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. Node Operations

Provider Requirements

Provider Requirements

Swarm’s node provider system outlines specific hardware and capacity requirements for each provider type to ensure compatibility, performance, and reliability across the decentralized infrastructure. These requirements are tailored to the provider's intended use case.

Provider Type

Minimum Requirements

Recommended Specs

Use Case

Individual

- 1 GPU, 32GB RAM - High-speed internet connection

- 4+ GPUs, 128GB RAM - SSD storage

Part-time compute for lightweight AI tasks, fine-tuning, or small-scale workloads.

Data Center

- 100+ GPUs, 1TB RAM - 10Gbps network connection

- 1000+ GPUs, 10TB RAM - NVMe storage

Full-time compute for large-scale training, distributed AI, and enterprise workloads.

Edge

- 10+ GPUs, 256GB RAM - Localized network with low latency

- 50+ GPUs, 1TB RAM - High-speed storage

Regional compute for low-latency applications, real-time inference, or IoT tasks.

Key Features

  • Scalability: Providers can join the network with minimum requirements and scale up to meet larger workloads.

  • Performance Optimization: Recommended specs ensure optimal efficiency and reliability for specific use cases.

  • Diverse Contributions: Supports a wide range of providers, from individual contributors to enterprise-grade data centers.

Benefits

  • Flexibility: Accommodates providers of varying capacities, ensuring broad participation in the network.

  • Cost Efficiency: Leverages underutilized resources from individuals and organizations to reduce operational costs.

  • High Availability: Ensures continuous resource availability for AI workloads, regardless of scale or complexity.

These provider requirements create a robust and versatile infrastructure, enabling Swarm to deliver high-performance, cost-effective AI services.

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Last updated 5 months ago