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Hence, fine-grained parallelism facilitates load balancing. [3] As each task processes less data, the number of processors required to perform the complete processing is high. This in turn, increases the communication and synchronization overhead. Fine-grained parallelism is best exploited in architectures which support fast communication.
This type of multithreading is known as block, cooperative or coarse-grained multithreading. The goal of multithreading hardware support is to allow quick switching between a blocked thread and another thread ready to run. Switching from one thread to another means the hardware switches from using one register set to another.
A lock is a programming language construct that allows one thread to take control of a variable and prevent other threads from reading or writing it, until that variable is unlocked. The thread holding the lock is free to execute its critical section (the section of a program that requires exclusive access to some variable), and to unlock the ...
Fine-grained multithreading—such as in a barrel processor—issues instructions for different threads after every cycle, while coarse-grained multithreading only switches to issue instructions from another thread when the current executing thread causes some long latency events (like page fault etc.). Coarse-grain multithreading is more ...
"Embarrassingly" is used here to refer to parallelization problems which are "embarrassingly easy". [4] The term may imply embarrassment on the part of developers or compilers: "Because so many important problems remain unsolved mainly due to their intrinsic computational complexity, it would be embarrassing not to develop parallel implementations of polynomial homotopy continuation methods."
lock contention: this occurs whenever one process or thread attempts to acquire a lock held by another process or thread. The more fine-grained the available locks, the less likely one process/thread will request a lock held by the other. (For example, locking a row rather than the entire table, or locking a cell rather than the entire row);
This code shows the effect of false sharing. It creates an increasing number of threads from one thread to the number of physical threads in the system. Each thread sequentially increments one byte of a cache line, which as a whole is shared among all threads. The higher the level of contention between threads, the longer each increment takes.
Core Python Programming is a textbook on the Python programming language, written by Wesley J. Chun. The first edition of the book was released on December 14, 2000. [1] The second edition was released several years later on September 18, 2006. [2] Core Python Programming is mainly targeted at higher education students and IT professionals. [3]