Search Results for "parallel"
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628 projects for "parallel" with 1 filter applied:
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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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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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parallel-ssh
Asynchronous parallel SSH client library.
parallel-ssh is an asynchronous parallel SSH library designed for large-scale automation. It differentiates itself from alternatives, other libraries and higher-level frameworks like Ansible or Chef in several ways. -
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EnvPool
C++-based high-performance parallel environment execution engine
EnvPool is a fast, asynchronous, and parallel RL environment library designed for scaling reinforcement learning experiments. Developed by SAIL at Singapore, it leverages C++ backend and Python frontend for extremely high-speed environment interaction, supporting thousands of environments running in parallel on a single machine. It's compatible with Gymnasium API and RLlib, making it suitable for scalable training pipelines. -
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Piscina
A fast, efficient Node.js Worker Thread Pool implementation
Piscina is a fast, efficient Node.js worker thread pool implementation, designed to perform heavy CPU-bound tasks in parallel, thereby improving application performance. -
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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. -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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MiroFish
A Simple and Universal Swarm Intelligence Engine
MiroFish is a next-generation artificial intelligence prediction engine that leverages multi-agent technology and swarm-intelligence simulation to model, simulate, and forecast complex real-world scenarios. The system extracts “seed” information from sources such as breaking news, policy documents, and market signals to construct a high-fidelity digital parallel world populated by thousands of virtual agents with independent memory and behavior rules. Users can inject variables or conditions into this simulated environment from a “god’s eye view,” enabling iterative prediction of future trends under different assumptions, which can be useful for decision support, scenario planning, or creative exploration. ... -
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Parallel executor
paexec distributes tasks over network or CPUs.
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multi-agent-shogun
Samurai-inspired multi-agent system for Claude Code
multi-agent-shogun is a multi-agent orchestration system designed to coordinate multiple AI coding agents working in parallel. Inspired by the hierarchy of a feudal Japanese military structure, the system organizes agents into roles such as Shogun, Karo, and Ashigaru, which correspond to strategist, coordinator, and worker agents. A user interacts primarily with the Shogun agent by issuing natural language instructions that describe the desired tasks. -
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Brax
Massively parallel rigidbody physics simulation
Brax is a fast and fully differentiable physics engine for large-scale rigid body simulations, built on JAX. It is designed for research in reinforcement learning and robotics, enabling efficient simulations and gradient-based optimization. -
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HYPRE
Parallel solvers for sparse linear systems featuring multigrid methods
Livermore’s HYPRE library of linear solvers makes possible larger, more detailed simulations by solving problems faster than traditional methods at large scales. It offers a comprehensive suite of scalable solvers for large-scale scientific simulation, featuring parallel multigrid methods for both structured and unstructured grid problems. The HYPRE library is highly portable and supports a number of languages. Work on HYPRE began in the late 1990s. It has since been used by research institutions and private companies to simulate groundwater flow, magnetic fusion energy plasmas in tokamaks and stellarators, blood flow through the heart, fluid flow in steam generators for nuclear power plants, and pumping activity in oil reservoirs, to name just a few areas. ... -
Gemini 3 and 200+ AI Models on One PlatformBuild generative AI apps with Vertex AI. Switch between models without switching platforms.
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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. -
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LLMCompiler
An LLM Compiler for Parallel Function Calling
...LLMCompiler addresses this limitation by applying principles from classical compilers to analyze a task and construct an execution plan that allows multiple functions to run in parallel whenever possible. The framework builds a dependency graph of required operations, identifying which tasks must run sequentially and which can be executed simultaneously. Its architecture includes components such as a planning module that constructs the task graph, a task dispatcher that manages dependencies, and an executor that performs parallel calls. -
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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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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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CodeMachine
CLI tool for multi-agent workflows and automated code generation
...It enables developers to transform high-level specifications into production-ready code by managing planning, architecture, implementation, testing, and validation within a unified environment. CodeMachine CLI supports parallel execution through multiple specialized agents, allowing faster development cycles and scalable automation. Built for flexibility, it can handle anything from simple scripts to complex, long-running workflows that span hours or days. CodeMachine also integrates with various AI engines, assigning roles such as planning, coding, and review to different models for efficient collaboration. -
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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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Swarms
Enterprise multi-agent orchestration framework for scalable AI apps
Swarms is an enterprise-grade multi-agent orchestration framework designed to help developers build, manage, and scale collaborative AI systems composed of multiple agents. It provides a structured infrastructure for coordinating agents in hierarchical, parallel, or sequential workflows, enabling complex task execution across distributed components. It emphasizes production readiness, offering modular architecture, high availability, and observability features suitable for large-scale deployments. It supports integration with multiple model providers and existing ecosystems, allowing developers to combine different AI tools and frameworks within a unified system. ... -
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mvnd
Apache Maven Daemon
Apache Maven is a software project management and comprehension tool. Based on the concept of a project object model (POM), Maven can manage a project's build, reporting and documentation from a central piece of information. -
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Balloon
Modernized and sophisticated tooltips, fully customizable
Modernized and sophisticated tooltips, fully customizable with an arrow and animations on Android. -
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CodeceptJS
Supercharged End 2 End Testing Framework for NodeJS
CodeceptJS is a modern end-to-end testing framework for Node.js applications, enabling developers to write tests in a behavior-driven development (BDD) style with an emphasis on simplicity and readability. -
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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. ... -
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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. -
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Otter-Grader
A Python and R autograding solution
...It is designed to work with classes at any scale by abstracting away the autograding internals in a way that is compatible with any instructor's assignment distribution and collection pipeline. Otter supports local grading through parallel Docker containers, grading using the autograder platforms of 3rd party learning management systems (LMSs), the deployment of an Otter-managed grading virtual machine, and a client package that allows students to run public checks on their own machines. Otter is designed to grade Python scripts and Jupyter Notebooks, and is compatible with a few different LMSs, including Canvas and Gradescope. -
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Findomain
Fast open source tool for discovering and monitoring domain subdomains
...It focuses on speed and reliability by using Certificate Transparency logs and multiple well tested public APIs instead of relying solely on brute force scanning techniques. By querying multiple passive data sources in parallel, the tool can identify a large number of subdomains within a short time, making it useful for security researchers, penetration testers, and bug bounty hunters. Findomain aggregates information from various online services to provide a comprehensive list of discovered subdomains without directly attacking the target infrastructure. ... -
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Flash-MoE
Running a big model on a small laptop
...The project aims to reduce the computational cost typically associated with MoE systems while maintaining or improving performance. It likely includes support for GPU acceleration and parallel processing, enabling it to handle large-scale workloads effectively. The architecture emphasizes speed and efficiency, making it suitable for both research and production environments where performance is critical. It may also provide tools for benchmarking and tuning model behavior. Overall, flash-moe represents a technical advancement in making MoE models more practical and deployable. -
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CampusShame
Crowdsource and document the reputational history of companies
...It compiles lists of companies that have had so-called “shameful” behaviors, such as rescinding offers, canceling intention letters, or terminating three-party agreements after acceptance, alongside a parallel list of companies without reported negative incidents. The project draws on publicly available anecdotes, snapshots, and forum posts from platforms such as NowCoder, Maimai, and Zhihu to provide evidence and context for each entry, preserving details that might otherwise be lost as threads get deleted or censored. It also includes commentary on recruitment pitfalls and encourages contributors to share their own experiences or corrections to keep the list up to date.
