Caching in Modern Computing

Overview

• Caching is used to enhance system performance and reduce response time.
• It is prevalent across different layers of system architecture from hardware to application level.

Hardware Caches

• L1 Cache:
  • Smallest and fastest, integrated into CPU.
  • Stores frequently accessed data and instructions for quick CPU access.
• L2 Cache:
  • Larger and slower than L1, located on CPU die or separate chip.
• L3 Cache:
  • Larger and slower than L2, often shared between CPU cores.
• Translation Lookaside Buffer (TLB):
  • Stores virtual-to-physical address translations to speed up memory access.

Operating System Level Caches

• Page Cache:
  • Managed by OS, stores recently used disk blocks in memory.
• Inode Cache:
  • Speeds up file system operations by reducing disk access.

Application System Architecture

• Front End Caching:
  • Web Browsers:
    • Cache HTTP responses for faster data retrieval based on expiration policies.
  • Content Delivery Networks (CDNs):
    • Cache static content to improve delivery speed.
• Load Balancers:
  • Can cache resources to reduce server load and improve response times.

Messaging Infrastructure

• Message Brokers (e.g., Kafka):
  • Cache messages on disk, allowing paced retrieval by consumers.

Distributed Caches

• Redis:
  • Stores key-value pairs in memory, offering high performance.

Full-Text Search Engines

• Elastic Search:
  • Indexes data for rapid document and log search.

Database Caching

• Write-Ahead Log (WAL):
  • Logs data before indexing in B-tree.
• Buffer Pool:
  • Caches query results in memory.
• Materialized Views:
  • Precompute and cache query results for faster access.
• Transaction Log:
  • Records all transactions and updates.
• Replication Log:
  • Tracks replication state in database clusters.

Importance of Caching

• Essential for optimizing system performance and efficiency.
• Multiple layers exist from front end to back end to enhance application and system efficiency.