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In computer science, a parallel algorithm, as opposed to a traditional serial algorithm, is an algorithm which can do multiple operations in a given time. It has been a tradition of computer science to describe serial algorithms in abstract machine models, often the one known as random-access machine .
An initial version of this model was introduced, under the MapReduce name, in a 2010 paper by Howard Karloff, Siddharth Suri, and Sergei Vassilvitskii. [2] As they and others showed, it is possible to simulate algorithms for other models of parallel computation, including the bulk synchronous parallel model and the parallel RAM, in the massively parallel communication model.
In many respects, analysis of parallel algorithms is similar to the analysis of sequential algorithms, but is generally more involved because one must reason about the behavior of multiple cooperating threads of execution. One of the primary goals of parallel analysis is to understand how a parallel algorithm's use of resources (speed, space ...
HRT-HOOD: A Structured Design Method for Hard Real-Time Ada Systems. North-Holland. ISBN 0-444-82164-3. Savitch, Walter; Peterson, Charles (1992). Ada: An Introduction to the Art and Science of Programming. Benjamin-Cummings Publishing Company. ISBN 0-8053-7070-6. Weiss, Mark Allen (1993). Data Structures and Algorithm Analysis in Ada. Benjamin ...
Concurrent and parallel programming languages involve multiple timelines. Such languages provide synchronization constructs whose behavior is defined by a parallel execution model . A concurrent programming language is defined as one which uses the concept of simultaneously executing processes or threads of execution as a means of structuring a ...
These parallel algorithms are also known for being simple, by standards of other approaches to parallel algorithms. This large body of parallel algorithms knowledge for the PRAM model and their relative simplicity motivated building computers whose programming can be guided by these parallel algorithms.
Due to the inherent difficulties in full automatic parallelization, several easier approaches exist to get a parallel program in higher quality. One of these is to allow programmers to add "hints" to their programs to guide compiler parallelization, such as HPF for distributed memory systems and OpenMP or OpenHMPP for shared memory systems ...
In parallel computing, execution occurs at the same physical instant: for example, on separate processors of a multi-processor machine, with the goal of speeding up computations—parallel computing is impossible on a single processor, as only one computation can occur at any instant (during any single clock cycle).