Parallel computational geometry of rectangles

Rectangles in a plane provide a very useful abstraction for a number of problems in diverse fields. In this paper we consider the problem of computing geometric properties of a set of rectangles in the plane. We give parallel algorithms for a number of problems usingn processors wheren is the number of upright rectangles. Specifically, we present algorithms for computing the area, perimeter, eccentricity, and moment of inertia of the region covered by the rectangles inO(logn) time. We also present algorithms for computing the maximum clique and connected components of the rectangles inO(logn) time. Finally, we give algorithms for finding the entire contour of the rectangles and the medial axis representation of a givenn × n binary image inO(n) time. Our results are faster than previous results and optimal (to within a constant factor).     

Parallel methods for visibility and shortest-path problems in simple polygons

In this paper we give efficient parallel algorithms for solving a number of visibility and shortest-path problems for simple polygons. Our algorithms all run inO(logn) time and are based on the use of a new data structure for implicitly representing all shortest paths in a simple polygonP, which we call thestratified decomposition tree. We use this approach to derive efficient parallel methods for computing the visibility ofP from an edge, constructing the visibility graph of the vertices ofP (using an output-sensitive number of processors), constructing the shortest-path tree from a vertex ofP, and determining all-farthest neighbors for the vertices inP. The computational model we use is the CREW PRAM.This research was announced in preliminary form in theProceedings of the 6th ACM Symposium on Computational Geometry, 1990, pp. 73–82. The research of Michael T. Goodrich was supported by the National Science Foundation under Grants CCR-8810568 and CCR-9003299, and by the NSF and DARPA under Grant CCR-8908092.     

Constructing the Voronoi diagram of a set of line segments in parallel

In this paper we give a parallel algorithm for constructing the Voronoi diagram of a polygonal scene, i.e., a set of line segments in the plane such that no two segments intersect except possibly at their endpoints. Our algorithm runs inO(log² n) time usingO(n) processors in the CREW PRAM model.The research of M. T. Goodrich was supported by NSF under Grants CCR-8810568 and CCR-9003299 and by NSF/DARPA under Grant CCR-8908092. C. K. Yap's research was supported in part by NSF Grants DCR-8401898 and CCR-9002819.     

Parallel algorithms for arrangements

We give the first efficient parallel algorithms for solving the arrangement problem. We give a deterministic algorithm for the CREW PRAM which runs in nearly optimal bounds ofO (logn log^* n) time andn ²/logn processors. We generalize this to obtain anO (logn log^* n)-time algorithm usingn ^d /logn processors for solving the problem ind dimensions. We also give a randomized algorithm for the EREW PRAM that constructs an arrangement ofn lines on-line, in which each insertion is done in optimalO (logn) time usingn/logn processors. Our algorithms develop new parallel data structures and new methods for traversing an arrangement.This work was supported by the National Science Foundation, under Grants CCR-8657562 and CCR-8858799, NSF/DARPA under Grant CCR-8907960, and Digital Equipment Corporation. A preliminary version of this paper appeared at the Second Annual ACM Symposium on Parallel Algorithms and Architectures [3].     

Optimal edge ranking of trees in polynomial time

An edge ranking of a graph is a labeling of the edges using positive integers such that all paths between two edges with the same label contain an intermediate edge with a higher label. An edge ranking isoptimal if the highest label used is as small as possible. The edge-ranking problem has applications in scheduling the manufacture of complex multipart products; it is equivalent to finding the minimum height edge-separator tree. In this paper we give the first polynomial-time algorithm to find anoptimal edge ranking of a tree, placing the problem inP. An interesting feature of the algorithm is an unusual greedy procedure that allows us to narrow an exponential search space down to a polynomial search space containing an optimal solution. AnNC algorithm is presented that finds an optimal edge ranking for trees of constant degree. We also prove that a natural decision problem emerging from our sequential algorithm isP-complete.The research of P. de la Torre was partially supported by NSF Grant CCR-9010445. R. Greenlaw's research was partially supported by NSF Grant CCR-9209184. The research of A. A. Schäffer was partially supported by NSF Grant CCR-9010534.Subsequent to the acceptance of this paper, Zhou and Nishizeki found faster algorithms for optimal edge ranking of trees, first reducing the time toO(n²) [22] and then toO(n logn) [23].     

Optimal parallel detection of squares in strings

A stringw isprimitive if it is not a power of another string (i.e., writingw =v ^k impliesk = 1. Conversely,w is asquare ifw =vv, withv a primitive string. A stringx issquare-free if it has no nonempty substring of the formww. It is shown that the square-freedom of a string ofn symbols over an arbitrary alphabet can be tested by a CRCW PRAM withn processors inO(logn) time and linear auxiliary space. If the cardinality of the input alphabet is bounded by a constant independent of the input size, then the number of processors can be reduced ton/logn without affecting the time complexity of this strategy. The fastest sequential algorithms solve this problemO(n logn) orO(n) time, depending on whether the cardinality of the input alphabet is unbounded or bounded, and either performance is known to be optimal within its class. More elaborate constructions lead to a CRCW PRAM algorithm for detecting, within the samen-processors bounds, all positioned squares inx in timeO(logn) and using linear auxiliary space. The fastest sequential algorithms solve this problem inO(n logn) time, and such a performance is known to be optimal.This research was supported, through the Leonardo Fibonacci Institute, by the Istituto Trentino di Cultura, Trento, Italy. Additional support was provided by the French and Italian Ministries of Education, by the National Research Council of Italy, by the British Research Council Grant SERC-E76797, by NSF Grant CCR-89-00305, by NIH Library of Medicine Grant ROI LM05118, by AFOSR Grant 90-0107, and by NATO Grant CRG900293.     

Optimal parallel verification of minimum spanning trees in logarithmic time

We present the first optimal parallel algorithms for the verification and sensitivity analysis of minimum spanning trees. Our algorithms are deterministic and run inO(logn) time and require linear-work in the CREW PRAM model. These algorithms are used as a subroutine in the linear-work randomized algorithm for finding minimum spanning trees of Cole, Klein, and Tarjan. Research partially supported by a National Science Foundation Graduate Fellowship and by DIMACS (Center for Discrete Mathematics and Theoretical Computer Science), a National Science Foundation Science and Technology Center, Grant No. NSF-STC88-09648. Research at Princeton University was partially supported by the National Science Foundation, Grant No. CCR-8920505, the Office of Naval Research, Contract No. N00014-91-J-1463, and by DIMACS (Center for Discrete Mathematics and Theoretical Computer Science), a National Science Foundation Science and Technology Center, Grant No. NSF-STC88-09648.     

Ray shooting in polygons using geodesic triangulations

LetP be a simple polygon withn vertices. We present a simple decomposition scheme that partitions the interior ofP intoO(n) so-called geodesic triangles, so that any line segment interior toP crosses at most 2 logn of these triangles. This decomposition can be used to preprocessP in a very simple manner, so that any ray-shooting query can be answered in timeO(logn). The data structure requiresO(n) storage andO(n logn) preprocessing time. By using more sophisticated techniques, we can reduce the preprocessing time toO(n). We also extend our general technique to the case of ray shooting amidstk polygonal obstacles with a total ofn edges, so that a query can be answered inO( logn) time.Work by Bernard Chazelle has been supported by NSF Grant CCR-87-00917. Work by Herbert Edelsbrunner has been supported by NSF Grant CCR-89-21421. Work by Micha Sharir has been supported by ONR Grants N00014-89-J-3042 and N00014-90-J-1284, by NSF Grant CCR-89-01484, and by grants from the U.S.-Israeli Binational Science Foundation, the Fund for Basic Research administered by the Israeli Academy of Sciences, and the G.I.F., the German-Israeli Foundation for Scientific Research and Development.     

An optimal parallel algorithm for planar cycle separators

We present an optimal parallel algorithm for computing a cycle separator of ann-vertex embedded planar undirected graph inO(logn) time onn/logn processors. As a consequence, we also obtain an improved parallel algorithm for constructing a depth-first search tree rooted at any given vertex in a connected planar undirected graph in O(log² n) time on n/logn processors. The best previous algorithms for computing depth-first search trees and cycle separators achieved the same time complexities, but withn processors. Our algorithms run on a parallel random access machine that permits concurrent reads and concurrent writes in its shared memory and allows an arbitrary processor to succeed in case of a write conflict.A preliminary version of this paper appeared as Improved Parallel Depth-First Search in Undirected Planar Graphs in theProceedings of the Third Workshop on Algorithms and Data Structures, 1993, pp. 407–420.Supported in part by NSF Grant CCR-9101385.     

Planar geometric location problems

We present anO(n ² log³ n) algorithm for the two-center problem, in which we are given a setS ofn points in the plane and wish to find two closed disks whose union containsS so that the larger of the two radii is as small as possible. We also give anO(n ² log⁵ n) algorithm for solving the two-line-center problem, where we want to find two strips that coverS whose maximum width is as small as possible. The best previous solutions of both problems requireO(n ³) time.Pankaj Agarwal has been supported by DIMACS (Center for Discrete Mathematics and Theoretical Computer Science), an NSF Science and Technology Center, under Grant STC-88-09648. Micha Sharir has been supported by the Office of Naval Research under Grants N00014-89-J-3042 and N00014-90-J-1284, by the National Science Foundation under Grant CCR-89-01484, by DIMACS, and by grants from the US-Israeli Binational Science Foundation, the Fund for Basic Research administered by the Israeli Academy of Sciences, and the G.I.F., the German-Israeli Foundation for Scientific Research and Development. A preliminary version of this paper has appeared inProceedings of the Second Annual ACM-SIAM Symposium on Discrete Algorithms, 1991, pp. 449–458.     

Efficient parallel algorithms forr-dominating set andp-center problems on trees

We develop efficient parallel algorithms for ther-dominating set and thep-center problems on trees. On a concurrent-read exclusive-write PRAM, our algorithm for ther-dominating set problem runs inO(logn log logn) time withn processors. The algorithm for thep-center problem runs inO(log² n log logn) time withn processors.Xin He was supported in part by an Ohio State University Presidential Fellowship, and by the Office of Research and Graduate Studies of Ohio State University. Yaacov Yesha was supported in part by the National Science Foundation under Grant No. DCR-8606366.     

Data structures and algorithms for the string statistics problem

Given a textstringx of lengthn, theMinimal Augmented Suffix Tree T (x) ofx is a digital-search index that returns, for anyquery stringw and in a number of comparisons bounded by the length ofw, the maximum number of nonoverlapping occurrences ofw inx. It is shown that, denoting the length ofx byn, T(x) can be built in timeO(n log² n) and spaceO(n logn), off-line on a RAM.This research was supported in part, through the Leonardo Fibonacci Institute, by the Istituto Trentino di Cultura, Trento, Italy.Additional support was provided by NSF Grants CCR-8900305 and CCR-9201078, by NATO Grant CRG 900293, by the National Research Council of Italy, and by the ESPRIT III Basic Research Programme of the EC under Contract No. 9072 (Project GEPPCOM).Additional support was provided by NSF Grant CCR-91-96176 and ONR Contract N 00014-91-J-4052, ARPA Order 2225.     

A faster parallel algorithm for a matrix searching problem

We give an improved parallel algorithm for the problem of computing the tube minima of a totally monotonen ×n ×n matrix, an important matrix searching problem that was formalized by Aggarwal and Park and has many applications. Our algorithm runs inO(log logn) time withO(n²/log logn) processors in theCRCW-PRAM model, whereas the previous best ran inO((log logn)²) time withO(n²/(log logn)² processors, also in theCRCW-PRAM model. Thus we improve the speed without any deterioration in thetime ×processors product. Our improved bound immediately translates into improvedCRCW-PRAM bounds for the numerous applications of this problem, including string editing, construction of Huffmann codes and other coding trees, and many other combinatorial and geometric problems.This research was supported by the Office of Naval Research under Grants N00014-84-K-0502 and N00014-86-K-0689, the Air Force Office of Scientific Research under Grant AFOSR-90-0107, the National Science Foundation under Grant DCR-8451393, and the National Library of Medicine under Grant R01-LM05118. Part of the research was done while the author was at Princeton University, visiting the DIMACS center.     

An optimal algorithm for shortest paths on weighted interval and circular-arc graphs,with applications

We give the first linear-time algorithm for computing single-source shortest paths in a weighted interval or circular-arc graph, when we are given the model of that graph, i.e., the actual weighted intervals or circular-arcsand the sorted list of the interval endpoints. Our algorithm solves this problem optimally inO(n) time, wheren is the number of intervals or circular-arcs in a graph. An immediate consequence of our result is anO(qn + n logn)-time algorithm for the minimum-weight circle-cover problem, whereq is the minimum number of arcs crossing any point on the circle; then logn term in this time complexity is from a preprocessing sorting step when the sorted list of endpoints is not given as part of the input. The previously best time bounds were0(n logn) for this shortest paths problem, andO(qn logn) for the minimum-weight circle-cover problem. Thus we improve the bounds of both problems. More importantly, the techniques we give hold the promise of achieving similar (logn)-factor improvements in other problems on such graphs.The research of M. J. Atallah was supported in part by the Leonardo Fibonacci Institute, Trento, Italy, by the Air Force Office of Scientific Research under Contract AFOSR-90-0107, and by the National Science Foundation under Grant CCR-9202807. D. Z. Chen's research was supported in part by the Leonardo Fibonacci Institute, Trento, Italy. The research of D. T. Lee was supported in part by the Leonardo Fibonacci Institute, Trento, Italy, by the National Science Foundation, and the Office of Naval Research under Grants CCR-8901815, CCR-9309743, and N00014-93-1-0272.     

An efficient parallel algorithm for shortest paths in planar layered digraphs

Computing shortest paths in a directed graph has received considerable attention in the sequential RAM model of computation. However, developing a polylog-time parallel algorithm that is close to the sequential optimal in terms of the total work done remains an elusive goal. We present a first step in this direction by giving efficient parallel algorithms for shortest paths in planar layered digraphs.We show that these graphs admit special kinds of separators calledone- way separators which allow the paths in the graph to cross it only once. We use these separators to give divide- and -conquer solutions to the problem of finding the shortest paths between any two vertices. We first give a simple algorithm that works in the CREW model and computes the shortest path between any two vertices in ann-node planar layered digraph in timeO(log² n) usingn/logn processors. We then use results of Aggarwal and Park [1] and Atallah [4] to improve the time bound toO(log² n) in the CREW model andO(logn log logn) in the CREW model. The processor bounds still remain asn/logn for the CREW model andn/log logn for the CRCW model.Support for the first and third authors was provided in part by a National Science Foundation Presidential Young Investigator Award CCR-9047466 with matching funds from IBM, by NSF Research Grant CCR-9007851, by Army Research Office Grant DAAL03-91-G-0035, and by the Office of Naval Research and the Advanced Research Projects Agency under Contract N00014-91-J-4052, ARPA, Order 8225. Support for the second author was provided in part by NSF Research Grant CCR-9007851, by Army Research Office Grant DAAL03-91-G-0035, and by the Office of Naval Research and the Advanced Research Projects Agency under Contract N00014-91-J-4052 and ARPA Order 8225.     

Fast parallel Lyndon factorization with applications

It is shown that the Lyndon decomposition of a word ofn symbols can be computed by ann-processor CRCW PRAM inO(logn) time. Extensions of the basic algorithm convey, within the same time and processors bounds, efficient parallel solutions to problems such as finding the lexicographically minimum or maximum suffix for all prefixes of the input string, and finding the lexicographically least rotation of all prefixes of the input.A. Apostolico's research was supported in part by the French and Italian Ministries of Education, by British Research Council Grant SERC-E76797, by NSF Grants CCR-89-00305 and CCR-9201078, by NIH Library of Medicine Grant R01 LM05118, by AFOSR Grant 89NM682, and by NATO Grant CRG 900293. M. Crochemore's research was supported in part by PRC Mathématiques et Informatique and by NATO Grant CRG 900293.     

An efficient parallel algorithm for finding rectangular duals of plane triangular graphs

We present an efficient parallel algorithm for constructing rectangular duals of plane triangular graphs. This problem finds applications in VLSI design and floor-planning problems. No NC algorithm for solving this problem was previously known. The algorithm takesO(log² n) time withO(n) processors on a CRCW PRAM, wheren is the number of vertices of the graph.This research was supported by NSF Grants CCR-9011214 and CCR-9205982.     

Deterministic parallel list ranking

In this paper we describe a simple parallel algorithm for list ranking. The algorithm is deterministic and runs inO(logn) time on an EREW PRAM withn/logn processors. The algorithm matches the performance of the Cole-Vishkin [CV3] algorithm but is simple and has reasonable constant factors.R. J. Anderson was supported by an NSF Presidential Young Investigator award and G. L. Miller was supported by NSF Grant DCR-85114961.     

Computing shortest transversals

We present anO(nlog² n) time andO(n) space algorithm for computing the shortest line segment that intersects a set ofn given line segments or lines in the plane. If the line segments do not intersect the algorithm may be trimmed to run inO(nlogn) time. Furthermore, in combination with linear programming the algorithm will also find the shortest line segment that intersects a set ofn isothetic rectangles in the plane inO(nlogk) time, wherek is the combinatorial complexity of the space of transversals andk≤4n. These results find application in: (1) line-fitting between a set ofn data ranges where it is desired to obtain the shortestline-of-fit, (2) finding the shortest line segment from which a convexn-vertex polygon is weakly externally visible, and (3) determing the shortestline-of-sight between two edges of a simplen-vertex polygon, for whichO(n) time algorithms are also given. All the algorithms are based on the solution to a new fundamental geometric optimization problem that is of independent interest and should find application in different contexts as well.     

An optimal speed-up parallel algorithm for triangulating simplicial point sets in space

Previous research on developing parallel triangulation algorithms concentrated on triangulating planar point sets.O(log³ n) running time algorithms usingO(n) processors have been developed in Refs. 1 and 2. Atallah and Goodrich⁽³⁾ presented a data structure that can be viewed as a parallel analogue of the sequential plane-sweeping paradigm, which can be used to triangulate a planar point set inO(logn loglogn) time usingO(n) processors. Recently Merks⁽⁴⁾ described an algorithm for triangulating point sets which runs inO(logn) time usingO(n) processors, and is thus optimal. In this paper we develop a parallel algorithm for triangulating simplicial point sets in arbitrary dimensions based on the idea of the sequential algorithm presented in Ref. 5. The algorithm runs inO(log² n) time usingO(n/logn) processors. The algorithm hasO(n logn) as the product of the running time and the number of processors; i.e., an optimal speed-up.