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Then, depending on the value, we can use the kernel only if we need to sleep or to wake other threads. Instead of asking for the kernel to take care of the mutex value for us, we can keep track of it in userspace. Don't forget that our goal is to be as fast as possible in the common case, which is when the lock is not taken. However, doing syscalls requires expensive context switches (and costs even more in the face of Meltdown).
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After all, only the kernel can put a thread to sleep and awaken it when asked. But if I would implement my own, I would make sure to use the kernel. So how is a userspace mutex implemented? There are different approaches to it, as operating systems and programming libraries can take different directions. They should be super fast when the lock is not taken and ensure that tasks waiting to get the lock don't waste CPU time. The goal of a mutex is to enable multiple threads to do their work, so ideally we should not impose high overheads with our mutexes. There are several other sync mechanisms out there, like spinlocks, semaphores and barriers, but in this article we are going to focus just on mutexes. Even if the thread gets scheduled with the lock, any other thread that tries to change the account_balance would face the mutex_lock() and would have to wait until someone calls mutex_unlock(). This would then make any thread changing the account balance do so exclusively, without racing to other threads. In our bank example, the code could be fixed like this: mutex_lock() If when you want to lock it's already locked, then you need to patiently wait for another thread to open the door and give you the key. This is how a mutex works: you lock to use access the critical section and then unlock after using it. When exiting, you leave the key for the next person. You get the key for the room, access it, and lock the door. Imagine that there's a room that can only be accessed by one person at a time. Mutex is a sync primitive that helps you make sure only one thread can access a critical section (hence the name, mutual exclusion). So how do we solve this? Mutual exclusion: Mutex If we were in a multiprocessor machine, this issue would be even worse given that these threads can run in concurrency.īut it's not that bad, right? You got more moneys! However, the opposite scheduling could happen as well, keeping you with only 200 moneys in the bank. Thread 2 writes 200 to account_balance, but just after Thread 1 overwrites it with 700. Given that both threads were sharing the same resource ( account_balance) and aren't using synchronization mechanisms, they failed to keep data consistence. However, the scheduler preemption can interleave the execution of both threads, resulting in something like this: Thread 1 aux = account_balance // 500Īnd back to Thread 1 account_balance = aux // 700 In this case, if Thread 2 went before Thread 1 the final result would be the same anyway: Thread 2 aux = account_balance // 500 The kernel can order the threads in different manners. Then, in the fast multithread bank system, this happens: Thread 1 aux = account_balance // 500Īll good! Everything went as expected. You want to withdraw 300 moneys and at the same time your friend wants to send you 200 moneys.
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Let's say that you have 500 moneys in the bank.
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Imagine that your bank has a multithreading software to manage your account running in a single core, but failed to correctly use synchronization mechanisms. Using the same data at the same moment can lead to serious bugs as we will see next. Since the arrival of multitasking operating systems, different tasks can now work at the same time and compete for the same resources. Data racingīefore getting into futex, we need to know which problem it solves: race condition. Read on as I take a deep dive into this important system call and how it is used to process synchronization functions. If you are a Linux gamer trying to increase the performance of your setup, you have probably heard of futex as well. If you've ever run strace in a multithread program, chances are that the trace was filled with futex() calls.
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But what exactly is futex? This series of blog posts will help answer that and other questions around this tricky function.
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As part of this prolonged effort, the futex_waitv() syscall has now successfully landed in Linux 5.16.Ī followup of the initial futex syscall, this new interface aims to overcome long term issues that have been limiting the way applications use the Linux kernel. Over the past 18 months, we have been on a roller-coaster ride developing futex2, a new set of system calls.