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Synchronization overheads can significantly impact performance in parallel computing environments, where merging data from multiple processes can incur costs substantially higher—often by two or more orders of magnitude—than processing the same data on a single thread, primarily due to the additional overhead of inter-process communication ...
In concurrent programming, a monitor is a synchronization construct that prevents threads from concurrently accessing a shared object's state and allows them to wait for the state to change. They provide a mechanism for threads to temporarily give up exclusive access in order to wait for some condition to be met, before regaining exclusive ...
A process is a program in execution, and an integral part of any modern-day operating system (OS). The OS must allocate resources to processes, enable processes to share and exchange information, protect the resources of each process from other processes and enable synchronization among processes.
If a process performs a P operation on a semaphore that has the value zero, the process is added to the semaphore's queue and its execution is suspended. When another process increments the semaphore by performing a V operation, and there are processes on the queue, one of them is removed from the queue and resumes execution.
Specifically, inter-process communication and synchronization can lead to overheads that are substantially higher—often by two or more orders of magnitude—compared to processing the same data on a single thread. [35] [36] [37] Therefore, the overall improvement should be carefully evaluated.
In computer science, read-copy-update (RCU) is a synchronization mechanism that avoids the use of lock primitives while multiple threads concurrently read and update elements that are linked through pointers and that belong to shared data structures (e.g., linked lists, trees, hash tables).
In parallel computing, a barrier is a type of synchronization method. [1] A barrier for a group of threads or processes in the source code means any thread/process must stop at this point and cannot proceed until all other threads/processes reach this barrier. [2] Many collective routines and directive-based parallel languages impose implicit ...
In computer science, the readers–writers problems are examples of a common computing problem in concurrency. [1] There are at least three variations of the problems, which deal with situations in which many concurrent threads of execution try to access the same shared resource at one time.