9944318
Finding all periods and initial palindromes of a string in parallel
An optimalO(log logn)-time CRCW-PRAM algorithm for computing all period lengths of a string is presented. Previous parallel algorithms compute the period only if it is shorter than half of the length of the string. The algorithm can be used to find all initial palindromes of a string in the same time and processor bounds. Both algorithms are the fastest possible over a general alphabet. We derive a lower bound for finding initial palindromes by modifying a known lower bound for finding the period length of a string [9]. Whenp processors are available the bounds become Θ(⌈n/p⌉+log⌈1+p/n⌉2p).
53304548
Parallel Detection of all Palindromes in a String
This paper presents two efficient concurrent-read concurrent-write parallel algorithms that find all palindromes in a given string: 
 
1. 
 
An O(log n) time, n-processor algorithm over general alphabets. In case of constant size alphabets the algorithm requires only n/log n processors, and thus achieves an optimal-speedup. 
 
 
 
 
2. 
 
An O(log log n) time, n log n/loglog n-processor algorithm over general alphabets. This is the fastest possible time with the number of processors used.
9566604
Speeding up dynamic programming
A number of important computational problems in molecular biology, geology, speech recognition, and other areas can be expressed as recurrences which have typically been solved with dynamic programming. By using more sophisticated data structures, and by taking advantage of further structure from the applications, the authors speed up the computation of several of these recurrences by one or two orders of magnitude. The algorithms used are simple and practical.<<ETX>>
11584586
Parallel Algorithmic Techniques for Combinatorial Computation
We have described a number of algorithmic tools that have been found useful in the construction of parallel algorithms; among these are prefix computation, ranking, Euler tours, ear decomposition, and matrix calculations. We have also described some of the applications of these tools, and listed many other applications. These algorithms seem likely to be useful not only in their own right, but also as examples of ways to break up other problems into parts suitable for parallel solution.
42250902
Maintaining Biconnected Components of Dynamic Planar Graphs
We present algorithms for maintaining the biconnected components of a planar graph undergoing repeated dynamic modifications, such as insertions and deletions of edges and vertices. We show how to test at any time whether two vertices belong to the same biconnected component, and how to insert and delete an edge in O(n2/3) time in the worst case, where n is the number of vertices in the graph. The data structure supports also insertions of new vertices and deletions of disconnected vertices in the same time bounds. This is the first sublinear-time algorithm known for this problem.