Caching
10 months ago
- #caching
- #computing
- #performance
- Caching is a fundamental principle in computing that enhances speed and efficiency by storing frequently accessed data in faster storage.
- Trade-offs between capacity, speed, cost, and durability are key considerations in designing data storage systems.
- RAM serves as an intermediate cache between the CPU and hard drives, significantly speeding up data access.
- Modern CPUs utilize multiple cache layers (L1, L2, L3) to optimize performance, with each layer balancing speed and capacity.
- Temporal locality in caching prioritizes recent data, as seen in social media platforms where newer posts are accessed more frequently.
- Spatial locality predicts and prefetches related data, improving performance in applications like photo albums.
- Geospatial caching uses CDNs to reduce latency by storing data closer to the user's location.
- Cache replacement policies like LIFO, LRU, and time-aware LRU determine which data to evict when the cache is full.
- Databases like Postgres and MySQL implement internal caching mechanisms to optimize query performance.
- Caching is pervasive across all layers of computing, though this article only scratches the surface of its complexities and applications.