Search Results for "graphs" - Page 6
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Showing 1004 open source projects for "graphs"
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s-tui
Terminal-based CPU stress and monitoring utility
s-tui (Stress Terminal UI) is a terminal-based performance monitoring and stress-testing tool focused specifically on CPU behavior analysis in Linux and other UNIX-like systems. It provides real-time graphical visualization of CPU temperature, frequency, power consumption, and utilization directly within a text-based interface, eliminating the need for a graphical desktop environment. The utility is particularly useful for diagnosing thermal throttling, validating cooling solutions, and... -
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ANE Training
Training neural networks on Apple Neural Engine via APIs
...The repository implements a from-scratch transformer training pipeline capable of running both forward and backward passes on ANE hardware without relying on CoreML, Metal, or GPU acceleration. It explores the internal software stack of the Apple Neural Engine by interfacing with private classes such as _ANEClient and compiling custom compute graphs in the MIL format. The project includes performance benchmarks and kernel breakdowns that show how different components of the training loop are distributed between the ANE and CPU. It is primarily intended as a research and educational proof of concept rather than a production library, highlighting what is technically possible with undocumented hardware access. -
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Christmas Tree
Just a simple Christmas tree, based on reddit story
...Because tree structures are ubiquitous in computing—from file systems and organizational charts to DOM structures and evolutionary taxonomies—atree provides a reusable foundation for representing and interacting with nested data. It separates the logical model from rendering concerns, so you can use it as the data backbone in UI frameworks, graphs, or custom visual components. The library’s API makes it easy to add, remove, or move nodes anywhere in the hierarchy while maintaining consistent references and performance. -
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TensorRT Node for ComfyUI
Enables the best performance on NVIDIA RTX Graphics Cards
...It bridges the gap between ComfyUI’s flexible, node-based workflows and TensorRT’s highly optimized engine format. The result is that complex diffusion or image-processing graphs can be accelerated without the user having to rewrite the pipeline. The repo typically includes instructions for converting models to TensorRT engines and for wiring those engines into ComfyUI nodes. This is particularly attractive for power users who run many generations or who host ComfyUI on dedicated hardware and want to squeeze out every bit of GPU performance. ... -
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Wireit
Wireit upgrades your npm/pnpm/yarn scripts to make them smarter
Wireit is a productivity tool for npm scripts that adds smart caching, concurrency control, and dependency awareness without replacing your package manager. It wraps ordinary npm run commands with a declarative configuration describing inputs, outputs, and script relationships, then skips work when nothing has changed. Wireit can watch files, detect invalidated outputs, and propagate rebuilds through a graph of scripts, improving feedback loops in monorepos and complex apps. It persists... -
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JMH Gradle Plugin
Integrates the JMH benchmarking framework with Gradle
The JMH Gradle Plugin provides integration of the Java Microbenchmark Harness (JMH) into Gradle builds, enabling developers to write and run performance benchmarks directly in their projects. JMH is the de facto standard for writing accurate and reliable Java microbenchmarks, and this plugin automates tasks like generating benchmark sources, compiling them with the required JMH support classes, and packaging runnable benchmark jars. It simplifies the workflow by handling classpath setup and... -
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Optuna
A hyperparameter optimization framework
...Thanks to our define-by-run API, the code written with Optuna enjoys high modularity, and the user of Optuna can dynamically construct the search spaces for the hyperparameters. Optuna Dashboard is a real-time web dashboard for Optuna. You can check the optimization history, hyperparameter importances, etc. in graphs and tables. You don't need to create a Python script to call Optuna's visualization functions. Automated search for optimal hyperparameters using Python conditionals, loops, and syntax. Efficiently search large spaces and prune unpromising trials for faster results. Parallelize hyperparameter searches over multiple threads or processes without modifying code. -
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Django Rules
Awesome Django authorization, without the database
...At its core, it is a generic framework for building rule-based systems, similar to decision trees. It can also be used as a standalone library in other contexts and frameworks. Versatile. Decorate callables to build complex graphs of predicates. Predicates can be any type of callable -- simple functions, lambdas, methods, callable class objects, partial functions, decorated functions, anything really. A good Django citizen. Seamless integration with Django views, templates and the Admin for testing for object-level permissions. Efficient and smart. No need to mess around with a database to figure out whether John really wrote that book. ... -
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IndraDB
A graph database written in rust
A graph database written in rust. IndraDB consists of a server and an underlying library. Most users would use the server, which is available via releases as pre-compiled binaries. But if you're a rust developer that wants to embed a graph database directly in your application, you can use the library. IndraDB's original design is heavily inspired by TAO, facebook's graph datastore. In particular, IndraDB emphasizes simplicity of implementation and query semantics, and is similarly designed... -
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Charts.css
Open source CSS framework for data visualization
...No dependencies. 72kb file size. Less than 6kb gzipped file size! Visualization helps end-users understand data. Charts.css help frontend developers turn data into beautiful charts and graphs using simple CSS classes. The data is structured using semantic HTML tags and styled using CSS classes which change the visual representation displayed to the end-user. The framework offers developers flexibility. You choose what components to display and how to style them. Each component offers several CSS classes and CSS variables to customize your style. ... -
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Aden Hive
Outcome driven agent development framework that evolves
Hive is an open-source agent development framework that helps developers build autonomous, reliable, self-improving AI agents by letting them describe goals in ordinary natural language instead of hand-coding detailed workflows. Rather than manually defining execution graphs, Hive’s coding agent generates the agent graph, connection code, and test cases based on your high-level objectives, enabling outcome-driven agent creation that fits real business processes. Once deployed, agents can capture failure data, evolve automatically to meet their success criteria, and redeploy without constant manual intervention, delivering continual improvement over time. ... -
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OpenClaw Office
OpenClaw Office is the visual monitoring and management frontend
OpenClaw Office is a visual monitoring and management interface designed for the OpenClaw multi-agent system, providing an immersive and interactive way to observe and control autonomous AI agents. It presents agent activity through a virtual office environment, where each agent is represented as an animated entity within a 2D or 3D workspace. The platform enables real-time visualization of agent states, interactions, and workflows, making complex multi-agent coordination easier to... -
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AI Powered Knowledge Graph Generator
AI Powered Knowledge Graph Generator
AI-Powered Knowledge Graph is an open-source project focused on building knowledge graph systems that integrate artificial intelligence and machine learning to represent complex relationships between data entities. Knowledge graphs organize information as networks of nodes and relationships, allowing applications to analyze connections between concepts, datasets, or real-world entities. By incorporating AI techniques such as natural language processing and semantic reasoning, the project enables systems to automatically extract relationships and insights from large volumes of data. ... -
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Anomaly Detection Learning Resources
Anomaly detection related books, papers, videos, and toolboxes
Anomaly Detection Learning Resources is a curated open-source repository that collects educational materials, tools, and academic references related to anomaly detection and outlier analysis in data science. The project serves as a centralized index for researchers and practitioners who want to explore algorithms, datasets, and publications associated with detecting unusual patterns in data. The repository organizes resources into structured categories such as books, tutorials, academic... -
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grepai
Semantic Search & Call Graphs for AI Agents
grepai is a privacy-first, semantic code search CLI designed to replace traditional keyword-based search with meaning-aware queries, letting developers and code tools find relevant code by what it does rather than just text matches. It builds a semantic index of a project using vector embeddings, enabling natural language queries like “authentication logic” to return contextually relevant functions and modules even when naming differs dramatically, making code exploration far more intuitive.... -
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Scientific Visualization
An open access book on scientific visualization using python
The Scientific Visualization book is a freely available open-access textbook that introduces how to produce effective scientific visualizations using Python, focusing especially on leveraging the popular plotting library Matplotlib (and related tools). It goes beyond simple plotting tutorials and emphasizes design principles: how to choose colors, layout subplots, annotate graphs, and present data in a way that is both accurate and visually compelling. As such, it serves as a guide for researchers, data scientists, and academic authors who need to create publication-quality figures or explanatory graphics, rather than quick exploratory plots. It includes extensive examples that demonstrate best practices — for instance handling multiple subplots, combining line plots with scatter/density overlays, or rendering high-resolution vector graphics for print. -
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Penzai
A JAX research toolkit to build, edit, & visualize neural networks
Penzai, developed by Google DeepMind, is a JAX-based library for representing, visualizing, and manipulating neural network models as functional pytree data structures. It is designed to make machine learning research more interpretable and interactive, particularly for tasks like model surgery, ablation studies, architecture debugging, and interpretability research. Unlike conventional neural network libraries, Penzai exposes the full internal structure of models, enabling fine-grained... -
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Theseus
A library for differentiable nonlinear optimization
Theseus is a library for differentiable nonlinear optimization that lets you embed solvers like Gauss-Newton or Levenberg–Marquardt inside PyTorch models. Problems are expressed as factor graphs with variables on manifolds (e.g., SE(3), SO(3)), so classical robotics and vision tasks—bundle adjustment, pose graph optimization, hand–eye calibration—can be written succinctly and solved efficiently. Because solves are differentiable, you can backpropagate through optimization to learn cost weights, feature extractors, or initialization networks end-to-end. ... -
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frugally-deep
A lightweight header-only library for using Keras (TensorFlow) models
Use Keras models in C++ with ease. A lightweight header-only library for using Keras (TensorFlow) models in C++. Works out-of-the-box also when compiled into a 32-bit executable. (Of course, 64 bit is fine too.) Avoids temporarily allocating (potentially large chunks of) additional RAM during convolutions (by not materializing the im2col input matrix). Utterly ignores even the most powerful GPU in your system and uses only one CPU core per prediction. Quite fast on one CPU core, and you can... -
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jsoniter-scala
Scala macros for compile-time generation of safe and ultra-fast JSON
Scala macros for compile-time generation of safe and ultra-fast JSON codecs. This library had started from macros that reused jsoniter (json-iterator) for Java reader and writer but then the library evolved to have its own core of mechanics for parsing and serialization. The idea to generate codecs by Scala macros and main details was borrowed from Kryo Macros and adapted for the needs of the JSON domain. Validate parsed values safely with the fail-fast approach and clear reporting, provide... -
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guide-rpc-framework
A custom RPC framework implemented by Netty+Kyro+Zookeeper
...Since RPC remains a foundational building block in microservices, server architectures, and high-performance systems, this codebase helps you trace how requests are framed, routed, serialized, and executed across nodes. Because it integrates key pieces of the ecosystem (Netty event loops, Kyro object graphs, Zookeeper coordination), you also gain exposure to that stack. -
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fvcore
Collection of common code shared among different research projects
...Its common modules include timers, logging, checkpoints, registry patterns, and configuration helpers that reduce boilerplate in research code. A standout capability is FLOP and activation counting, which analyzes arbitrary PyTorch graphs to report cost by operator and by module for precise profiling. The file I/O layer (PathManager) abstracts local/remote storage so the same code can read from disks, cloud buckets, or HTTP endpoints. Because it is small, stable, and well-tested, fvcore is frequently imported by projects like Detectron2 and PyTorchVideo to avoid duplicating infrastructure and to keep research repos. -
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Likwid
Performance monitoring and benchmarking suite
Likwid is a simple to install and use toolsuite of command line applications and a library for performance oriented programmers. It works for Intel, AMD, ARMv8 and POWER9 processors on the Linux operating system. There is additional support for Nvidia and AMD GPUs. There is support for ARMv7 and POWER8/9 but there is currently no test machine in our hands to test them properly. -
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DeepFlow
Application Observability using eBPF
...Distributed tracing enters a new era, Zero Instrumentation. DeepFlow collects profiling data at a cost of below 1% with Zero Code, plots OnCPU/OffCPU function call stack flame graphs, and locates Full Stack performance bottleneck in the application. -
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PyTorch Geometric Temporal
Spatiotemporal Signal Processing with Neural Machine Learning Models
The library consists of various dynamic and temporal geometric deep learning, embedding, and Spatio-temporal regression methods from a variety of published research papers. Moreover, it comes with an easy-to-use dataset loader, train-test splitter and temporal snaphot iterator for dynamic and temporal graphs. The framework naturally provides GPU support. It also comes with a number of benchmark datasets from the epidemiological forecasting, sharing economy, energy production and web traffic management domains. Finally, you can also create your own datasets. The package interfaces well with Pytorch Lightning which allows training on CPUs, single and multiple GPUs out-of-the-box. ...
