Showing 3 open source projects for "parallel"

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    forkd

    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.
    Downloads: 4 This Week
    Last Update:
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  • 2
    CubeSandbox

    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. ...
    Downloads: 2 This Week
    Last Update:
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  • 3
    AgentENV

    AgentENV

    Distributed platform for running agent environments at scale

    ...Overlay-based storage and bounded local caching keep frequently used data close without requiring every image to fit on each host. Snapshot-backed sandboxes can pause, resume, fork, and persist memory and filesystem changes for parallel or recoverable workflows. The platform includes an aenv command-line interface for creating templates, starting shells, executing commands, and managing sandbox lifecycles. Its E2B-compatible HTTP API lets existing Python and TypeScript integrations target a self-hosted deployment with minimal changes. AgentENV is designed for high-density agentic reinforcement learning and currently requires trusted-network deployment because built-in authorization is not yet available.
    Downloads: 0 This Week
    Last Update:
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