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Cache-coherent system

A cache-coherent system maintains consistent views of shared data across multiple caches or processing agents.

How 2 Manning books explain it

Latency

Cache coherence is the property that multiple caches maintain mutually consistent views of shared data.

How it is used
Uses coherence protocols to preserve a consistent shared-memory view across caches in multicore systems.
How deep it goes
Defines stale-data failure, explains write coordination, names MESI, and stops short of fully detailing all protocol states.
Examples
Uses per-core caches holding the same value and a 64-byte cache line to illustrate stale reads after a write.
What you can do after
Evaluate/understand why multicore programs avoid stale reads and why coherence introduces update latency.

Read how Latency explains cache-coherent system →

Learn Concurrent Programming with Go

Cache coherence is the coordination of cached copies so that processors observe consistent values for shared memory locations.

How it is used
Coordinates cached copies so processors communicate reliably through shared memory.
How deep it goes
Explains cache updates, invalidation, write-back, and scaling limits without detailing complete modern protocols.
Examples
Uses two threads, bus update messages, stale cache copies, and a shared-variable update diagram.
What you can do after
Evaluate how processors obtain updated shared values when local cache copies become stale.

Read how Learn Concurrent Programming with Go explains cache-coherent system →

Related concepts

These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.