Selection on rectangular meshes with multiple broadcasting

One of the fundamental algorithmic problems in computer science involves selecting thekth smallest element in a setS ofn elements. In this paper we present a fast selection algorithm which runs inO(n ^1/8 logn) time on a mesh with multiple broadcasting of sizen ^3/8 ×n ^5/8. Our result shows that, just like semigroup computations, selection can be done much faster on a suitably chosen rectangular mesh than on square meshes. We also show that if every processor can storen ^1/9 items, then our selection algorithm runs inO(n ^1/9 logn) time on a mesh with multiple broadcasting of sizen ^1/3 ×n ^5/9.Work supported by NASA under grant NCC1-99.This author was partly supported by NSF grant CCR-8009996.     

Applications of random sampling in computational geometry,II

We use random sampling for several new geometric algorithms. The algorithms are Las Vegas, and their expected bounds are with respect to the random behavior of the algorithms. These algorithms follow from new general results giving sharp bounds for the use of random subsets in geometric algorithms. These bounds show that random subsets can be used optimally for divide-and-conquer, and also give bounds for a simple, general technique for building geometric structures incrementally. One new algorithm reports all the intersecting pairs of a set of line segments in the plane, and requiresO(A+n logn) expected time, whereA is the number of intersecting pairs reported. The algorithm requiresO(n) space in the worst case. Another algorithm computes the convex hull ofn points inE ^d inO(n logn) expected time ford=3, andO(n ^[d/2]) expected time ford>3. The algorithm also gives fast expected times for random input points. Another algorithm computes the diameter of a set ofn points inE ³ inO(n logn) expected time, and on the way computes the intersection ofn unit balls inE ³. We show thatO(n logA) expected time suffices to compute the convex hull ofn points inE ³, whereA is the number of input points on the surface of the hull. Algorithms for halfspace range reporting are also given. In addition, we give asymptotically tight bounds for (k)-sets, which are certain halfspace partitions of point sets, and give a simple proof of Lee's bounds for high-order Voronoi diagrams.     

An optimal convex hull algorithm in any fixed dimension

We present a deterministic algorithm for computing the convex hull ofn points inE ^d in optimalO(n logn+n ^⌞d/2⌟ ) time. Optimal solutions were previously known only in even dimension and in dimension 3. A by-product of our result is an algorithm for computing the Voronoi diagram ofn points ind-space in optimalO(n logn+n ^⌜d/2⌝ ) time. This research was supported in part by the National Science Foundation under Grant CCR-9002352 and The Geometry Center, University of Minnesota, an STC funded by NSF, DOE, and Minnesota Technology, Inc. A preliminary version of this paper has appeared in “An optimal convex hull algorithm and new results on cuttings”,Proceedings of the 32nd Annual IEEE Symposium on the Foundations of Computer Science, October 1991, pp. 29–38. The convex hull algorithm given in the present paper, although similar in spirit, is considerably simpler than the one given in the proceedings.     

A constant-time channel-assignment algorithm on reconfigurable meshes

The channel-assignment problem is central to the integrated circuit fabrication process. Given a two-sided printed circuit board, we wish to maken pairs of components electrically equivalent. The connections are made using two vertical runs along with a horizontal one. Each horizontal run lies in a channel. The channel-assignment problem involves minimizing the total number of channels used.Recent advances in VLSI have made it possible to build massively parallel machines. To overcome the inefficiency of long distance communications among processors, some parallel architectures have been augmented by bus systems. If such a bus system can be dynamically changed to suit communication needs among processors, it is referred to asreconfigurable. The reconfigurable mesh is one of the practical models featuring a reconfigurable bus system. In this paper, we propose a constant-time algorithm to solve the channel-assignment problem of sizen on a reconfigurable mesh of sizen×n.This work was supported by NASA under grant NCC1-99.Additional support by the National Science Foundation under grant CCR-8909996 is gratefully acknowledged.     

Applications of a semi-dynamic convex hull algorithm

We obtain new results for manipulating and searching semi-dynamic planar convex hulls (subject to deletions only), and apply them to derive improved bounds for two problems in geometry and scheduling. The new convex hull results are logarithmic time bounds for set splitting and for finding a tangent when the two convex hulls are not linearly separated. Using these results, we solve the following two problems optimally inO(n logn) time: (1) [matching] givenn red points andn blue points in the plane, find a matching of red and blue points (by line segments) in which no two edges cross, and (2) [scheduling] givenn jobs with due dates, linear penalties for late completion, and a single machine on which to process them, find a schedule of jobs that minimizes the maximum penalty.     

A sublogarithmic convex hull algorithm

We present a parallel algorithm for finding the convex hull of a sorted set of points in the plane. Our algorithm runs inO(logn/log logn) time usingO(n log logn/logn) processors in theCommon crcw pram computational model, which is shown to be time and cost optimal. The algorithm is based onn ^1/3 divide-and-conquer and uses a simple pointer-based data structure.Part of this work was done when the last three authors were at the Department of Computer and Information Science, Linköping University. The research of the second author was supported by the Academy of Finland.     

Reconstructing visible regions from visible segments

An algorithm is presented for reconstructing visible regions from visible edge segments in object space. This has applications in hidden surface algorithms operating on polyhedral scenes and in cartography. A special case of reconstruction can be formulated as a graph problem: Determine the faces of a straight-edge planar graph given in terms of its edges. This is accomplished inO(n logn) time using linear space for a graph withn edges, and is worst-case optimal. The graph may have separate components but the components must not contain each other. The general problem of reconstruction is then solved by applying our algorithm to each component in the containment relation.Research of this author is supported by the National Science Foundation under grant no. ECS-8351942, and by the Schlumberger-Doll Research Labs, Ridgefield, Connecticut.     

A pivoting algorithm for convex hulls and vertex enumeration of arrangements and polyhedra

We present a new pivot-based algorithm which can be used with minor modification for the enumeration of the facets of the convex hull of a set of points, or for the enumeration of the vertices of an arrangement or of a convex polyhedron, in arbitrary dimension. The algorithm has the following properties:

Off-Line Maintenance of Planar Configurations

We achieve anO(log n) amortized time bound per operation for the off-line version of the dynamic convex hull problem in the plane. In this problem, a sequence ofninsert,delete, andqueryinstructions are to be processed, where each insert instruction adds a new point to the set, each delete instruction removes an existing point, and each query requests a standard convex hull search. We process the entire sequence in totalO(n log n) time andO(n) space. Alternatively, we can preprocess a sequence ofninsertions and deletions inO(n log n) time and space, then answer queries in history inO(log n) time apiece (a query in history means a query comes with a time parametert, and it must be answered with respect to the convex hull present at timet). The same bounds also hold for the off-line maintenance of several related structures, such as the maximal vectors, the intersection of half-planes, and the kernel of a polygon. Achieving anO(log n) per-operation time bound for theon-lineversions of these problems is a longstanding open problem in computational geometry.     

An efficient and numerically correct algorithm for the 2D convex hull problem

An efficient and numerically correct program called FastHull for computing the convex hulls of finite point sets in the plane is presented. It is based on the Akl-Toussaint algorithm and the MergeHull algorithm. Numerical correctness of the FastHull procedure is ensured by using special routines for interval arithmetic and multiple precision arithmetic. The FastHull algorithm guaranteesO(N logN) running time in the worst case and has linear time performance for many kinds of input patterns. It appears that the FastHull algorithm runs faster than any currently known 2D convex hull algorithm for many input point patterns.     

On the performance of peeling algorithms

The peeling of a d-dimensional set of points is usually performed with successive calls to a convex hull algorithm; the optimal worst-case convex hull algorithm, known to have an O(n^˙ Log (n)) execution time, may give an O(n^˙n^˙ Log (n)) to peel all the set; an O(n^˙n) convex hull algorithm, m being the number of extremal points, is shown to peel every set with an O(n-n) time, and proved to be optimal; an implementation of this algorithm is given for planar sets and spatial sets, but the latter give only an approximate O(n^˙n) performance.     

Searchability in merging and implicit data structures

We introduce the notion ofsearchability as a property of an in place merging algorithm. We show that a pair of sorted arrays can be merged in place in linear time, so that a search can be performed in logarithmic time at any point during the merging process. We apply this method to devise an implicit data structure which can support searches inO(log² n) time in the worst case, andO(logn) on the average, and insertions inO(logn) time, in the worst case.This research was partly supported by NSERC under grant A8237 and presented in preliminary form at the 10th International Colloquium on Automata, Languages and Programming.On leave from the University of Chile.     

Optimal output-sensitive convex hull algorithms in two and three dimensions

We present simple output-sensitive algorithms that construct the convex hull of a set ofn points in two or three dimensions in worst-case optimalO (n logh) time andO (n) space, whereh denotes the number of vertices of the convex hull. This research was supported by a Killam Predoctoral Fellowship and an NSERC Postgraduate Scholarship.     

Finding minimal nested polygons

An algorithm for finding a polygon with minimum number of edges nested in two simplen-sided polygons is presented. The algorithm solves the problem in at mostO(n logn) time, and improves the time complexity of two previousO(n ²) algorithms.The work was supported by NSERC grant OPG0041629.     

A note on optimal multiway split trees

Split trees are suitable data structures for storing records with different access frequencies. Under assumption that the access frequencies are all distinct, Huang has proposed anO(n ⁴ logm) time algorithm to construct an (m+1)-way split tree for a set ofn keys. In this paper, we generalize Huang's algorithm to deal with the case of non-distinct access frequencies. The technique used in the generalized algorithm is a generalization of Hesteret al.'s, where the binary case was considered. The generalized algorithm runs inO(n ⁵ logm) time.     

Computing minimum-area rectilinear convex hull and L-shape

We study the problems of computing two non-convex enclosing shapes with the minimum area; the L-shape and the rectilinear convex hull. Given a set of n points in the plane, we find an L-shape enclosing the points or a rectilinear convex hull of the point set with minimum area over all orientations. We show that the minimum enclosing shapes for fixed orientations change combinatorially at most O(n) times while rotating the coordinate system. Based on this, we propose efficient algorithms that compute both shapes with the minimum area over all orientations. The algorithms provide an efficient way of maintaining the set of extremal points, or the staircase, while rotating the coordinate system, and compute both minimum enclosing shapes in O(n²) time and O(n) space. We also show that the time complexity of maintaining the staircase can be improved if we use more space.     

Discrete fourier transform computation using prime Ramanujan numbers

Ramanujan numbers were introduced in [2] to implement discrete fourier transform (DFT) without using any multiplication operation. Ramanujan numbers are related to π and integers which are powers of 2. If the transform sizeN, is a Ramanujan number, then the computational complexity of the algorithms used for computing isO(N ²) addition and shift operations, and no multiplications. In these algorithms, the transform can be computed sequentially with a single adder inO(N ²) addition times. Parallel implementation of the algorithm can be executed inO(N) addition times, withO(N) number of adders. Some of these Ramanujan numbers of order-2 are related to the Biblical and Babylonian values of π [1]. In this paper, we analytically obtain upper bounds on the degree of approximation in the computation of DFT if JV is a prime Ramanujan number.     

Optimal parallel quicksort on EREW PRAM

In this paper, we present parallel quicksort algorithms running inO((n/p+logp) logn) expected time andO((n/p+logp+log logn) logn) deterministic time respectively, and both withO(n) space by usingp processors on EREW PRAM. Whenp=O(n/logn), the cost is optimal, in terms of the product of time and number of processors. These algorithms can be used to obtain parallel algorithms for constructing balanced binary search trees without using sorting algorithms. One of our quicksort algorithms leads to a parallel quickhull algorithm on EREW PRAM.The work of this author was partially supported by a fellowship from the College of Science, Old Dominion University, Norfolk, VA 23529, USA.     

AVLSI partition algorithm

A VLSI sorter of sizeO(n) can sortn elements in linear time when the input and output time are taken into account. If the input contains more thann elements, some prepocessing has to be performed. A VLSI partition algorithm that provides a solution to this problem is presented. The algorithm partitions the input data into two smaller parts as the quicksort algorithm does. That is, the elements of the first part will be smaller than the elements of the second part. The partition is repeated until the parts are small enough to fit in the sorter. It is shown that the average number of times each element must go through the partitioner isO(logk) for a data file of sizekn wheren is the size of the sorter. In the worst case where the partitioner fails to divide the input evenly, the elements must goO(k) times through the partitioner like in the quicksort algorithm. The partitioner can also be used, with simple modifications, as a sorter, a stack, a queue, or as a priority queue. Other advantages of the VLSI algorithm are also discussed.     

Steiner minimal trees for three points with one convex polygonal obstacle

The problem of constructing Steiner minimal trees in the Euclidean plane is NP-hard. When in addition obstacles are present, difficulties of constructing obstacle-avoiding Steiner minimal trees are compounded. This problem, which has many obvious practical applications when designing complex transportation and distribution systems, has received very little attention in the literature. The construction of Steiner minimal trees for three terminal points in the Euclidean plane (without obstacles) has been completely solved (among others by Fermat, Torricelli, Cavallieri, Simpson, Heinen) during the span of the last three centuries. This construction is a cornerstone for both exact algorithms and heuristics for the Euclidean Steiner tree problem with arbitrarily many terminal points. An algorithm for three terminal points in the presence of one polygonal convex obstacle is given. It is shown that this algorithm has the worst-case time complexityO(n), wheren is the number of extreme points on the obstacle. As an extension to the underlying algorithm, if the obstacle is appropriately preprocessed inO(n) time, we can solve any problem instance with three arbitrary terminal points and the preprocessed convex polygonal obstacle inO(logn) time. We believe that the three terminal points algorithm will play a critical role in the development of heuristics for problem instances with arbitrarily many terminal points and obstacles.