSpeed you can: 1. Train/Inference dense or sparse models with billions or trillions of parameters 2. Achieve excellent system throughput and efficiently scale to thousands of GPUs 3. Train/Inference on resource constrained GPU systems 4. -
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Xtuner
A Next-Generation Training Engine Built for Ultra-Large MoE Models
...XTuner is also designed to integrate with modern AI ecosystems, supporting multimodal training, reinforcement learning optimization, and instruction tuning pipelines. -
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VARLET
A Vue3 component library based on Material Design 2 and 3
Varlet UI is a Material design component library developed based on Vue3, supporting mobile and desktop, developed and maintained by varletjs organization. Support Typescript, import on demand, dark mode, theme customization, internationalization, and provide VSCode plugin to ensure a good development experience. -
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Winux Operating System
Breathe New Life Into Your Computer - www.winux.is
Break free from hardware restrictions and forced upgrades. Winux is the definitive successor for Windows 10 users seeking performance and reliability. Featuring an Intuitive Familiar Interface and Native Compatibility for your essential software. -
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claude-token-efficient
One CLAUDE.md file. Keeps Claude responses terse
...It is particularly useful in high-volume or agent-based workflows where output tokens accumulate quickly and significantly impact cost and latency. The system works best in iterative or automation-heavy environments where consistent formatting and brevity are more valuable than exploratory reasoning. -
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autoresearch-win-rtx
AI agents running research on single-GPU nanochat training
autoresearch-win-rtx is a Windows-based implementation of the autoresearch framework designed to run autonomous AI research loops on consumer NVIDIA RTX GPUs. It adapts the original autoresearch concept to a Windows environment, enabling users to perform iterative machine learning optimization without requiring specialized Linux or data center setups. The system revolves around a small set of core files, including a training script that is continuously modified by an AI agent, along with supporting utilities for data preparation and evaluation. Experiments are executed within a fixed time budget, ensuring consistent benchmarking across iterations and allowing the agent to focus on incremental improvements. ... -
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autoresearch-mlx
Apple Silicon (MLX) port of Karpathy's autoresearch
...It maintains the core autoresearch structure, where an AI agent iteratively edits a training script, executes experiments under a fixed time budget, and evaluates results based on a defined metric such as validation bits per byte. The system is tailored for Apple hardware, leveraging unified memory and MLX capabilities to achieve efficient training on Mac devices. It includes a minimal and focused project structure consisting of data preparation utilities, a modifiable training file, and a program specification that governs the agent’s behavior. The framework logs experiment results and supports continuous iteration, enabling long-running optimization cycles that can reveal hardware-specific performance patterns. -
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Lakka
Linux distribution that transforms a computers into game consoles
Lakka is a lightweight Linux distribution that transforms a small computer into a full-blown emulation console. Built on top of the famous RetroArch emulator, Lakka is able to emulate a large range of hardware and has some useful features such as Braid-like rewinding, joypad hotplug, and video streaming. Lakka is easy to set up and use. Once installed on your SD card, you just have to put your ROM on the card, plug your joypad, and enjoy your favorite old games. We also support PS3 and... -
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C/C++ for Visual Studio Code
Repository for the Microsoft C/C++ extension for VS Code
...Check with your instructors or colleagues for guidance on installing the recommended C++ toolset (compiler, debugger, project system, linter). -
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Open Interface
Control Any Computer Using LLMs
Open Interface is a cross-platform application that allows users to control their computers using large language models (LLMs). By sending user requests to an LLM backend, it determines the necessary steps and executes them by simulating keyboard and mouse inputs. The system can adjust its actions based on real-time feedback, providing a self-driving computer experience. -
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ScaleLLM
A high-performance inference system for large language models
ScaleLLM is a high-performance inference system tailored for Large Language Models (LLMs), specifically designed for production environments. It focuses on optimizing inference processes to handle large-scale deployments efficiently, ensuring low latency and high throughput. ScaleLLM supports various LLM architectures and integrates with existing infrastructures, providing a scalable solution for deploying LLMs in real-world applications.