Search Results for "parallel"
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659 projects for "parallel" with 1 filter applied:
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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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AudioBookConverter
Improved AudioBookConverter based on freeipodsoftware release
...The software supports a wide range of input formats including MP3, FLAC, and AAC, and provides flexible output options for different devices. It includes intelligent artwork handling, automatically sourcing and merging cover images from files or directories. The application uses parallel encoding to improve performance, making it efficient for large audiobook collections. It also supports advanced chapter management, including importing and editing chapter structures. Overall, it simplifies audiobook creation while maintaining high-quality output and metadata integrity. -
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.
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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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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. ... -
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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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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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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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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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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. -
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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. -
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DFlash
Block Diffusion for Ultra-Fast Speculative Decoding
DFlash is an open-source framework for ultra-fast speculative decoding using a lightweight block diffusion model to draft text in parallel with a target large language model, dramatically improving inference speed without sacrificing generation quality. It acts as a “drafter” that proposes likely continuations which the main model then verifies, enabling significant throughput gains compared to traditional autoregressive decoding methods that generate token by token. -
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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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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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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. -
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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. -
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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. -
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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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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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Balloon
Modernized and sophisticated tooltips, fully customizable
Modernized and sophisticated tooltips, fully customizable with an arrow and animations on Android. -
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Inspect Petri
An alignment auditing agent capable of exploring alignment hypothesis
...The system supports major model APIs and comes with starter seeds and judge dimensions, enabling minutes-to-insight workflows for questions like reward hacking, self-preservation, or eval awareness. Petri is designed for parallel exploration: it spins many audits in flight, aggregates findings, and highlights transcripts that deserve human review. -
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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. -
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Pro Workflow
Claude Code learns from your corrections: self-correcting memory
...The system learns from user corrections over time, storing feedback and refining its behavior across sessions to improve accuracy and efficiency. It supports advanced development setups such as parallel worktrees, enabling multiple tasks to be handled simultaneously without interference. The framework includes a collection of prebuilt skills and workflows that have been tested in real-world scenarios, providing a strong starting point for developers. It emphasizes continuous improvement, where each interaction contributes to better performance in future tasks. ...
