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In Python, functions are first-class objects that can be created and passed around dynamically. Python's limited support for anonymous functions is the lambda construct. An example is the anonymous function which squares its input, called with the argument of 5:
Busy-waiting itself can be made much less wasteful by using a delay function (e.g., sleep()) found in most operating systems. This puts a thread to sleep for a specified time, during which the thread will waste no CPU time. If the loop is checking something simple then it will spend most of its time asleep and will waste very little CPU time.
Python 3.0, released in 2008, was a major revision not completely backward-compatible with earlier versions. Python 2.7.18, released in 2020, was the last release of Python 2. [37] Python consistently ranks as one of the most popular programming languages, and has gained widespread use in the machine learning community. [38] [39] [40] [41]
Before being introduced to lock granularity, one needs to understand three concepts about locks: lock overhead: the extra resources for using locks, like the memory space allocated for locks, the CPU time to initialize and destroy locks, and the time for acquiring or releasing locks. The more locks a program uses, the more overhead associated ...
The longer a thread holds a lock, the greater the risk that the thread will be interrupted by the OS scheduler while holding the lock. If this happens, other threads will be left "spinning" (repeatedly trying to acquire the lock), while the thread holding the lock is not making progress towards releasing it.
The differences between the two approaches are quite small. Read-side locking moves to rcu_read_lock and rcu_read_unlock, update-side locking moves from a reader-writer lock to a simple spinlock, and a synchronize_rcu precedes the kfree. However, there is one potential catch: the read-side and update-side critical sections can now run concurrently.
The only difference in implementation is that in the first case we used a nested function with a name, g, while in the second case we used an anonymous nested function (using the Python keyword lambda for creating an anonymous function). The original name, if any, used in defining them is irrelevant.
The following pseudocode guarantees synchronization between barber and customer and is deadlock free, but may lead to starvation of a customer. The problem of starvation can be solved with a first-in first-out (FIFO) queue. The semaphore would provide two functions: wait() and signal(), which in terms of C code would correspond to P() and V ...