Off-line Parallel Exact String Searching

The string matching problem is defined as follows: given a string P0 ... Pm-1 called the pattern and a string T0 .. .Tn-1 called the text find all occurrences of the pattern in the text. The output of a string matching algorithm is a boolean array MATCH[0..n — 1] which contains a true value at each position where an occurrence of the pattern starts. Many sequential algorithms are known that solve this problem optimally, i.e., in a linear O(n) number of operations, most notable of which are the algorithms by Knuth, Morris and Pratt and by Boyer and Moore. In this chapter we limit ourselves to parallel algorithms. All algorithms considered in this chapter are for the parallel random access machine (PRAM) computation model. In the design of parallel algorithms for the various PRAM models, one tries to optimize two factors simultaneously: the number of processors used and the time required by the algorithm. The total number of operations performed, which is the time-processors product, is the measure of optimality. A parallel algorithm is called optimal if it needs the same number of operations as the fastest sequential algorithm. Hence, in the string matching problem, an algorithm is optimal if its time-processor product is linear in the length of the input strings. Apart from having an optimal algorithm the designer wishes the algorithm to be the fastest possible, where the only limit on the number of processors is the one caused by the time-processor product. The following fundamental lemma given by Brent is essential for understanding the tradeoff between time and processors : Any PRAM algoriihm of time t that consists of x elementary operations can be implemented on p processors in O(x/p + t) time. Using Brent’s lemma, any algorithm that uses a large number x of processors to run very fast can be implemented on p < x processors, with the same total work, however with an increase in time as described. A basic problem in the study of parallel algorithms for strings and arrays is finding the maximal/minimal position in an array that holds a certain value.