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

System Growth and Capacity

Scaling Limits: System Growth and Capacity

Swarm’s Scaling Limits define the parameters and growth rates for its decentralized infrastructure. These limits provide a flexible framework for adding capacity and adapting to increasing demands while maintaining optimal performance.

Dimension

Minimum

Maximum

Growth Rate

Nodes/Cluster

3

1,000

100 nodes/month

GPUs/Node

1

16

As needed

Storage/Node

1TB

100TB

10TB/month

Network/Node

1Gbps

100Gbps

10Gbps/quarter

Descriptions

  1. Nodes/Cluster:

    • Minimum: Requires at least 3 nodes per cluster for redundancy and distributed operations.

    • Maximum: Supports up to 1,000 nodes per cluster, scaling to handle large workloads.

    • Growth Rate: Allows for a rapid increase in capacity with up to 100 new nodes added per month.

  2. GPUs/Node:

    • Minimum: Each node requires at least one GPU for compute tasks.

    • Maximum: Nodes can support up to 16 GPUs for high-performance workloads.

    • Growth Rate: GPU additions scale as needed, depending on workload requirements.

  3. Storage/Node:

    • Minimum: Each node must provide at least 1TB of storage for data and workloads.

    • Maximum: Nodes can expand up to 100TB, accommodating extensive datasets.

    • Growth Rate: Storage scales by 10TB per month to meet increasing data demands.

  4. Network/Node:

    • Minimum: Requires a baseline of 1Gbps connectivity for basic operations.

    • Maximum: Supports up to 100Gbps for high-speed data transfer.

    • Growth Rate: Network capacity grows by 10Gbps per quarter to support expanding clusters.

Key Benefits

  • Flexibility: Supports gradual or rapid scaling to match workload and operational growth.

  • High Capacity: Accommodates the demands of large-scale AI training, inference, and data storage.

  • Global Reach: Scales network bandwidth to maintain low latency and high throughput for distributed systems.

  • Performance Optimization: Ensures infrastructure growth aligns with compute, storage, and network requirements.

These Scaling Limits provide Swarm with the ability to scale dynamically while maintaining performance, reliability, and cost efficiency, supporting both small and enterprise-scale AI workloads.

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Last updated 4 months ago