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Data Parallel Algorithms

Howard Jay Siege, Lee Wang, John John E. So, Muthucumaru Maheswaran

Abstract

Data parallelism is a model of parallel computing in which the same set of instructions is applied to all the elements in a data set. A sampling of data parallel algorithms is presented. The examples are certainly not exhaustive, but address many issues involved in designing data parallel algorithms. Case studies are used to illustrate some algorithm design techniques; and to highlight some implementation decisions that influence the overall performance of a parallel algorithm. It is shown that the characteristics of a particular parallel machine to be used need to be considered in transforming a given task into a parallel algorithm that executes effectively. DATA PARALLEL ALGORITHMS Howard Jay Siegel, Lee Wang, John John E. So, and Muthucurnaru Maheswaran

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Key concepts: Computer science, Parallelism (grammar), Parallel algorithm, Analysis of parallel algorithms, Algorithm, Data parallelism, Parallel computing, Task parallelism