The cube-connected cycles: a versatile network for parallel computation
Communications of the ACM
The Design and Analysis of Computer Algorithms
The Design and Analysis of Computer Algorithms
On the relation between functional and data parallel programming languages
FPCA '93 Proceedings of the conference on Functional programming languages and computer architecture
Parallelization of divide-and-conquer by translation to nested loops
Journal of Functional Programming
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In this paper we show how it is often possible to transform and optimize parallel algorithms based on the Divide-and-Conquer paradigm at compile time. Our goal is to make Divide-and-Conquer algorithms suitable for implementation on hypercube-like parallel architectures, such as the Connection Machine, even if the original algorithm implies a division function that is not the left-right division and/or communication pattern that cannot be implemented by direct-neighbor communication.Our tools are the formal model of the Divide-and-Conquer paradigm developed in [4] and the parallel programming language derived from this model: Divacon [2], [3].Our main results concern the replacement of last-k communication (broadcast) and mirror image communication with correspondent communication and the transformation from odd-even division to left-right division and vice versa. By using each of the techniques described in this paper it is possible to improve many Divide-and-Conquer algorithms by a factor of log(n).