Concatenated parallelism: a technique for efficient parallel divide and conquer

Abstract

Efficient divide and conquer algorithms can be mapped to a parallel computer using either task parallelism or data parallelism. The former involves significant data movement and the latter can lead to severe load imbalances. A new strategy is proposed, which the authors call concatenated parallelism, for efficient parallel solution of problems resulting in divide and conquer trees. Their strategy is useful when the communication time due to data movement in distributing the subproblems is significant in comparison to the time required for subdivision.