Swarm: Decentralized Cloud for AI
  • Introduction
    • The Problem
    • How Swarm works
    • Built for AGI
  • Market Opportunity
  • Key Benefits
  • Competitive Landscape
  • Primary Market Segments
  • Value Proposition
  • Core Technologies
  • System Architecture
    • System Layers
    • Core Components
    • Resource Types
    • Node Specifications
    • Ray Framework Integration
    • Kubernetes Integration
  • AI Services
  • High Availability Design
    • Redundancy Architecture
    • Failover Mechanisms
    • Resource Optimization
    • Performance Metric
  • Privacy and Security
    • Defense in Depth Strategy
    • Security Layer Components
    • Confidential Computing: Secure Enclave Architecture
    • Secure Enclave Architecture
    • Data Protection State
    • Mesh VPN Architecture: Network Security
    • Network Security Feature
    • Data Privacy Framework
    • Privacy Control
  • Compliance Framework: Standards Support
    • Compliance Features
  • Security Monitoring
    • Response Procedures
  • Disaster Recovery
    • Recovery Metrics
  • AI Infrastructure
    • Platform Components
    • Distributed Training Architecture
    • Hardware Configurations
    • Inference Architecture
    • Inference Workflow
    • Serving Capabilities
    • Fine-tuning Platform
    • Fine-tuning Features
    • AI Development Tools
    • AI Development Features
    • Performance Optimization
    • Performance Metrics
    • Integration Architecture
    • Integration Methods
  • Development Platform
    • Platform Architecture
    • Development Components
    • Development Environment
    • Environment Features
    • SDK and API Integration
    • Integration Methods
    • Resource Management
    • Management Features
    • Tool Suite: Development Tools
    • Tool Features
    • Monitoring and Analytics
    • Analytics Features
    • Pipeline Architecture
    • Pipeline Features
  • Node Operations
    • Provider Types
    • Provider Requirements
    • Node Setup Process
    • Setup Requirements
    • Resource Allocation
    • Management Features
    • Performance Optimization
    • Performance Metrics
    • Comprehensive Security Implementation
    • Security Features
    • Maintenance Operations
    • Maintenance Schedule
    • Provider Economics
    • Economic Metrics
  • Network Protocol
    • Protocol Layers
    • Protocol Components
    • Ray Framework Integration
    • Ray Features
    • Mesh VPN Network
    • Mesh Features
    • Service Discovery
    • Discovery Features
    • Data Transport
    • Transport Features
    • Protocol Security
    • Security Features
    • Performance Optimization
    • Performance Metrics
  • Technical Specifications
    • Node Requirements
    • Hardware Specifications
    • Network Requirements
    • Network Specifications
    • Key Metrics for Evaluating AI Infrastructure
    • Metrics and Service Level Agreements (SLAs)
    • Security Standards
    • Security Requirements
    • Scalability Specifications
    • System Growth and Capacity
    • Compatibility Integration
    • Compatibility Matrix: Supported Software and Integration Details
    • Resource Management Framework
    • Resource Allocation Framework
  • Future Developments
    • Development Priorities: Goals and Impact
    • Roadmap for Platform Enhancements
    • Research Areas for Future Development
    • Strategic Objectives and Collaboration
    • Infrastructure Evolution Roadmap
    • Roadmap for Advancing Core Components
    • Market Expansion Framework
    • Expansion Targets: Strategic Growth Objectives
    • Integration Architecture: Technology Integration Framework
    • Integration Roadmap: Phased Approach to Technology Integration
  • Reward System Architecture: Network Incentives and Rewards
    • Reward Framework
    • Reward Distribution Matrix: Metrics and Weighting for Equitable Rewards
    • Hardware Provider Incentives: Performance-Based Rewards Framework
    • Dynamic Reward Scaling: Adaptive Incentive Framework
    • Resource Valuation Factors: Dynamic Adjustment Model
    • Network Growth Incentives: Expansion Rewards Framework
    • Long-term Incentive Structure: Rewarding Sustained Contributions
    • Performance Requirements: Metrics and Impact on Rewards
    • Sustainability Mechanisms: Ensuring Economic Balance
    • Long-term Viability Factors: Ensuring a Scalable and Sustainable Ecosystem
    • Innovation Incentives: Driving Technological Advancement and Network Growth
  • Network Security and Staking
    • Staking Architecture
    • Stake Requirements: Ensuring Commitment and Security
    • Security Framework: Network Protection Mechanisms
    • Security Components: Key Functions and Implementation
    • Monitoring Architecture: Real-Time Performance and Security Oversight
    • Monitoring Metrics: Key Service Indicators for Swarm
    • Risk Framework: Comprehensive Risk Management for Swarm
    • Risk Mitigation Strategies: Proactive and Responsive Measures
    • Slashing Conditions: Penalty Framework for Ensuring Accountability
    • Slashing Matrix: Violation Impact and Recovery Path
    • Network Protection: Comprehensive Security Architecture
    • Security Features: Robust Mechanisms for Network Integrity
    • Recovery Framework: Ensuring Resilience and Service Continuity
    • Recovery Process: Staged Actions for Incident Management
    • Security Governance: Integrated Oversight Framework
    • Control Framework: A Comprehensive Approach to Network Governance and Security
  • FAQ
    • How Swarm Parallelizes and Connects All GPUs
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  1. Technical Specifications

Network Requirements

PreviousHardware SpecificationsNextNetwork Specifications

Last updated 5 months ago

Network Architecture: Network Requirements

Swarm’s Network Architecture ensures a high-performance and scalable communication framework, accommodating diverse workloads and data transport needs. The architecture integrates multiple layers—core, edge, and access—each tailored to specific operational demands and network speeds.

Network Layers and Specifications

  1. Core Network:

    • Purpose: Acts as the backbone of the Swarm infrastructure, interconnecting regional hubs and data centers.

    • Specifications:

      • Speed: 100Gbps or higher.

      • Redundancy: Ensures uninterrupted connectivity with multiple failover routes.

    • Use Case:

      • Facilitates high-speed data transfers for large-scale AI workloads, including distributed training.

  2. Edge Network:

    • Purpose: Connects regional hubs and edge nodes closer to the end-users or data sources.

    • Specifications:

      • Speed: 10Gbps.

      • Regional: Optimized for workloads requiring lower latency and higher bandwidth at regional levels.

    • Use Case:

      • Supports real-time inference, content delivery, and IoT applications.

  3. Access Network:

    • Purpose: Connects local nodes and individual providers to the Swarm ecosystem.

    • Specifications:

      • Speed: 1Gbps minimum.

      • Local: Facilitates connections for part-time contributors and lightweight tasks.

    • Use Case:

      • Suitable for data preprocessing, model fine-tuning, and other lightweight workloads.

Key Features

  • Scalable Bandwidth:

    • Accommodates increasing workloads by scaling speeds across all network layers.

  • Redundancy:

    • Multiple failover paths in the Core Network ensure resilience and reliability.

  • Low Latency:

    • Edge and Access Networks are optimized for latency-sensitive applications like real-time inference.

  • Regional Optimization:

    • Edge Network’s regional hubs improve performance for localized workloads and reduce backhaul traffic.

Benefits

  • High Performance: 100Gbps core links provide the throughput needed for large-scale AI workloads.

  • Reliability: Redundant paths and regional optimizations ensure consistent uptime and minimal disruptions.

  • Flexibility: Supports a wide range of providers and workloads, from individual contributors to enterprise-scale operations.

  • Cost Efficiency: Local and regional networks enable providers to contribute resources at various scales, optimizing network costs.

Swarm’s Network Architecture ensures seamless, high-speed communication across its decentralized infrastructure, enabling efficient and reliable operations for AI applications at any scale.