Create a free Team What is Teams? Learn more. How long time does a context switch take in Linux ubuntu Asked 2 years, 8 months ago. Active 1 year, 6 months ago. Viewed 4k times. Earlier i have used perf , is this best practice? And how much time is used on a context switch per CPU? Improve this question. There are many publications about this topic. For example, Quantifying the cost of context switch. Add a comment. Remember - it's quite unlikely that the actual workload of your task will be negligible compared to the us context switch; as we've seen, even a modest memcpy takes longer.
Any sort of server logic such as parsing headers, updating state, etc. If there's one takeaway to remember from these sections is that context switching on modern Linux systems is super fast. Now it's time to discuss the other overhead of a large number of threads - memory. Even though all threads in a process share their, there are still areas of memory that aren't shared.
In the post about clone we've mentioned page tables in the kernel, but these are comparatively small. A much larger memory area that it private to each thread is the stack. The default per-thread stack size on Linux is usually 8 MiB, and we can check what it is by invoking ulimit :. To see this in action, let's start a large number of threads and observe the process's memory usage.
This sample launches 10, threads and sleeps for a bit to let us observe its memory usage with external tools. What is the difference, and how can it use 80 GiB of memory on a machine that only has 16 available?
A short interlude on what virtual memory means. When a Linux program allocates memory with malloc or otherwise, this memory initially doesn't really exist - it's just an entry in a table the OS keeps. Only when the program actually accesses the memory is the backing RAM for it found; this is what virtual memory is all about.
Therefore, the "memory usage" of a process can mean two things - how much virtual memory it uses overall, and how much actual memory it uses. While the former can grow almost without bounds - the latter is obviously limited to the system's RAM capacity with swapping to disk being the other mechanism of virtual memory to assist here if usage grows above the side of physical memory.
The actual physical memory on Linux is called "resident" memory, because it's actually resident in RAM. There's a good StackOverflow discussion of this topic; here I'll just limit myself to a simple example:. This program starts by allocating MiB of memory assuming an int size of 4 with malloc , and later "touches" this memory by writing a number into every element of the allocated array.
It reports its own memory usage at every step - see the full code sample for the reporting code [4]. Here's the output from a sample run:.
The most interesting thing to note is how vm size remains the same between the second and third steps, while max RSS grows from the initial value to MiB. This is precisely because until we touch the memory, it's fully "virtual" and isn't actually counted for the process's RAM usage. Therefore, distinguishing between virtual memory and RSS in realistic usage is very important - this is why the thread launching sample from the previous section could "allocate" 80 GiB of virtual memory while having only 80 MiB of resident memory.
As we've seen, a new thread on Linux is created with 8 MiB of stack space, but this is virtual memory until the thread actually uses it. If the thread actually uses its stack, resident memory usage goes up dramatically for a large number of threads.
I've added a configuration option to the sample program that launches a large number of threads; with it enabled, the thread function actually uses stack memory and from the RSS report it is easy to observe the effects. How to we control the stack size of threads? The more interesting question is - what should the stack size be set to?
As we have seen above, just creating a large stack for a thread doesn't automatically eat up all the machine's memory - not before the stack is being used. If our threads actually use large amounts of stack memory, this is a problem, because this severely limits the number of threads we can run concurrently. Note that this is not really a problem with threads - but with concurrency; if our program uses some event-driven approach to concurrency and each handler uses a large amount of memory, we'd still have the same problem.
If the task doesn't actually use a lot of memory, what should we set the stack size to? Small stacks keep the OS safe - a deviant program may get into an infinite recursion and a small stack will make sure it's killed early.
Moreover, virtual memory is large but not unlimited; especially on bit OSes, we might not have 80 GiB of virtual address space for the process, so a 8 MiB stack for 10, threads makes no sense. On bit Linux the virtual address space is vastly larger, so this limitation is less serious though other limits kick in - on my machine the maximal number of threads the OS lets one process start is about 32K.
Therefore I think it's more important to focus on how much actual memory each concurrent task is using than on the OS stack size limit, as the latter is simply a safety measure. Step away from your computer and savor your breaks.
This advice also applies to non-work hours and vacations. Enjoy them, and give yourself a much-needed opportunity to recharge and return to work refreshed. Because I can increase the playback speed of these looms to 2x, I can go into the meeting feeling informed without having to allocate too much of my own focus time preparing for it.
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Meditation lowers stress, boosts productivity, and inspires creativity, among a multitude of other scientifically-proven benefits — and you only need to meditate for a few minutes a day to reap the rewards.
Set a timer for two minutes to start you can increase this over time as you get more comfortable with meditation. Gently shut your eyes. If your upper body is tense, do a few neck and shoulder rolls to settle in.
Focus on the sound and movement of your own breath. When the timer is up, slowly rise, do a stretch that feels good to you, and ease back into your next task.
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