Scaling Approach
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A Scaling Approach is a system development approach that achieves performance improvement through systematic resource increase (of computational resources, data volume, or model size).
- AKA: Scaling Strategy, Scale-Up Approach, Growth Approach.
- Context:
- It can typically follow Scaling Laws relating scaling approach resources to scaling approach performance.
- It can typically require Infrastructure Investment for scaling approach compute capacity.
- It can typically enable Capability Enhancement through scaling approach size increase.
- It can typically demonstrate Performance Gains at scaling approach threshold points.
- It can typically encounter Scaling Limits at scaling approach saturation levels.
- ...
- It can often reveal Emergent Properties at scaling approach critical scales.
- It can often drive Breakthrough Achievements through scaling approach extreme scales.
- It can often necessitate Architecture Redesign for scaling approach efficiency.
- It can often influence Resource Allocation in scaling approach optimization.
- ...
- It can range from being a Linear Scaling Approach to being an Exponential Scaling Approach, depending on its scaling approach growth pattern.
- It can range from being a Horizontal Scaling Approach to being a Vertical Scaling Approach, depending on its scaling approach expansion direction.
- It can range from being a Compute Scaling Approach to being a Data Scaling Approach, depending on its scaling approach resource focus.
- It can range from being an Efficient Scaling Approach to being a Brute-Force Scaling Approach, depending on its scaling approach optimization level.
- ...
- It can integrate with Moore's Law for scaling approach hardware progression.
- It can connect to Amdahl's Law for scaling approach parallelization limits.
- It can interface with Power Law for scaling approach relationship modeling.
- It can communicate with System Architecture for scaling approach implementation.
- It can synchronize with Performance Metric for scaling approach evaluation.
- ...
- Example(s):
- Horizontal Scaling adding scaling approach parallel nodes.
- Vertical Scaling increasing scaling approach node capacity.
- Database Sharding distributing scaling approach data partitions.
- Model Parallelism splitting scaling approach computation layers.
- ...
- Counter-Example(s):
- Optimization Approach, which improves efficiency without size increase.
- Algorithmic Innovation, which enhances performance through better methods.
- Compression Technique, which reduces resource requirements while maintaining capability.
- See: Moore's Law, Horizontally Scalable Computing System, Language Model Scaling Law, Deep Learning Scaling Laws Relationship, Quadratic Scaling, 1972 GeneralizedIterativeScaling.