Search Results for "parallel" - Page 3
Sort By:
Showing 1791 open source projects for "parallel"
View related business solutions-
$300 Free Credits to Build on Google CloudStart your next project with $300 in free Google Cloud credit. Spin up VMs, run containers, query petabytes in BigQuery, or build agents with Gemini Enterprise Agent Platform. Once your credits are used, keep building with 20+ always-free tier products including Compute Engine, Cloud Storage, GKE, and Cloud Run functions. No commitment required—just sign up and start building.
-
Save Up to 91% on Cloud Compute With Spot VMsRun batch jobs at 60-91% off with Spot VMs. Long-running workloads get automatic discounts with sustained use.
-
1
vLLM
A high-throughput and memory-efficient inference and serving engine
vLLM is a fast and easy-to-use library for LLM inference and serving. High-throughput serving with various decoding algorithms, including parallel sampling, beam search, and more. -
2
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. -
3
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. -
4
OpenCL.jl
OpenCL Julia bindings
Julia interface for the OpenCL parallel computation API. This package aims to be a complete solution for OpenCL programming in Julia, similar in scope to PyOpenCL for Python. It provides a high level API for OpenCL to make programing hardware accelerators, such as GPUs, FPGAs, and DSPs, as well as multicore CPUs much less onerous. -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
-
5
Eigent
The Open Source Cowork Desktop to Unlock Your Exceptional Productivity
Eigent is an open-source cowork desktop application designed to help you build, manage, and deploy a custom AI workforce. It enables multiple specialized AI agents to collaborate in parallel, turning complex workflows into automated, end-to-end tasks. Built on the CAMEL-AI multi-agent framework, Eigent emphasizes productivity, flexibility, and transparent system design. You can run Eigent fully locally for maximum privacy and data control, or choose a cloud-connected experience for quick access. The platform supports a wide range of AI models and integrates powerful tools through the Model Context Protocol (MCP). ... -
6
Open SWE
Open source async coding agent that plans, codes, and opens PRs
...Built with LangGraph, it can understand a codebase, generate a structured plan, and execute code changes from start to finish without constant human intervention. It operates in a cloud-based environment where tasks are processed asynchronously, allowing multiple coding jobs to run in parallel in isolated sandboxes. It integrates directly with development workflows by responding to triggers from tools like GitHub, enabling users to initiate tasks through issues or comments. Open SWE is capable of creating commits and automatically opening pull requests once implementation is complete, effectively closing the loop on development tasks. ... -
7
BigMac
An open-source toolkit for BigMac-style pipeline-parallel training
BigMac is an open-source toolkit for pipeline-parallel training of multimodal large language models. It preserves optimized language-model pipeline schedules while placing encoder and generator work around them. This design reduces activation memory without bringing back cross-module pipeline bubbles. Its scheduler creates global operator plans, while its executor runs those plans through a shared schedule abstraction. -
8
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. -
9
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. ... -
Your monitoring isn't a stack. It's a pile. Fix that.Replace Datadog, New Relic, and Sentry without adding three more dashboards.
-
10
CUDA Python
Performance meets Productivity
...The project is designed to simplify GPU programming by offering Pythonic abstractions while still exposing the full power of CUDA for advanced users. It integrates tightly with the broader Python GPU ecosystem, including Numba for kernel compilation and CCCL for parallel primitives, allowing developers to write performant code without leaving Python. The toolkit also includes utilities for profiling, memory management, distributed computing, and numerical operations, making it suitable for scientific computing, AI, and data processing workloads. -
11
Kreuzberg
Polyglot document intelligence framework
Kreuzberg is a flexible task orchestration and agent workflow platform designed to help developers build, coordinate, and scale intelligent agents or automation pipelines that interact with external services, runtime environments, and multi-step business workflows. It emphasizes modular design so that developers can define discrete tasks or “actions” and then compose them into complex flows where dependencies, parallel steps, and error handling are declaratively managed. This structure makes it simpler to build resilient automation pipelines that span multiple technologies or APIs without needing to glue everything together manually. The platform also supports observability and monitoring, helping teams trace the progression of workflows, catch errors early, and evaluate performance trends in orchestrated systems. -
12
PRDownloader
A file downloader library for Android with pause and resume support
...PRDownloader gives callbacks for everything like onProgress, onCancel, onStart, onError and etc while downloading a file. Supports proper request canceling. Many requests can be made in parallel. All types of customization are possible. -
13
Horust
Horust is a supervisor / init system written in rust
...Unlike traditional init systems, Horust focuses on stateless configuration using TOML files and aims to bring predictability and ease of use to system boot and service management. Written with Rust’s safety guarantees, Horust provides features like dependency handling, parallel service startup, and logging, making it suitable for containers, embedded systems, or minimal Linux environments where systemd is too complex or heavy. -
14
JavaCV
Java interface to OpenCV, FFmpeg, and more
JavaCV uses wrappers from the JavaCPP Presets of commonly used libraries by researchers in the field of computer vision (OpenCV, FFmpeg, libdc1394, FlyCapture, Spinnaker, OpenKinect, librealsense, CL PS3 Eye Driver, videoInput, ARToolKitPlus, flandmark, Leptonica, and Tesseract) and provides utility classes to make their functionality easier to use on the Java platform, including Android. JavaCV also comes with hardware accelerated full-screen image display (CanvasFrame and GLCanvasFrame), easy-to-use methods to execute code in parallel on multiple cores (Parallel), user-friendly geometric and color calibration of cameras and projectors (GeometricCalibrator, ProCamGeometricCalibrator, ProCamColorCalibrator), detection and matching of feature points (ObjectFinder), a set of classes that implement direct image alignment of projector-camera systems (mainly GNImageAligner, ProjectiveTransformer, ProjectiveColorTransformer, ProCamTransformer, and ReflectanceInitializer), and more. -
15
GitButler
The GitButler version control client, backed by Git
...The project is designed around developer productivity, emphasizing smoother workflows for handling multiple streams of work, reviewing changes, and recovering from mistakes without the usual friction. It also positions itself for AI-assisted development patterns, where tooling needs to support rapid iteration and parallel work while staying understandable and reversible. By offering both GUI and CLI surfaces, it can fit into different team preferences, from visual-first change review to scriptable automation. -
16
pyinfra
pyinfra turns Python code into shell commands
...Designed as an alternative to tools like Ansible, pyinfra prioritizes speed, scalability, and developer flexibility while maintaining a declarative operational model. It supports ad-hoc command execution, reusable operations, inventory management, and parallel deployments across thousands of hosts. The framework integrates naturally with existing DevOps ecosystems and allows users to create highly customizable deployment logic using native Python syntax. Its architecture combines infrastructure-as-code concepts with efficient remote execution, making it suitable for modern cloud and server automation workflows. -
17
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. -
18
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. -
19
Vibe Kanban
Get 10X more out of Claude Code, Codex or any coding agent
...Vibe Kanban tackles this by enabling users to define tasks as cards on a board, assign those tasks to one or more coding agents, and then track progress and outcomes as each agent executes in the background with its own isolated workspace. It supports running multiple agents in parallel or in sequence, giving engineers the freedom to plan, review, and address higher-level concerns while AI helpers execute individual pieces of work. -
20
Brakeman
A static analysis security vulnerability scanner for Ruby on Rails app
Brakeman is a free vulnerability scanner specifically designed for Ruby on Rails applications. It statically analyzes Rails application code to find security issues at any stage of development. Brakeman now uses the parallel gem to read and parse files in parallel. By default, parallel will split the reading/parsing into a number of separate processes based on number of CPUs. In testing, this has dramatically improved speed for large code bases, around 35% reduction in overall scan time. Brakeman will now track and return very simple literal values (e.g. strings, hashes of literals, arrays of literals) from very simple class methods (e.g. single line). ... -
21
fd
A simple, fast and user-friendly alternative to 'find'
...Instead of just showing the search results, you often want to do something with them. fd provides two ways to execute external commands for each of your search results: the -x/--exec option runs an external command for each of the search results (in parallel), or the -X/--exec-batch option launches the external command once, with all search results as arguments. -
22
Make It heavy
A Python framework that emulates Grok Heavy functionality
Make It heavy is a Python framework for producing deeper AI analysis through multi-agent orchestration. It is designed to emulate the style of Grok Heavy by splitting a user query into several specialized research angles. The system runs four agents in parallel so each one can explore the problem from a different perspective. It then combines their outputs into one unified answer through an intelligent synthesis step. The framework uses OpenRouter for model access and can also run in single-agent mode for simpler tasks. Overall, it is useful for users who want broader research coverage, richer reasoning diversity, and structured multi-agent responses from one command-line workflow. -
23
OpenWorkflow
Open-source TypeScript framework for building durable workflows
...The framework supports long-running processes that can sleep for seconds or months, making it suitable for background jobs, automation pipelines, and event-driven systems. OpenWorkflow includes automatic retries with exponential backoff, parallel step execution, and scheduling capabilities, all while using the developer’s existing database instead of requiring dedicated orchestration infrastructure. A built-in dashboard provides visibility into workflow execution and debugging. Overall, it delivers production-ready workflow durability similar to temporal-style systems but with a simpler operational footprint. -
24
Claude Octopus
Put up to 8 AI models on every coding task
Claude Octopus is a multi-model orchestration plugin that enables developers to run multiple AI models simultaneously on a single coding task to reduce blind spots and improve output quality. It allows up to eight different models to analyze the same problem in parallel, surfacing diverse perspectives before finalizing results. The system is particularly useful for detecting inconsistencies, edge cases, and errors that a single model might miss. It integrates directly into coding workflows, making it easy to compare outputs without leaving the development environment. The plugin supports multiple providers and model types, enabling flexible combinations of local and cloud-based models. ... -
25
Loki Mode
Multi-agent autonomous startup system for Claude Code
...It orchestrates dozens of agent types across swarms that handle designated roles — such as architecture, coding, QA, deployment, and business workflows — running in parallel to cover both engineering and operational tasks without continuous human intervention. By supporting multiple AI providers (like Claude Code, OpenAI Codex CLI, and Google Gemini CLI), loki-mode dynamically selects and spawns only the needed agents for a given project, optimizing computational resources and task throughput. Its Reason-Act-Reflect-Verify (RARV) cycle with self-verification loops emphasizes quality and resilience, automating end-to-end development lifecycles.
