parallel programs are described as action systems. These are basically nondeterministic do-od programs that can be executed in both a sequential and a parallel fashion. A method for refining the atomicity of actions i...
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We present sequential and parallel algorithms for various embedding problems on bounded degree partial k-trees and k-connected partial k-trees;these include subgraph isomorphism and topological embedding, known to be ...
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We present parallel algorithms for several graph and geometric problems, including transitive closure and topological sorting in planar st-graphs, preprocessing planar subdivisions for point location queries, and cons...
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Smith normal form computation has many applications in group theory, module theory and number theory. As the entries of the matrix and of its corresponding transformation matrices can explode during the computation, i...
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The key operation to obtain stationary and transient solutions of transition systems described by Kronecker structured formalisms is the Vector-Descriptor product. This operation is usually performed with shuffling op...
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A common statistical problem is that of finding the median element in a set of data. This paper presents a fast and portable parallel algorithm for finding the median given a set of elements distributed across a paral...
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A common statistical problem is that of finding the median element in a set of data. This paper presents a fast and portable parallel algorithm for finding the median given a set of elements distributed across a parallel machine. In fact, our algorithm solves the general selection problem that requires the determination of the element of rank i, for an arbitrarily given integer i. Practical algorithms needed by our selection algorithm for the dynamic redistribution of data are also discussed. Our general framework is a distributed memory programming model enhanced by a set of communication primitives. We use efficient techniques for distributing, coalescing, and load balancing data as well as efficient combinations of task and data parallelism. The algorithms have been coded in Split-C and run on a variety of platforms, including the Thinking Machines CM-5, IBM SP-1 and SP-2, Cray Research T3D, Meiko Scientific CS-2, Intel Paragon, and workstation clusters. Our experimental results illustrate the scalability and efficiency of our algorithms across different platforms and improve upon all the related experimental results known to the authors.
The star graph is an attractive alternative to the hypercube for interconnecting processors in a parallel computer. Since its proposal, many parallel algorithms have been designed to run on this topology. However, mos...
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The problem of obtaining blocks of operations and threads of parallel algorithm resulting in a smaller number of accesses to global memory and resulting in the efficient use of caches and shared memory graphics proces...
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The problem of obtaining blocks of operations and threads of parallel algorithm resulting in a smaller number of accesses to global memory and resulting in the efficient use of caches and shared memory graphics processor is investigated. We formulated and proved statements to assess the volume of communication transactions generated by alternative sizing of blocks, as well as to minimize the number of cache misses due to the use of temporal and spatial locality of data. The research is constructive and allows software implementation for practical use.
For many years, computer scientists have explored the computing power of so-called computing clusters to address performance requirements of computationally intensive tasks. Historically, computing clusters have been ...
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In this paper we give parallel algorithms for a number of problems defined on polygons and point sets. All of our algorithms have optimal T(n) ∗ P(n) products, where T(n) is the time complexity and P(n) is the number ...
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