Search results
Results From The WOW.Com Content Network
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]
Alternatively an RW lock can be implemented in terms of a condition variable, cond, an ordinary (mutex) lock, g, and various counters and flags describing the threads that are currently active or waiting. [7] [8] [9] For a write-preferring RW lock one can use two integer counters and one Boolean flag:
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.
Python sets are very much like mathematical sets, and support operations like set intersection and union. Python also features a frozenset class for immutable sets, see Collection types. Dictionaries (class dict) are mutable mappings tying keys and corresponding values. Python has special syntax to create dictionaries ({key: value})
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 ...
This approach does not work on multiprocessor systems where it is possible for two programs sharing a semaphore to run on different processors at the same time. To solve this problem in a multiprocessor system, a locking variable can be used to control access to the semaphore. The locking variable is manipulated using a test-and-set-lock command.
not hold the lock across system or function calls where the entity is no longer running on the processor – this can lead to deadlock; ensure that if the entity is unexpectedly exited for any reason, the lock is freed. Non-holders of the lock (a.k.a. waiters) can be held in a list that is serviced in a round-robin fashion, or in a FIFO queue ...