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Examples include iterative numerical methods, such as Newton's method, iterative solutions to the three-body problem, and most of the available algorithms to compute pi (π). [citation needed] Some sequential algorithms can be converted into parallel algorithms using automatic parallelization. [3]
A trivial example involves serving static data. It would take very little effort to have many processing units produce the same set of bits. Indeed, the famous Hello World problem could easily be parallelized with few programming considerations or computational costs. Some examples of embarrassingly parallel problems include: Monte Carlo ...
For example, the WT framework was adopted as the basic presentation framework in the parallel algorithms books (for the parallel random-access machine PRAM model) [3] and, [4] as well as in the class notes . [5]
Many parallel programs require that their subtasks act in synchrony. This requires the use of a barrier. Barriers are typically implemented using a lock or a semaphore. [27] One class of algorithms, known as lock-free and wait-free algorithms, altogether avoids the use of locks and barriers. However, this approach is generally difficult to ...
Pointer jumping or path doubling is a design technique for parallel algorithms that operate on pointer structures, such as linked lists and directed graphs. Pointer jumping allows an algorithm to follow paths with a time complexity that is logarithmic with respect to the length of the longest path. It does this by "jumping" to the end of the ...
In this article two efficient algorithms solving this problem are introduced. Another variation of the problem is the single-source-shortest-paths (SSSP) problem, which also has parallel approaches: Parallel single-source shortest path algorithm.
Concurrent computations may be executed in parallel, [3] [6] for example, by assigning each process to a separate processor or processor core, or distributing a computation across a network. The exact timing of when tasks in a concurrent system are executed depends on the scheduling , and tasks need not always be executed concurrently.
Fork–join is the main model of parallel execution in the OpenMP framework, although OpenMP implementations may or may not support nesting of parallel sections. [6] It is also supported by the Java concurrency framework, [ 7 ] the Task Parallel Library for .NET, [ 8 ] and Intel's Threading Building Blocks (TBB). [ 1 ]