Search Results for "edge computing"
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15 projects for "edge computing" with 1 filter applied:
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KubeEdge
Kubernetes Native Edge Computing Framework (project under CNCF)
KubeEdge is built upon Kubernetes and extends native containerized application orchestration and device management to hosts at the Edge. It consists of a cloud part and an edge part, and provides core infrastructure support for networking, application deployment, and metadata synchronization between the cloud and edge. It also supports MQTT which enables edge devices to access through edge nodes. With KubeEdge it is easy to get and deploy existing complicated machine learning, image... -
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PicoLM
Run a 1-billion parameter LLM on a $10 board with 256MB RAM
...The runtime is capable of running language models with billions of parameters on devices with only a few hundred megabytes of memory, which is significantly lower than typical LLM infrastructure requirements. This makes PicoLM particularly suitable for edge computing, offline AI applications, and embedded AI devices that cannot rely on cloud resources. -
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mllm
Fast Multimodal LLM on Mobile Devices
mllm is an open-source inference engine designed to run multimodal large language models efficiently on mobile devices and edge computing environments. The framework focuses on delivering high-performance AI inference in resource-constrained systems such as smartphones, embedded hardware, and lightweight computing platforms. Implemented primarily in C and C++, it is designed to operate with minimal external dependencies while taking advantage of hardware-specific acceleration technologies such as ARM NEON and x86 AVX2 instructions. ... -
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Zvec
A lightweight, lightning-fast, in-process vector database
...Because it runs in-process, developers can embed it in native apps, microservices, or edge computing scenarios where traditional server-based vector databases might be overkill. -
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sebastian/diff
Diff implementation
...Internally, the library splits input into hunks and manages edge cases such as whitespace-only changes and end-of-line variations. Its abstractions make it straightforward to plug custom output styles or colorizers without reimplementing diff logic. Because it’s the diff engine under PHPUnit, it has been exercised across countless projects and edge cases. -
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ElatoAI
Realtime AI Voice Agents with SoTA Multimodal AI models on Arduino ESP
ElatoAI is a real-time AI voice agent platform built around IoT hardware (ESP32) that enables continuous speech-to-speech conversations using state-of-the-art multimodal voice models with minimal latency and global performance via edge computing. The system integrates voice synthesis and recognition by connecting an ESP32 device through secure WebSockets to edge server functions written in Deno, allowing users to speak naturally with AI agents hosted through cloud APIs including OpenAI’s Realtime API, Gemini’s Live API, xAI’s Grok Voice Agent API, and others. It includes a web client (built with Next.js) for managing devices, controlling volume, and viewing conversation transcripts, while the hardware runs optimized firmware to deliver responses in near real time — even supporting >15-minute uninterrupted conversations. -
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RuleGo
Component orchestration rule engine framework for Go
...It’s lightweight, embeddable, orchestration-ready, and built for flexible composition of business logic into reusable components. No external middleware dependencies, efficient data processing and linkage on low-cost devices, suitable for IoT edge computing. Embedded and Standalone Deployment modes. Supports embedding RuleGo into existing applications. It can also be deployed independently as middleware, providing rule engine and orchestration services. -
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Project MINI RACK
Miniature rack builds, for portable or compact Homelabs
Project MINI RACK is a project dedicated to designing, documenting, and showcasing compact, portable rack-mount or small-form factor “mini” labs, suitable for home labs, edge deployments, or mobile network stacks. The repository contains build guides, hardware lists, layout ideas (10” wide racks, 1U/2U modules, custom shelves), 3D printable components, and real-world examples of mini homelab rigs. Its goal is to help hobbyists, devops engineers, or tinkerers understand how to build... -
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Unikraft
A next-generation cloud native kernel designed to unlock performance
Unikraft powers the next generation of cloud-native, containerless applications by enabling you to radically customize and build custom OS/kernels; unlocking best-in-class performance, security primitives, and efficiency savings. Unikraft optimizes resource utilization, leading to smaller footprints (meaning higher server saturation) and improved efficiency in resource-constrained environments. Unikraft is an open-source project driven by a vibrant community of over 100 developers, fostering... -
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AssemblyScript
A TypeScript-like language for WebAssembly
...AssemblyScript integrates with the WebAssembly ecosystem, enabling seamless interaction with JavaScript through standard APIs. It is widely used in scenarios where performance and portability are essential, such as gaming, data processing, and edge computing. -
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Computer vision projects
computer vision projects | Fun AI projects related to computer vision
...The repository includes multiple demonstration systems implemented using languages such as Python and C++, covering topics ranging from object detection to embedded vision systems. Many of the projects illustrate how computer vision algorithms can interact with hardware platforms, including robotics systems and edge computing devices. The repository provides examples that combine machine learning models with real-world applications such as robotic arms, video analysis, and automated visual measurement systems. -
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dispy
Distributed and Parallel Computing with/for Python.
dispy is a generic and comprehensive, yet easy to use framework for creating and using compute clusters to execute computations in parallel across multiple processors in a single machine (SMP), among many machines in a cluster, grid or cloud. dispy is well suited for data parallel (SIMD) paradigm where a computation (Python function or standalone program) is evaluated with different (large) datasets independently. dispy supports public / private / hybrid cloud computing, fog / edge computing. -
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jetson-ffmpeg
ffmpeg support on jetson nano
...The project includes a library and patch system that modifies FFmpeg builds to enable NVMPI-based acceleration. This allows efficient processing of video streams on embedded systems without overloading CPU resources. jetson-ffmpeg is particularly useful for edge computing applications such as robotics, surveillance, and real-time streaming. It requires building both the library and a patched version of FFmpeg to fully enable hardware features. Overall, it extends FFmpeg functionality to better suit embedded GPU-powered environments. -
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Lucet
Lucet, the Sandboxing WebAssembly Compiler.
...Developed by the Bytecode Alliance, it focuses on ahead-of-time compilation, converting WebAssembly modules into native machine code before execution to achieve fast startup times and predictable performance. Lucet is particularly notable for its use in edge computing environments, where low latency and efficient resource usage are critical, such as in content delivery networks. It leverages the Cranelift code generator to produce optimized native binaries and provides a runtime that enforces strict sandboxing, ensuring that untrusted code cannot compromise the host system. The project is designed to embed easily into applications, allowing developers to extend systems with plugin-like architectures powered by WebAssembly. -
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PyCNN
Image Processing with Cellular Neural Networks in Python
Image Processing with Cellular Neural Networks in Python. Cellular Neural Networks (CNN) are a parallel computing paradigm that was first proposed in 1988. Cellular neural networks are similar to neural networks, with the difference that communication is allowed only between neighboring units. Image Processing is one of its applications. CNN processors were designed to perform image processing; specifically, the original application of CNN processors was to perform real-time ultra-high...
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