Fractal-Compute-Orchestrations/FractalWorkspace

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A unified ecosystem and workspace for large-scale federated learning, bridging the gap between centralized model evolution and decentralized edge intelligence.

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  • Ngày tạo12/05/2026
  • Cập nhật gần nhất22/10/2026
  • Ngôn ngữPython
  • Giấy phép—
README.md23.0 KBRaw

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Fractal

Distributed Compute Orchestration and Edge Intelligence Framework

License Platform Design Status Architecture Maintainer

A unified distributed systems framework bridging centralized model orchestration with decentralized edge intelligence.

Overview | Design Case Study | Architecture | Core Paradigms | Repository Topology | Getting Started | Security


Fractal-Compute-Orchestrations%2FFractalWorkspace | Trendshift Fractal-Compute-Orchestrations%2FFractalWorkspace | Trendshift

Overview

Fractal is a high-performance distributed computing ecosystem engineered to harvest fragmented consumer compute across mobile edge devices while strictly preserving user privacy and device health. The framework treats edge devices not merely as remote processors, but as autonomous, resource-constrained nodes operating under human-centric constraints.

The ecosystem resolves the computational and memory walls of foundation models through two distinct, unified systems:

  1. FractalCore (Central Server & Orchestrator): The Python-based control plane responsible for multi-tenant isolation, dataset segment allocation, model graph compilation/slicing, deterministic federated weight aggregation (FedAvg), compute budgeting, and tokenized reward distribution.
  2. FractalAndroid (Edge Compute Node & Application): The native Kotlin/Android execution engine running on mobile hardware. It performs hardware-gated on-device training and memory-mapped inference, dynamically pausing workloads if thermals or battery thresholds are exceeded.

Ecosystem Subsystems

Central Server (FractalCore) Edge Compute Node (FractalAndroid)
Tenant Dashboard

Multi-Tenant Dashboard: Real-time fleet tracking, segment dispatch, and live aggregation telemetry.

Android Active Node

Edge Node: On-device training & telemetry.


System Architecture

Fractal operates on a hierarchical Master-Worker architecture designed to isolate control signals from mathematical payloads.

graph TD
    subgraph ControlPlane ["Control Plane (FractalCore Server)"]
        direction TB
        API["REST Gateway & Auth Controller"]
        TM["Tenant Isolation Manager"]
        TS["Task Scheduler & Segment Dispatcher"]
        FA["Federated Weight Aggregator (FedAvg)"]
        Slicer["Graph Slicer & INT4 Quantizer"]
        Budget["TFLOPs Budget Controller"]
    end

    subgraph DataPlane ["Data Plane (FractalAndroid Edge Nodes)"]
        direction TB
        N1["Android Node A (Layers 0-7 / Worker)"]
        N2["Android Node B (Layers 8-15 / Worker)"]
        N3["Android Node C (Layers 16-23 / Worker)"]
        N4["Android Node D (Layers 24-31 / Worker)"]
    end

    subgraph PersistenceLayer ["Persistence & Ledger"]
        FS[("Firestore Ledger (Tokens / Rewards / Nodes)")]
        Disk[("Physical Data Silos (Bins / Checkpoints / PTE Slices)")]
    end

    %% Control Plane Internal Flow
    API --> TM
    TM --> TS
    TS --> Budget
    FA --> Disk
    Slicer --> Disk
    API --> FS

    %% Network Interactions
    N1 & N2 & N3 & N4 <-->|"REST API / TLS (Task Polling & Weight Uploads)"| API
    N1 -->|"INT8 Activation Stream (Wi-Fi Socket)"| 

Nội dung README thuộc về Fractal-Compute-Orchestrations và cộng đồng đóng góp, giấy phép Không có giấy phép. Nguồn: github.com/Fractal-Compute-Orchestrations/FractalWorkspace