Search Results for "algorithms" - Page 2
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995 projects for "algorithms" with 2 filters applied:
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Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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Go From AI Idea to AI App FastAccess Gemini 3 and 200+ models. Build chatbots, agents, or custom models with built-in monitoring and scaling.
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mold
A Modern Linker
...In compiled languages like C, C++, and Rust, the linking phase can become a significant bottleneck, especially in large codebases, and mold addresses this by leveraging highly optimized algorithms and extensive parallelism. It is capable of utilizing all available CPU cores efficiently, resulting in significantly faster linking compared to other popular linkers such as GNU ld, gold, and LLVM lld. The tool is designed to integrate seamlessly into existing build systems, requiring minimal configuration changes to adopt. Mold supports a wide range of architectures, including x86-64, ARM, RISC-V, and PowerPC, making it suitable for diverse development environments. -
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X For You Feed Algorithm
Algorithm powering the For You feed on X
X For You Feed Algorithm is the open-sourced core recommendation system that powers the For You feed on X (the social network formerly known as Twitter), and it represents one of the first times a major social platform has published production-level ranking code for public review and experimentation. The repository contains the full pipeline that ingests user engagement and content candidate data, processes it through retrieval, hydration, filtering, scoring, and selection layers, and... -
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huihut interview
A summary of C/C++ technical interview basics
interview is a curated repository of technical interview questions, solutions, and explanations covering a wide range of topics in computer science and software engineering. It aims to help developers prepare for job interviews by providing sample problems in algorithms, data structures, system design, databases, and programming language intricacies, often with code snippets and discussion. The repo is designed so learners can practice real interview scenarios, compare approaches, and internalize foundational concepts that are frequently tested by tech companies. Many entries include both the problem statement and one or more reference implementations, offering insights into time/space complexity and tradeoffs between competing strategies. ... -
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Anomalib
An anomaly detection library comprising state-of-the-art algorithms
Anomalib is an open-source deep learning library focused on anomaly detection and localization tasks, collecting state-of-the-art algorithms and tools under one modular framework. It provides implementations of leading anomaly detection methods drawn from current research, as well as a full set of utilities for training, evaluating, benchmarking, and deploying these models on both public and private datasets. Anomalib emphasizes flexibility and reproducibility: you can use its simple APIs to plug in custom models, track experiments, tune hyperparameters, and generate visualizations that highlight anomalous regions. ... -
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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DualPipe
A bidirectional pipeline parallelism algorithm
DualPipe is a bidirectional pipeline parallelism algorithm open-sourced by DeepSeek, introduced in their DeepSeek-V3 technical framework. The main goal of DualPipe is to maximize overlap between computation and communication phases during distributed training, thus reducing idle GPU time (i.e. “pipeline bubbles”) and improving cluster efficiency. Traditional pipeline parallelism methods (e.g. 1F1B or staggered pipelining) leave gaps because forward and backward phases can’t fully overlap... -
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MLJ
A Julia machine learning framework
MLJ (Machine Learning in Julia) is a toolbox written in Julia providing a common interface and meta-algorithms for selecting, tuning, evaluating, composing and comparing about 200 machine learning models written in Julia and other languages. The functionality of MLJ is distributed over several repositories illustrated in the dependency chart below. These repositories live at the JuliaAI umbrella organization. -
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CDT
Constrained Delaunay Triangulation (C++)
CDT is a C++ library for generating constraints or conforming Delaunay triangulations. -
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QPanda 2
QPanda 2 is an open source quantum computing framework
QPanda2 is an open source quantum computing framework developed by Origin Quantum, which can be used to build, run and optimize quantum algorithms. QPanda2 is the basic library of a series of software developed by Origin Quantum, which provides core components for QRunes, Qurator and quantum computing services. -
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Easy3D
Efficient library for processing 3D data
Easy3D is a lightweight, easy-to-use, and efficient library for processing and rendering 3D data, implemented in C++ with Python bindings. It is designed for tasks such as 3D modeling, geometry processing, and rendering, emphasizing simplicity and efficiency. Easy3D serves as a valuable tool for research, education, and the development of sophisticated 3D applications, providing a solid foundation for handling 3D data. -
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Apollo-11
Original Apollo 11 Guidance Computer (AGC) source code
...It is written in AGC assembly and reflects 1960s software engineering practices, complete with comments from the original programmers. The code is both a cultural artifact and a technical reference, illustrating how limited memory and processor constraints shaped algorithms and system design. Developers can examine navigation routines, guidance logic, and task scheduling in an environment with no luxury features—everything is explicit and resource-aware. The repository’s structure and documentation make it approachable for modern readers despite the archaic environment. It’s frequently used in education, talks, and explorations of software history to show how a landmark mission depended on disciplined code and verification. -
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Node Argon2
Node.js bindings for Argon2 hashing algorithm
A Node.js library for hashing passwords securely using the Argon2 key derivation function, a modern cryptographic algorithm. -
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libplacebo
Official mirror of libplacebo
libplacebo is a flexible, high-performance graphics library built on top of Vulkan, designed to provide reusable GPU-accelerated components for media applications. It originated as a core part of the rendering pipeline for the mpv media player and has since grown into a standalone library used for tone mapping, dithering, color space conversion, and more. libplacebo is ideal for developers looking to integrate sophisticated video rendering and post-processing into their own applications with... -
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Maelstrom
A workbench for writing toy implementations of distributed systems
Maelstrom is a distributed-systems workbench by the Jepsen team. It provides standardized JSON-based protocols and test harnesses (via Jepsen) to validate the behavior of custom toy systems—like commutative sets or transactional key-value stores—under simulated failure conditions. You implement your server in any language, connect through stdin/stdout, and the framework injects network disruptions, partitions, and consistency checks. -
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XZ Utils
Open-source compression utility and library
xz is a widely used open-source compression utility and library that implements the high-ratio LZMA and LZMA2 compression algorithms. It provides both command-line tools and a reusable C library, enabling developers and system administrators to compress and decompress files efficiently across many environments. The project is known for delivering strong compression performance while maintaining reasonable memory usage, making it suitable for software distribution, backups, and archival workflows. xz is commonly included in Unix-like operating systems and is often used as a standard packaging format in Linux ecosystems. ... -
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xqvm-py
A python implementation of the Quip Network's quantum virtual machine
...It integrates into the broader Quip ecosystem, allowing interoperability with other components such as blockchain nodes and management tools. Python’s dynamic nature makes it suitable for testing new algorithms, educational purposes, and exploratory research. The implementation likely sacrifices some performance compared to Rust but gains significant flexibility and ease of iteration. -
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The Agda standard library
The Agda standard library
The standard library aims to contain all the tools needed to write both programs and proofs easily. While we always try and write efficient code, we prioritize ease of proof over type-checking and normalization performance. If computational performance is important to you, then perhaps try agda-prelude instead. Agda is a dependently typed programming language. It is an extension of Martin-Löf’s type theory and is the latest in the tradition of languages developed in the programming logic... -
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DynamicalSystems.jl
Award winning software library for nonlinear dynamics timeseries
...To learn how to use it and see its contents visit the documentation, which you can either find online or build locally by running the docs/make.jl file. DynamicalSystems.jl is part of JuliaDynamics, an organization dedicated to creating high-quality scientific software. All implemented algorithms provide a high-level scientific description of their functionality in their documentation string as well as references to scientific papers. The documentation features hundreds of tutorials and examples ranging from introductory to expert usage. -
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Substrate Node Template
A rust implementation of the Quip Protocol forked from Substrate
...It also includes tools for running single-node or multi-node networks, enabling developers to simulate distributed consensus systems locally. The architecture is designed for extensibility, allowing custom consensus algorithms, storage models, and transaction logic to be integrated. -
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GeoStats.jl
An extensible framework for geospatial data science
GeoStats.jl is a Julia framework for geospatial data science and geostatistical modeling. It’s fully implemented in Julia and designed to provide an extensible, high-performance stack that handles spatial domains, interpolation, simulation, learning, and visualization. The package is modular: it breaks out geometry, spatial domains, transforms, variograms, covariance models, and modeling into subpackages (e.g., GeoStatsBase, GeoStatsModels, GeoStatsTransforms). Users can represent... -
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Catlab.jl
A framework for applied category theory in the Julia language
...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 applied category theory. Macros offer a convenient syntax for specifying categorical doctrines and type-safe symbolic manipulation systems. Wiring diagrams (aka string diagrams) are supported through specialized data structures and can be serialized to and from GraphML (an XML-based format) and JSON. -
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Aglais XQVM
A rust implementation of the Quip Network's quantum virtual machine
Aglais XQVM is a Rust implementation of the Quip Network’s quantum virtual machine, designed to simulate or execute quantum-inspired computation within a blockchain or distributed system context. The project focuses on providing a performant and low-level execution environment that can handle specialized computational workloads associated with quantum algorithms or hybrid systems. Built in Rust, it emphasizes memory safety, performance, and deterministic execution, which are critical for distributed environments. It integrates with the broader Quip ecosystem, allowing it to function as part of a larger protocol stack that includes blockchain infrastructure and node management tools. The virtual machine abstraction enables developers to define and execute computational logic in a controlled environment, potentially bridging classical and quantum paradigms. ... -
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Kintsugi
A tool to automatically resolve Git conflicts
Kintsugi is an innovative open-source project from Lightricks focused on robust perceptual image quality and enhancement, bringing together advanced algorithms for denoising, super-resolution, tone mapping, and stylistic refinement into a cohesive framework. Named after the Japanese art of repair and beauty, Kintsugi embraces imperfect captures and enhances them intelligently, preserving natural detail while reducing noise and artifacts in ways that align with human visual preferences. ... -
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Optuna
A hyperparameter optimization framework
Optuna is an automatic hyperparameter optimization software framework, particularly designed for machine learning. It features an imperative, define-by-run style user API. 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... -
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Best-websites-a-programmer-should-visit
Some useful websites for programmers
Best-websites-a-programmer-should-visit is a living, community-curated directory of links that programmers consistently find useful throughout their careers. Rather than being a random bookmark dump, it organizes resources into practical categories such as algorithms, competitive programming, reading materials, podcasts, newsletters, interview prep, design, security, performance, and more. The list aims to reduce the “what should I learn next?” friction by pointing you to high-signal, time-tested tutorials, references, and tools. Because it spans beginner to advanced topics, you can use it as an on-ramp when starting out and as a roadmap for deeper specialization later. ... -
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type-challenges
Collection of TypeScript type challenges with online judge
type-challenges is a massive set of TypeScript type-level puzzles that turn the compiler into a playground for metaprogramming. Each challenge is a miniature kata where you implement types that transform other types—parsing strings, inferring tuples, mapping unions—without writing any runtime code. Problems are arranged from warm-ups to brain-twisters, letting developers build intuition about distributive conditional types, inference in extends, variance, and other corner cases of the type...
