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
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.
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.
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.
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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