A parallel algorithm to construct a dominance graph on nonoverlapping rectangles

A parallel algorithm to generate the dominance graph on a collection of nonoverlapping iso-oriented rectangles is presented. This graph arises from the constraint graph commonly used in compaction algorithms for VLSI circuits. The dominance graph expresses the notion of aboveness on a collection of nonoverlapping rectangles: it is the directed graph which contains an edge from a rectangleb to rectanglec iffc is immediately aboveb. The algorithm is based on the divide and conquer paradigm; in the EREW PRAM model, it has time complexityO(log² n), usingn/logn processors. Its processor-time product isO(nlogn), which is optimal.     

Shortest noncrossing paths in plane graphs

Let G be an undirected plane graph with nonnegative edge length, and letk terminal pairs lie on two specified face boundaries. This paper presents an algorithm for findingk noncrossing paths inG, each connecting a terminal pair, and whose total length is minimum. Noncrossing paths may share common vertices or edges but do not cross each other in the plane. The algorithm runs in timeO(n logn) wheren is the number of vertices inG andk is an arbitrary integer.     

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 (n/p+log_1+p/n2p).This work was partially supported by NSF Grant CCR-90-14605. D. Breslauer was partially supported by an IBM Graduate Fellowship while studying at Columbia University and by a European Research Consortium for Informatics and Mathematics postdoctoral fellowship.     

Parallel general prefix computations with geometric,algebraic, and other applications

We introduce a generic problem component that captures the most common, difficult kernel of many problems. This kernel involves general prefix computations (GPC). GPC's lower bound complexity of (n logn) time is established, and we give optimal solutions on the sequential model inO(n logn) time, on the CREW PRAM model inO(logn) time, on the BSR (broadcasting with selective reduction) model in constant time, and on mesh-connected computers inO(n) time, all withn processors, plus anO(log² n) time solution on the hypercube model. We show that GPC techniques can be applied to a wide variety of geometric (point set and tree) problems, including triangulation of point sets, two-set dominance counting, ECDF searching, finding two-and three-dimensional maximal points, the reconstruction of trees from their traversals, counting inversions in a permutation, and matching parentheses.work partially supported by NSF IRI/8709726work partially supported by NSERC.     

Parallel integer sorting using small operations

We consider the problem of sortingn integers in the range [0,n ^c -1], wherec is a constant. It has been shown by Rajasekaran and Sen [14] that this problem can be solved optimally inO(logn) steps on an EREW PRAM withO(n) n -bit operations, for any constant >O. Though the number of operations is optimal, each operation is very large. In this paper, we show thatn integers in the range [0,n ^c -1] can be sorted inO(logn) time withO(nlogn)O(1)-bit operations andO(n) O(logn)-bit operations. The model used is a non-standard variant of an EREW PRAMtthat permits processors to have word-sizes ofO(1)-bits and (logn)-bits. Clearly, the speed of the proposed algorithm is optimal. Considering that the input to the problem consists ofO (n logn) bits, the proposed algorithm performs an optimal amount of work, measured at the bit level.This work was partially supported by The Northeast Parallel Architectures Center (NPAC) at Syracuse University, Syracuse, NY 13244 and The Rome Air Development Center, under contract F30602-88-D-0027.     

A faster divide-and-conquer algorithm for constructing delaunay triangulations

An easily implemented modification to the divide-and-conquer algorithm for computing the Delaunay triangulation ofn sites in the plane is presented. The change reduces its (n logn) expected running time toO(n log logn) for a large class of distributions that includes the uniform distribution in the unit square. Experimental evidence presented demonstrates that the modified algorithm performs very well forn2¹⁶, the range of the experiments. It is conjectured that the average number of edges it creates—a good measure of its efficiency—is no more than twice optimal forn less than seven trillion. The improvement is shown to extend to the computation of the Delaunay triangulation in theL _p metric for 1<p.This research was supported by National Science Foundation Grants DCR-8352081 and DCR-8416190.     

Designing broadcasting algorithms in the postal model for message-passing systems

In many distributed-memory parallel computers and high-speed communication networks, the exact structure of the underlying communication network may be ignored. These systems assume that the network creates a complete communication graph between the processors, in which passing messages is associated with communication latencies. In this paper we explore the impact of communication latencies on the design of broadcasting algorithms for fully connected message-passing systems. For this purpose, we introduce thepostal model that incorporates a communication latency parameter 1. This parameter measures the inverse of the ratio between the time it takes an originator of a message to send the message and the time that passes until the recipient of the message receives it. We present an optimal algorithm for broadcasting one message in systems withn processors and communication latency , the running time of which is (( logn)/log( + 1)). For broadcastingm 1 messages, we first examine several generalizations of the algorithm for broadcasting one message and then analyze a family of broadcasting algorithms based on degree-d trees. All the algorithms described in this paper are practical event-driven algorithms that preserve the order of messages.     

Parallel algorithms for routing in nonblocking networks

We construct nonblocking networks that are efficient not only as regards their cost and delay, but also as regards the time and space required to control them. In this paper we present the first simultaneous weakly optimal solutions for the explicit construction of nonblocking networks, the design of algorithms and data-structures. Weakly optimal is in the sense that all measures of complexity (size and depth of the network, time for the algorithm, space for the data-structure, and number of processor-time product) are within one or more logarithmic factors of their smallest possible values. In fact, we construct a scheme in which networks withn inputs andn outputs have sizeO(n(logn)²) and depthO(logn), and we present deterministic and randomized on-line parallel algorithms to establish and abolish routes dynamically in these networks. In particular, the deterministic algorithm usesO((logn)⁵) steps to process any number of transactions in parallel (with one processor per transaction), maintaining a data structure that useO(n(logn)²) words.     

Shallow circuits and concise formulae for multiple addition and multiplication

A theory is developed for the construction of carry-save networks with minimal delay, using a given collection of carry-save adders each of which may receive inputs and produce outputs using several different representation standards.The construction of some new carry-save adders is described. Using these carry-save adders optimally, as prescribed by the above theory, we get {, , }-circuits of depth 3.48 log₂ n and {, , }-circuits of depth 4.95 log₂ n for the carry-save addition ofn numbers of arbitrary length. As a consequence we get multiplication circuits of the same depth. These circuits put out two numbers whose sum is the result of the multiplication. If a single output number is required then the depth of the multiplication circuits increases respectively to 4.48 log₂ n and 5.95 log₂ n.We also get {, , }-formulae of sizeO (n ^3.13) and {, }-formulae of sizeO (n ^4.57) for all the output bits of a carry-save addition ofn numbers. As a consequence we get formulae of the same size for the majority function and many other symmetric Boolean functions.     

Drawings of graphs on surfaces with few crossings

We give drawings of a complete graphK _n withO(n ⁴ log² g/g) many crossings on an orientable or nonorientable surface of genusg 2. We use these drawings ofK _n and give a polynomial-time algorithm for drawing any graph withn vertices andm edges withO(m ² log² g/g) many crossings on an orientable or nonorientable surface of genusg 2. Moreover, we derive lower bounds on the crossing number of any graph on a surface of genusg 0. The number of crossings in the drawings produced by our algorithm are within a multiplicative factor ofO(log² g) from the lower bound (and hence from the optimal) for any graph withm 8n andn ²/m g m/64.The research of the third and the fourth authors was partially supported by Grant No. 2/1138/94 of the Slovak Academy of Sciences and by EC Cooperative action IC1000 Algorithms for Future Technologies (Project ALTEC). A preliminary version of this paper was presented at WG93 and published in Lecture Notes in Computer Science, Vol. 790, 1993, pp. 388–396.     

Scheduling tree dags on parallel architectures

We provide optimal within a constant explicit upper bounds on the makespan of schedules for tree-structured programs on mesh arrays of processors, and provide polynomial-time algorithms to find schedules with makespan matching these bounds. In particular, we show how to find, in polynomial time, a (nonpreemptive) schedule for a binary tree dag withn unit execution time tasks and heighth on ad-dimensional mesh array withm processors and links of unit bandwidth and unit propagation delay whose makespan isO(n/m+n ¹/(d+1)+h), i.e., optimal within a constant factor. Further, we extend these schedules to bounded degree forest dags with arbitrary positive integer execution time tasks and to meshes when the propagation delay of all the links is an arbitrary positive integer. Thus, we provide a polynomial-time approximation algorithm for an NP-hard problem, with a performance ratio that is a constant.We also show how to schedule tree dags on any parallel architecture that satisfies certain natural, not very restrictive, conditions that are satisfied by most parallel architectures used in practice. Let be a fixed positive real number. We provide polynomial time computable schedules for binary tree dags withn unit execution time tasks and heighth (g(n)n ^–,g(n) logn) on any parallel architecture satisfying those conditions, with unit bandwidth and unit propagation delay links, with optimal up to a constant makespanO(g(n)+ft), whereg is a function that depends only on that architecture. The number of processors used is optimal within a constant factor ifh g(n)n ^–, and is optimal within anO(logn) factor ifhg(n)logn. As an example, for hypercube and complete binary tree architectures, we achieve optimal within a constant makespanO(h) whenh=(log² n), using an optimal within anO(logn) factor number of processors. Further, we extend these schedules to the case of bounded-degree forest dags with tasks of arbitrary positive integer execution times and architectures when the propagation delay of all the links is a given arbitrary positive integer.The second author was supported in part by the National Science Foundation under Grant CCR-9106062, and in part by the University of Maryland at College Park, Institute for Advanced Computer Studies.     

A time-optimal parallel algorithm for three-dimensional convex hulls

In this paper we present an O(1/ logn)-time parallel algorithm for computing the convex hull ofn points in ³. This algorithm usesO(@#@ n^1+a) processors on a CREW PRAM, for any constant 0 < 1. So far, all adequately documented parallel algorithms proposed for this problem use time at least O(log² n). In addition, the algorithm presented here is the first parallel algorithm for the three-dimensional convex hull problem that is not based on the serial divide-and-conquer algorithm of Preparata and Hong, whose crucial operation is the merging of the convex hulls of two linearly separated point sets. The contributions of this paper are therefore (i) an O(logn)-time parallel algorithm for the three-dimensional convex hull problem, and (ii) a parallel algorithm for this problem that does not follow the traditional paradigm.This paper was presented in preliminary form at the 9th Annual ACM Symposium on Computational Geometry, San Diego, CA, May 1993 [32]. The work of N. M. Amato was supported in part by an AT&T Bell Laboratories Graduate Fellowship, the Joint Services Electronics Program (U.S. Army, U.S. Navy, U.S. Air Force) under Contract N00014-90-J-1270, and NSF Grant CCR-89-22008. This work was done while N. M. Amato was with the Department of Computer Science at the University of Illinois. The work of F. P. Preparata was supported in part by NSF Grants CCR-91-96152, CCR-91-96176, and ONR Contract N00014-91-J-4052, ARPA order 8225.     

Undirecteds-t connectivity in polynomial time and sublinear space

Thes-t connectivity problem for undirected graphs is to decide whether two designated vertices,s andt, are in the same connected component. This paper presents the first known deterministic algorithms solving undirecteds-t connectivity using sublinear space and polynomial time. Our algorithms provide a nearly smooth time-space tradeoff between depth-first search and Savitch's algorithm. Forn vertex,m edge graphs, the simplest of our algorithms uses spaceO(s),n ^1/2log₂ nsnlog₂ n, and timeO(((m+n)n ² log² n)/s). We give a variant of this method that is faster at the higher end of the space spectrum. For example, with space (nlogn), its time bound isO((m+n)logn), close to the optimal time for the problem. Another generalization uses less space, but more time: spaceO(n ^1/logn), for 2log₂ n, and timen ^O(). For constant the time remains polynomial.     

An efficient parallel algorithm for computing a large independent set in a planar graph

Let (G) denote the independence number of a graphG, that is the maximum number of pairwise independent vertices inG. We present a parallel algorithm that computes in a planar graphG = (V, E), an independent set such that ¦I¦ (G)/2. The algorithm runs in timeOlog² n) and requires a linear number of processors. This is achieved by denning a new set of reductions that can be executed locally and simultaneously; furthermore, it is shown that a constant fraction of the vertices in the graph are reducible. This is the best known approximation scheme when the number of processors available is linear; parallel implementation of known sequential algorithms requires many more processors.Joseph Naor was supported by Contract ONR N00014-88-K-0166. Most of this work was done while he was a post-doctoral fellow at the Department of Computer Science, University of Southern California, Los Angeles, CA 90089-0782, USA.     

A new algorithm for shortest paths among obstacles in the plane

We introduce a new algorithm for computing Euclidean shortest paths in the plane in the presence of polygonal obstacles. In particular, for a given start points, we build a planar subdivision (ashortest path map) that supports efficient queries for shortest paths froms to any destination pointt. The worst-case time complexity of our algorithm isO(kn log² n), wheren is the number of vertices describing the polygonal obstacles, andk is a parameter we call the illumination depth of the obstacle space. Our algorithm usesO(n) space, avoiding the possibly quadratic space complexity of methods that rely on visibility graphs. The quantityk is frequently significantly smaller thann, especially in some of the cases in which the visibility graph has quadratic size. In particular,k is bounded above by the number of different obstacles that touch any shortest path froms.Partially supported by NSF Grants IRI-8710858 and ECSE-8857642 and by a grant from Hughes Research Laboratories, Malibu, CA.     

Optimal randomized parallel algorithms for computational geometry

We present parallel algorithms for some fundamental problems in computational geometry which have a running time ofO(logn) usingn processors, with very high probability (approaching 1 asn ). These include planar-point location, triangulation, and trapezoidal decomposition. We also present optimal algorithms for three-dimensional maxima and two-set dominance counting by an application of integer sorting. Most of these algorithms run on a CREW PRAM model and have optimal processor-time product which improve on the previously best-known algorithms of Atallah and Goodrich [5] for these problems. The crux of these algorithms is a useful data structure which emulates the plane-sweeping paradigm used for sequential algorithms. We extend some of the techniques used by Reischuk [26] and Reif and Valiant [25] for flashsort algorithm to perform divide and conquer in a plane very efficiently leading to the improved performance by our approach.This is a substantially revised version of the paper that appeared as Optimal Randomized Parallel Algorithms for Computational Geometry in theProceedings of the 16th International Conference on Parallel Processing, St. Charles, Illinois, August 1987.This research was supported by DARPA/ARO Contract DAAL03-88-K-0195, Air Force Contract AFOSR-87-0386, DARPA/ISTO Contracts N00014-88-K-0458 and N00014-91-J-1985, and by NASA Subcontract 550-63 of Primecontract NAS5-30428.     

RL \subseteq SC

We show that any randomized logspace algorithm (running in polynomial time with bounded two-sided error) can be simulated deterministically in polynomial time andO(log² n) space. This puts RL in SC, Steve's Class In particular, we get a polynomial time,O(log² n) space algorithm for thest-connectivity problem on undirected graphs.Subject classifications. 68Q10, 68Q15, 68Q25.     

Optimal algorithms for symmetry detection in two and three dimensions

Exact algorithms for detecting all rotational and involutional symmetries in point sets, polygons and polyhedra are described. The time complexities of the algorithms are shown to be (n) for polygons and (n logn) for two- and three-dimensional point sets. (n logn) time is also required for general polyhedra, but for polyhedra with connected, planar surface graphs (n) time can be achieved. All algorithms are optimal in time complexity, within constants.     

The expected additive weight of trees

Summary We consider a general additive weight of random trees which depends on the structure of the subtrees, on weight functions defined on the number of internal and external nodes and on the degrees of the nodes appearing in the tree and its subtrees. Choosing particular weight functions, the corresponding weight is an important parameter appearing in the analysis of sorting and searching algorithms. For a simply generated family of rooted planar trees , we shall derive a general approach to the computation of the average weight of a tree T with n nodes and m leaves for arbitrary weight functions. This general result implies exact and asymptotic expressions for many types of average weights of a tree T with n nodes if the weight functions are arbitrary polynomials in the number of nodes and leaves with coefficients depending on the node degrees.