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GPU621/Analyzing False Sharing

9 bytes removed, 14:56, 30 November 2022
Preface
= '''Preface''' =
In multicore concurrent programming, if the mutual exclusion is a "performance killer", then false sharing is a worthy "performance assassin". The difference between "killer" and "assassin" is that a "killer" can be easily detected, and we always have many ways to deal with a "killer" when we fight it, such as fighting, running away, detouring, and begging for mercy, but an "assassin" is completely different. Assassins are good at hiding in the shadows and can strike give a fatal blow at any time, which makes making people defencelessdefensive.
In our concurrent development, when we encounter situations that affect concurrency performance, we always have many ways to find and improve the concurrency performance of the program. But false sharing leaves no trace in our code that it is in the "dark" and is seriously slowing down concurrency performance, making it hard to find the root cause of the problem, let alone improve concurrency performance.
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