Implementing Partition on Vector Computers

The partitioning of an array is the basic building block of many efficient sorting algorithms. Here we study three ways to implement partitioning on vector supercomputers. A data model is presented with which the performances of these algorithms are analyzed. Performance is also measured on one processor of a Cray X-MP. Speedups between four and seventeen have been obtained for large data sets for an implementation using only O( p n) more storage space and comparisons than the original algorithm. 1 Introduction One of the most popular methods for internal sorting is "quicksort" originally proposed by Hoare [7, 9, 4, 18]. It has optimal mean complexity O(n log(n)) which makes it competitive for large data sets even for vector computers running in sequential mode [13]. This motivated the present study on vectorization properties of the kernel of quicksort. Several implementations of quicksort for sequential computers have been investigated to some depth in [7, 8, 16, 14, 15, 10]. Th..