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ep:labs:01:contents:tasks:ex1 [2019/09/22 15:46] radu.mantu |
ep:labs:01:contents:tasks:ex1 [2025/02/11 23:14] (current) cezar.craciunoiu |
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| - | ==== 01. [15p] Vmstat ==== | + | ==== Google Colab Notebook ==== |
| - | The **vmstat** utility provides a good low-overhead view of system performance. Since **vmstat** is such a low-overhead tool, it is practical to have it running even on heavily loaded servers when it is needed to monitor the system’s health. | + | |
| - | === [10p] Task A - Monitoring stress === | ||
| - | Run **vmstat** on your machine with a 1 second delay between updates. Notice the CPU utilization (info about the output columns [[https://medium.com/@damianmyerscough/vmstat-explained-83b3e87493b3|here]]). | ||
| - | In another terminal, use the **stress** command to start N CPU workers, where N is the number of cores on your system. | + | For this lab, we will use Google Colab for exploring numpy and matplotlib. Please solve your tasks [[https://github.com/cosmaadrian/ml-environment/blob/master/EP_Plotting_I.ipynb|here]] by clicking "**Open in Colaboratory**". |
| - | Do not pass the number directly. In stead, use command substitution. | + | |
| - | + | ||
| - | === [5p] Task B - How does it work? === | + | |
| - | Let us look at how **vmstat** works under the hood. We can assume that all these statistics (memory, swap, etc.) can not be normally gathered in userspace. So how does **vmstat** get these values from the kernel? Or rather, how does any process interact with the kernel? Most obvious answer: //**system calls**//. | + | |
| - | + | ||
| - | <code bash> | + | |
| - | $ strace vmstat | + | |
| - | </code> | + | |
| - | + | ||
| - | "All well and good. But what am I looking at?" | + | |
| - | + | ||
| - | What you //should// be looking at are the system calls after the two **write**s that display the output header (hint: it has to do with **/proc/** file system). So. what are these files that **vmstat** opens? | + | |
| - | + | ||
| - | <code bash> | + | |
| - | $ file /proc/meminfo | + | |
| - | $ cat /proc/meminfo | + | |
| - | + | ||
| - | $ man 5 proc | + | |
| - | </code> | + | |
| - | + | ||
| - | The manual should contain enough information about what these kernel interfaces can provide. However, if you are interested in //how// the kernel generates the statistics in **/proc/meminfo** (for example), a good place to start would be [[https://elixir.bootlin.com/linux/v4.15/source/fs/proc/meminfo.c|meminfo.c]] (but first, [[https://ocw.cs.pub.ro/courses/so2|SO2 wiki]]). | + | |
| - | + | ||
| - | <solution -hidden> | + | |
| - | **Task A:**\\ | + | |
| - | <code bash> | + | |
| - | $ vmstat -w -n 1 | + | |
| - | $ stress -c $(nproc) | + | |
| - | </code> | + | |
| - | </solution> | + | |
| + | You can then export this python notebook as a PDF (**File -> Print**) and upload it to **Moodle**. | ||
