# False Sharing

DevFeed: [False Sharing](<https://devfeed.tech/articles/false-sharing-24842.md>)

Original publisher: [Read original article](<https://alidg.me/blog/2020/5/1/false-sharing>)

Author: Alimate

Published: 2020-05-01T00:00:00Z

Content type: article

Language: en

Sources: [Ali Dehghan - Kemikit](<https://devfeed.tech/sources/ali-dehghan-kemikit.md>)

Topics: [Latency](<https://devfeed.tech/topics/latency.md>), [Concurrency](<https://devfeed.tech/topics/concurrency.md>), [Benchmark](<https://devfeed.tech/topics/benchmark.md>), [Concurrent Programming](<https://devfeed.tech/topics/concurrent-programming.md>)

Tags: [benchmark](<https://devfeed.tech/tags/benchmark.md>), [jvm](<https://devfeed.tech/tags/jvm.md>), [latency](<https://devfeed.tech/tags/latency.md>), [memory](<https://devfeed.tech/tags/memory.md>), [multithreading](<https://devfeed.tech/tags/multithreading.md>), [padding](<https://devfeed.tech/tags/padding.md>)

## AI overview

This article explains how false sharing in multithreaded JVM applications can increase latency and throughput costs. It uses benchmarks and object-layout analysis to show how padding can isolate counters and improve performance.

## Source excerpt

Measuring false-sharing effect on latency and throughput