Affinity broken due to vector space exhaustion 问题
dmesg 中异常打印:
kernel: irq 632: Affinity broken due to vector space exhaustion.
kernel: irq 633: Affinity broken due to vector space exhaustion.
这个打印并不是申请不到中断号,而是已经申请到了中断号,但是配置中断路由的时候,
想要生效的中断绑核与预期不一致,代码为:
commit 743dac494d61d991967ebcfab92e4f80dc7583b3
Author: Neil Horman <nhorman@tuxdriver.com>
Date: Thu Aug 22 10:34:21 2019 -0400
x86/apic/vector: Warn when vector space exhaustion breaks affinity
On x86, CPUs are limited in the number of interrupts they can have affined
to them as they only **support 256 interrupt** vectors per CPU. 32 vectors are
reserved for the CPU and the kernel reserves another 22 for internal
purposes. That leaves 202 vectors for assignement to devices.
When an interrupt is set up or the affinity is changed by the kernel or the
administrator, the vector assignment code attempts to honor the requested
affinity mask. If the vector space on the CPUs in that affinity mask is
exhausted the code falls back to a wider set of CPUs and assigns a vector
on a CPU outside of the requested affinity mask silently.
While the effective affinity is reflected in the corresponding
/proc/irq/$N/effective_affinity* files the silent breakage of the requested
affinity can lead to unexpected behaviour for administrators.
Add a pr_warn() when this happens so that adminstrators get at least
informed about it in the syslog.
[ tglx: Massaged changelog and made the pr_warn() more informative ]
Reported-by: djuran@redhat.com
Signed-off-by: Neil Horman <nhorman@tuxdriver.com>
Signed-off-by: Thomas Gleixner <tglx@linutronix.de>
Tested-by: djuran@redhat.com
Link: https://lkml.kernel.org/r/20190822143421.9535-1-nhorman@tuxdriver.com
diff --git a/arch/x86/kernel/apic/vector.c b/arch/x86/kernel/apic/vector.c
index fdacb864c3dd..2c5676b0a6e7 100644
--- a/arch/x86/kernel/apic/vector.c
+++ b/arch/x86/kernel/apic/vector.c
@@ -398,6 +398,17 @@ static int activate_reserved(struct irq_data *irqd)
if (!irqd_can_reserve(irqd))
apicd->can_reserve = false;
}
+
+ /*
+ * Check to ensure that the effective affinity mask is a subset
+ * the user supplied affinity mask, and warn the user if it is not
+ */
+ if (!cpumask_subset(irq_data_get_effective_affinity_mask(irqd),
+ irq_data_get_affinity_mask(irqd))) {
+ pr_warn("irq %u: Affinity broken due to vector space exhaustion.\n",
+ irqd->irq);
+ }
+
return ret;
}
原因作者也解释得很清楚,就是x86的cpu,各个核能够接收的中断个数是有限制的,在centos7中,我们经常遇到配置中断路由失败的情况,没有异常打印,
所以针对这个问题,目前在内核中增加了这个打印。然后centos 8.3也移植了这个打印。
遇到这个问题,由于我们0号核一般是重灾区,所以要尽量将中断不要路由到0号核。
Affinity broken due to vector space exhaustion 问题的更多相关文章
- 向量空间模型(Vector Space Model)的理解
1. 问题描述 给你若干篇文档,找出这些文档中最相似的两篇文档? 相似性,可以用距离来衡量.而在数学上,可使用余弦来计算两个向量的距离. \[cos(\vec a, \vec b)=\frac {\v ...
- In abstract algebra, a congruence relation (or simply congruence) is an equivalence relation on an algebraic structure (such as a group, ring, or vector space) that is compatible with the structure in
https://en.wikipedia.org/wiki/Congruence_relation In abstract algebra, a congruence relation (or sim ...
- Solr相似度名词:VSM(Vector Space Model)向量空间模型
最近想学习下Lucene ,以前运行的Demo就感觉很神奇,什么原理呢,尤其是查找相似度最高的.最优的结果.索性就直接跳到这个问题看,很多资料都提到了VSM(Vector Space Model)即向 ...
- 转:Lucene之计算相似度模型VSM(Vector Space Model) : tf-idf与交叉熵关系,cos余弦相似度
原文:http://blog.csdn.net/zhangbinfly/article/details/7734118 最近想学习下Lucene ,以前运行的Demo就感觉很神奇,什么原理呢,尤其是查 ...
- ES搜索排序,文档相关度评分介绍——Vector Space Model
Vector Space Model The vector space model provides a way of comparing a multiterm query against a do ...
- 向量空间模型(Vector Space Model)
搜索结果排序是搜索引擎最核心的构成部分,很大程度上决定了搜索引擎的质量好坏.虽然搜索引擎在实际结果排序时考虑了上百个相关因子,但最重要的因素还是用户查询与网页内容的相关性.(ps:百度最臭名朝著的“竞 ...
- pytorch --- word2vec 实现 --《Efficient Estimation of Word Representations in Vector Space》
论文来自Mikolov等人的<Efficient Estimation of Word Representations in Vector Space> 论文地址: 66666 论文介绍了 ...
- Efficient Estimation of Word Representations in Vector Space 论文笔记
Mikolov T , Chen K , Corrado G , et al. Efficient Estimation of Word Representations in Vector Space ...
- 一天一经典Efficient Estimation of Word Representations in Vector Space
摘要 本文提出了两种从大规模数据集中计算连续向量表示(Continuous Vector Representation)的计算模型架构.这些表示的有效性是通过词相似度任务(Word Similarit ...
随机推荐
- vue大型电商项目尚品汇(后台篇)day02
这几天更新有点小慢,逐渐开始回归状态了.尽快把这个后台做完,要开始vue3了 3.添加修改品牌 用到组件 Dialog 对话框,其中visible.sync这个配置是修改他的显示隐藏的,label-w ...
- 十分钟快速实战Three.js
前言 本文不会对Three.js几何体.材质.相机.模型.光源等概念详细讲解,会首先分成几个模块给大家快速演示一盒小案例.大家可以根据这几个模块快速了解Three.js的无限魅力.学习 我们会使用Th ...
- CentOS中实现基于Docker部署BI数据分析
作为一个专业小白,咱啥都不懂. linux不懂,docker不懂. 但是我还想要完成领导下达的任务:在linux中安装docker后部署数据可视化工具.作为一名敬业 的打工人摆烂不可以,躺平不可以,弱 ...
- SAP 实例 9 Text output
REPORT demo_show_text. CLASS demo DEFINITION. PUBLIC SECTION. CLASS-METHODS main. ENDCLASS. CLASS de ...
- ArrayList和LinkedList内部是怎么实现的?他们之间的区别和优缺点?
ArrayList 内部使用了数组形式进行了存储,利用数组的下标进行元素的访问,因此对元素的随机访问速度非常快.因为是数组,所以ArrayList在初始化的时候, 有初始大小10,插入新元素的时候,会 ...
- 初学python常用,python模块安装和卸载的几种方法
兄弟们常常因为遇到模块不会安装,或者遇到报错就懵了,就很耽误学习进度,今天我们就一次性了解Python几种安装模块的方法~不过~ 实在是懒得看 点击此处找管理员小姐姐手把手教你安装 一.命令提示符窗口 ...
- CANN算子:利用迭代器高效实现Tensor数据切割分块处理
摘要:本文以Diagonal算子为例,介绍并详细讲解如何利用迭代器对n维Tensor进行基于位置坐标的大批量数据读取工作. 本文分享自华为云社区<CANN算子:利用迭代器高效实现Tensor数据 ...
- Codeforces Round #779 (Div. 2)
A 题目连接 题目大意 给一个01串,其中每一个长度大于等于2的子区间中0的数量不大于1的数量,最少插入多少1 思路 寻找 00 和 010 00 -->0110 加2 010 --&g ...
- thymeleaf实现前后端数据交换
1.前端传数据后端接收: 用户在登录界面输入用户名和密码传给后端controller,由后端判断是否正确! 在html界面中要传递的数据name命名,通过表单的提交按钮会传递给响应的controlle ...
- react配置postcss-pxtorem适配
适配移动端操作如下: 安装 postcss-pxtorem .amfe-flexible npm i postcss-pxtorem npm i amfe-flexible amfe-flexible ...