Parallel programming

Abstract

In the past 20 years there has been treftlen-dous progress in developing and analyzing parallel algorithftls. Researchers have developed efficient parallel algorithms to solve most problems for which efficient sequential solutions are known. Although some of these algo-rithms are efficient only in a theoretical framework, many are quite efficient in practice or have key ideas that have been used in efficient implementations. This research on parallel algo-rithms has not only improved our general understanding ofpar-allelism but in several cases has led to improvements in sequential algorithms. Unf:ortunately there has been less success in developing good lan-guages f:or prograftlftling parallel algorithftls, particularly languages that are well suited for teaching and pro-totyping algorithms. There has been a large gap between lan-guages that are too low level, requiring specification of many details that obscure the meaning of the algorithm, and languages that are too high level, making the performance implications of various constructs unclear. In sequential computing many stan-dard languages such as C or Pascal do a reasonable J·ob of bridg-ing this gap, but in parallel languages building such a bridge has been significantly more difficult.