ABSTRACT
The subject of this chapter is the design and analysis of parallel algorithms. Most of today’s computer algorithms are sequential, that is, they specify a sequence of steps in which each step consists of a single operation. As it has become more difficult to improve the performance of sequential computers, however, researchers have sought performance improvements in another place: parallelism. In contrast to a sequential algorithm, a parallel algorithm may perform multiple operations in a single step. For example, consider the problem of computing the sum of a sequence, A, of n numbers. The standard sequential algorithm computes the sum by making a single pass through the sequence, keeping a running sum of the numbers seen so far. It is not difficult, however, to devise an algorithm for computing the sum that performs many operations in parallel. For example, suppose that, in parallel, each element of A with an even index is paired and summed with the next element of A, which has an odd index, i.e., A[0] is paired with A[1], A[2] with A[3], and so on. The result is a new sequence of n/2 numbers whose sum is identical to the sum that we wish to compute. This pairing and summing step can be repeated, and after log2 n steps, only the final sum remains.
