This paper presents a new, simpler ALOGTIME algorithm for the Boolean sentence value problem (BSVP). Unlike prior work, this algorithm avoids the use of postfix-longer-operand-first formulas. This paper also shows that tree-contraction can be made ALOGTIME uniform.

We consider a new class of routing requests or partial permutations for which we give optimal on-line routing algorithms on the hypercube and shuffle-exchange network. For well-formed words of parentheses our algorithm establishes communication between all matching pairs in logarithmic time. It can be applied to the membership problem for Dyck languages and a number of problems for algebraic expressions.

We present optimal algorithms for sorting on parallel CREW and EREW versions of the pointer machine model. Intuitively, one can view our methods as being based on a parallel mergesort using linked lists rather than arrays (the usual parallel data structure). We also show how to exploit the "locality" of our approach to solve the set expression evaluation problem, a problem with applications to database querying and logic-programming, in O(log n) time using O(n) processors. Interestingly, this is an asymptotic improvement over what seems possible using previous techniques. Categories and Subject Descriptors: E.1 [Data Structures]: arrays, lists; F.2.2. [Analysis of Algorithms and Problem Complexity]: Nonnumerical Algorithms and Problems---sorting and searching General Terms: Algorithms, Theory, Verification Additional Key Words and Phrases: parallel algorithms, PRAM, pointer machine, linking automaton, expression evaluation, mergesort, cascade merging 1 Introduction One of the primar...

We develop a linear time algorithm for the following problem: Given a graph G and a hierarchical clustering of the vertices, such that all clusters induce connected subgraphs, determine whether G can be embedded into the plane, such that no cluster has a hole. This is an improvement to the O(n 2 )-algorithm of Q.W. Feng et al. [6] and the algorithm of Lengauer [12].

This paper explores the parallel complexity of finite constraint satisfaction problems (FCSPs) by developing three algorithms for deriving minimal constraint networks in parallel. The first is a parallel algorithm for the EREW PRAM model, the second is a distributed algorithm for fine-grain interconnected networks, and the third is a distributed algorithm for coarse-grain interconnected networks. Our major results are: given an FCSP represented by an acyclic constraint network (or a join tree) of size n with treewidth bounded by a constant, then (1) the parallel algorithm takes O(log n) time using O(n) processors, (2) there is an equivalent network, of size poly(n) with treewidth also bounded by a constant, which can be solved by the fine-grain distributed algorithm in O(log n) time using poly(n) processors and (3) the distributed algorithm for coarse-grain interconnected networks has linear speedup and linear scaleup. In addition, we have simulated the fine-grain distributed algorit...

A survey of techniques for solving geometric problems in parallel is given, both for shared memory parallel machines and for networks of processors. Open problems are also discussed, as well as directions for future research. 'This work was supported by the office oi Naval Research under Contracts N00014-84-K-0502 and

The first half of the paper is a general introduction which emphasizes the central role that the PRAM model of parallel computation plays in algorithmic studies for parallel computers. Some of the collective knowledge-base on non-numerical parallel algorithms can be characterized in a structural way. Each structure relates a few problems and technique to one another from the basic to the more involved. The second half of the paper provides a bird's-eye view of such structures for: (1) list, tree and graph parallel algorithms; (2) very fast deterministic parallel algorithms; and (3) very fast randomized parallel algorithms. 1 Introduction Parallelism is a concern that is missing from "traditional" algorithmic design. Unfortunately, it turns out that most efficient serial algorithms become rather inefficient parallel algorithms. The experience is that the design of parallel algorithms requires new paradigms and techniques, offering an exciting intellectual challenge. We note that it had...

Abstract—The Fibonacci Cube is an interconnection network that possesses many desirable properties that are important in network design and application. The Fibonacci Cube can efficiently emulate many hypercube algorithms and uses fewer links than the comparable hypercube, while its size does not increase as fast as the hypercube. However, most Fibonacci Cubes (more than 2/3 of all) are not Hamiltonian. In this paper, we propose an Extended Fibonacci Cube (EFC 1) with an even number of nodes. It is defined based on the same sequence F(i) = F(i- 1) + F(i- 2) as the regular Fibonacci sequence; however, its initial conditions are different. We show that the Extended Fibonacci Cube includes the Fibonacci Cube as a subgraph and maintains its sparsity property. In addition, it is Hamiltonian and is better in emulating other topologies. Specifically, the Extended Fibonacci Cube can embed binary trees more efficiently than the regular Fibonacci Cube and is almost as efficient as the hypercube, even though the Extended Fibonacci Cube is a much sparser network than the hypercube. We also propose a series of Extended Fibonacci Cubes with even number of nodes. Any Extended Fibonacci Cube (EFC k, with k ≥ 1) in the series contains the node set of any other cube that precedes EFC k in the series. We show that any Extended Fibonacci Cube maintains virtually all the desirable properties of the Fibonacci Cube. The EFC k s can be considered as flexible versions of incomplete hypercubes, which eliminates their restriction on the number of nodes, and, thus, makes it possible to construct parallel machines with arbitrary sizes. Index Terms—Fibonacci numbers, Hamiltonian graphs, graph embedding, hypercubes, interconnection topologies.

With the increasing popularity of parallel programming environments such as PC clusters, more and more sequential programmers, with little knowledge about parallel architectures and parallel programming, are hoping to write parallel programs. Numerous attempts have been made to develop high-level parallel programming libraries that use abstraction to hide low-level concerns and reduce difficulties in parallel programming. Among them, libraries of parallel skeletons have emerged as a promising way towards this direction. Unfortunately, these libraries are not well accepted by sequential programmers, because of incomplete elimination of lower-level details, ad-hoc selection of library functions, unsatisfactory performance, or lack of convincing application examples. This paper addresses principle of designing skeleton libraries of parallel programming and reports implementation details and practical applications of a skeleton library SkeTo. The SkeTo library is unique in its feature that it has a solid theoretical foundation based on the theory of Constructive Algorithmics, and is practical to be used to describe various parallel computations in a sequential manner. 1.

Parallel primitives (skeletons) intend to encourage programmers to build a parallel program from ready-made components for which efficient implementations are known to exist, making the parallelization process easier. However, programmers often suffer from the difficulty to choose a combination of proper parallel primitives so as to construct efficient parallel programs. To overcome this difficulty, we shall propose a new transformation, called diffusion, which can efficiently decompose a recursive definition into several functions such that each function can be described by some parallel primitive. This allows programmers to describe algorithms in a more natural recursive form. We demonstrate our idea with several interesting examples. Our diffusion transformation should be significant not only in development of new parallel algorithms, but also in construction of parallelizing compilers.