Distributed Processing

Abstract

AbstractParallel processing describes a computing environment where multiple processors cooperate to solve a given computational problem. It falls under the more general area of high‐performance computing that focuses on accelerating the execution time of applications by using a wide range of hardware and software techniques. Several scientific research areas have used parallel processing to address the computational requirements of data and compute‐intensive applications.Distributed memory architectures and shared memory architectures are the two main parallel hardware architectures. Distributed computing is often used to refer to the implementation of applications on distributed memory architectures. In the biomedical research field, it is the most widely used form of parallel processing. This article starts by a review of the architectural features of distributed and shared memory multiprocessor systems. The use of these architectures to empower sequence alignment algorithms, phylogenetic trees construction, and protein folding simulations is then discussed. Both general strategies as well as specific case examples of parallel applications in the biomedical research field are presented.