Search Results for "parallel" - Page 2
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Showing 1479 open source projects for "parallel"
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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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nbmake
Pytest plugin for testing notebooks
Pytest plugin for testing and releasing notebook documentation. To raise the quality of scientific material through better automation. Research/Machine Learning Software Engineers who maintain packages/teaching materials with documentation written in notebooks. -
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pgBadger
A fast PostgreSQL Log Analyzer
...It parses PostgreSQL logs and generates detailed, visually appealing HTML reports, helping DBAs and developers understand query performance, connection issues, and system bottlenecks. With support for incremental analysis, gzip-compressed logs, and parallel processing, pgBadger is ideal for monitoring and optimizing PostgreSQL database activity in production environments. -
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Sogou C++ Workflow
C++ parallel computing and asynchronous networking engine
As Sogou`s C++ server engine, Sogou C++ Workflow supports almost all back-end C++ online services of Sogou, including all search services, cloud input method, online advertisements, etc., handling more than 10 billion requests every day. This is an enterprise-level programming engine in light and elegant design which can satisfy most C++ back-end development requirements. -
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LAMMPS
Public development project of the LAMMPS MD software package
...LAMMPS is script-driven, so users can define simulation geometry, force fields, integration methods, output, and analysis behavior through input files. Its main value is combining broad scientific flexibility with scalable parallel performance for complex molecular and mesoscale simulations. -
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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Colly
Elegant Scraper and Crawler Framework for Golang
...With Colly you can easily extract structured data from websites, which can be used for a wide range of applications, like data mining, data processing or archiving. Clean API. Fast (>1k request/sec on a single core) Manages request delays and maximum concurrency per domain. Automatic cookie and session handling. Sync/async/parallel scraping. Distributed scraping. Caching, automatic encoding of non-unicode responses. Robots.txt support. Google App Engine support. -
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Crawl4AI
Open-source LLM Friendly Web Crawler & Scraper
Crawl4AI is a high-performance, AI‑ready web crawler tailored for LLM data ingestion and RAG pipelines. It supports adaptive crawling heuristics (stopping when enough info is gathered), structured markdown output, and high-speed parallel execution. Designed to operate at scale with optional Docker deployment and framework integrations. -
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CubeSandbox
Instant, Concurrent, Secure & Lightweight Sandbox for AI Agents
...Built in Rust, it focuses on enabling concurrent execution while maintaining strong isolation and low overhead. The system is optimized for scenarios where multiple AI agents need to execute tasks in parallel without compromising system integrity. It provides fast startup times and efficient resource management, making it suitable for large-scale agent orchestration. CubeSandbox integrates well with cloud-native workflows and modern infrastructure pipelines. Its design prioritizes security, concurrency, and performance in AI-driven environments. ... -
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Async PHP
Easily run code asynchronously
Spatie Async is a PHP library that allows developers to run parallel processes using asynchronous tasks. It helps optimize performance by executing long-running or resource-intensive tasks concurrently, instead of sequentially. The library is easy to use and integrates well with existing PHP applications, making it suitable for batch processing, data scraping, or any scenario where concurrency can boost efficiency. -
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Agent Orchestrator
Agentic orchestrator for parallel coding agents
Agent Orchestrator from Composio is an open-source orchestration layer designed to manage fleets of parallel AI coding agents working on a shared codebase. It enables each agent to operate independently in isolated git worktrees, handling tasks like fixing CI failures, addressing code review comments, and creating pull requests. The platform automates the coordination of multiple agents, reducing the need for manual oversight in complex development workflows. -
Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
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Soufflé
Datalog variant for tool designers crafting analyses in Horn clauses
Rapid prototyping for your analysis problems with logic; enabling deep design-space explorations; designed for large-scale static analysis; e.g., points-to analysis for Java, taint-analysis, and security checks. Futamura projections/partial evaluation for effective translation to parallel C++; optimized staged compilation; specialized data-structures for logical relations. Efficient translation to parallel C++ of Datalog programs (CAV'16, CC'16) Efficient interpretation using de-specialization techniques (PLDI'21) Specialized data structure for relations (PACT'19, PPoPP'19, PMAM'19) with optimal index selection (VLDB'18) Extended semantics of Datalog, e.g., permitting unbounded recursions with numbers and terms. ... -
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LobeHub
Workspace to find, build, and collaborate with AI agents
...LobeHub brings multiple models, tools, and modalities into a single unified environment under the user’s control. With built-in collaboration features, agents can work in parallel, share context, and support complex projects seamlessly. The platform is built around the idea of co-evolution, where both humans and agents continuously learn and improve together. -
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Bevy
A refreshingly simple data-driven game engine built in Rust
A refreshingly simple data-driven game engine built in Rust. All engine and game logic uses Bevy ECS, a custom Entity Component System. Massively Parallel and Cache-Friendly. The fastest ECS according to some benchmarks. Components are Rust structs, Systems are Rust functions. Queries, Global Resources, Local Resources, Change Detection, Lock-Free Parallel Scheduler. Bevy is still in the very early stages of development. APIs can and will change (now is the time to make suggestions!). ... -
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forkd
Fork() for AI agent microVMs
...Instead of cold-booting a separate virtual machine for every worker, it forks children from a warmed parent snapshot and uses copy-on-write behavior to share the initial memory state. This makes it useful for spawning many isolated agent environments quickly during parallel research, testing, or code execution. The project is focused on runtime performance, sandbox isolation, and efficient branching from a live or prepared VM state. It is especially relevant for developers building agent infrastructure where many short-lived execution branches need to run safely. forkd is best understood as a low-level systems tool for scalable, isolated AI-agent workloads. -
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future
R package: future: Unified Parallel and Distributed Processing in R
The future package in R provides a unified abstraction for asynchronous and/or parallel computation. It allows R expressions to be scheduled for future evaluation, with the result retrieved later, in a way decoupled from the specific backend used. This lets code be written in a way that works with sequential execution, multicore, multisession, cluster, or remote compute backends, without changing the high-level code. -
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PlatEMO
Evolutionary multi-objective optimization platform
...Users can select various figures to be displayed, including the Pareto front of the result, the Pareto set of the result, the true Pareto front, and the evolutionary trajectories of any performance indicator values. PlatEMO provides a powerful and friendly GUI, where users can configure all the settings and perform experiments in parallel via the GUI without writing any code. -
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Zoo Code
Zoo Code gives you a whole dev team of AI agents in your code editor
...It can generate, refactor, debug, document, and explain code while working with the surrounding codebase. Dedicated Code, Architect, Ask, Debug, and Custom modes adapt the assistant to different tasks. Its orchestrator can delegate work, coordinate parallel subtasks, and recover parent or child tasks. Semantic code search helps agents locate relevant code without a separate indexing workflow. The project also supports many model providers, MCP servers, workspace rules, file-access controls, and safeguards against destructive commands. -
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Binaryen
Compiler infrastructure and toolchain library for WebAssembly
...It accepts input in WebAssembly-like form but also accepts a general control flow graph for compilers that prefer that. Binaryen's internal IR uses compact data structures and is designed for completely parallel codegen and optimization, using all available CPU cores. Binaryen's IR also compiles down to WebAssembly extremely easily and quickly because it is essentially a subset of WebAssembly. Binaryen's optimizer has many passes (see an overview later down) that can improve code size and speed. These optimizations aim to make Binaryen powerful enough to be used as a compiler backend by itself. -
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Oh My codeX (OMX)
Your codex is not alone. Add hooks, agent teams, HUDs
...It addresses limitations in the base Codex environment, such as the lack of hooks, agent coordination, and persistent execution, by layering a shell-based system that enables richer interaction patterns. The project transforms a single AI coding assistant into a coordinated system of specialized agents that can collaborate in parallel, improving both speed and reliability of development tasks. It leverages tools like tmux to manage multiple agent sessions simultaneously, enabling a “team mode” where different agents handle distinct responsibilities within a shared workflow. The system also introduces staged pipelines, allowing tasks to move through phases such as planning, execution, verification, and refinement in a structured manner. -
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conflux-rust
The official Rust implementation of Conflux protocol
conflux-rust is the Rust implementation of Conflux, a high-performance Layer 1 blockchain designed to deliver high throughput without compromising decentralization or security. Conflux introduces a Tree-Graph consensus mechanism that allows parallel block processing while maintaining consensus integrity. This implementation focuses on performance and is compatible with the Ethereum Virtual Machine (EVM), enabling developers to deploy smart contracts written for Ethereum. It provides a robust foundation for dApps, DeFi, and Web3 applications in regions requiring regulatory compliance and scalability. -
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Numaflow
Kubernetes-native platform to run massively parallel data/streaming
Numaflow is a Kubernetes-native tool for running massively parallel stream processing. A Numaflow Pipeline is implemented as a Kubernetes custom resource and consists of one or more source, data processing, and sink vertices. Numaflow installs in a few minutes and is easier and cheaper to use for simple data processing applications than a full-featured stream processing platform. -
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Servo
Embed web technologies in applications
Servo is an experimental, highly parallel, and embeddable browser rendering engine written in Rust. It leverages Rust’s memory-safety and concurrency strengths, supports modern GPU-powered rendering (WebGL/WebGPU), and serves as a research-forward alternative to traditional browser engines. Servo is a prototype web browser engine written in the Rust language. It is currently developed on 64-bit macOS, 64-bit Linux, 64-bit Windows, 64-bit OpenHarmony, and Android. -
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Claude Ads
Comprehensive paid advertising audit & optimization skill
...The system generates structured reports, identifies inefficiencies, and suggests optimization strategies based on industry benchmarks. It supports platforms like Google Ads, Meta Ads, TikTok, LinkedIn, and more, offering a unified analysis workflow. The architecture uses parallel subagents to speed up audits and includes financial modeling and A/B testing guidance. It runs locally, ensuring privacy and control over sensitive advertising data. The project is aimed at replacing manual audit workflows with fast, automated, and repeatable analysis. -
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ChainForge
An open-source visual programming environment
...Instead of relying on isolated prompt experimentation, it introduces a dataflow-based interface that allows users to create complex prompt pipelines and evaluate them across different models, parameters, and datasets simultaneously. The platform enables rapid experimentation by generating permutations of prompts and inputs, making it possible to test hundreds of variations in parallel and analyze performance trends more effectively. It also includes evaluation nodes that allow developers to define scoring functions, enabling automated benchmarking of outputs based on custom criteria such as accuracy, formatting, or relevance. -
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mosaicml composer
Supercharge Your Model Training
...The framework is intended for modern workloads that may span anything from a single GPU to very large distributed training environments, which makes it suitable for both experimentation and production-scale development. It includes built-in support for distributed training strategies such as Fully Sharded Data Parallelism and standard Distributed Data Parallel execution, helping teams scale models without having to assemble as much infrastructure by hand. -
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HunyuanVideo-I2V
A Customizable Image-to-Video Model based on HunyuanVideo
...It extends video generation so that given a static reference image plus an optional prompt, it generates a video sequence that preserves the reference image’s identity (especially in the first frame) and allows stylized effects via LoRA adapters. The repository includes pretrained weights, inference and sampling scripts, training code for LoRA effects, and support for parallel inference via xDiT. Resolution, video length, stability mode, flow shift, seed, CPU offload etc. Parallel inference support using xDiT for multi-GPU speedups. LoRA training / fine-tuning support to add special effects or customize generation.
