Multi-scale modeling, the simulation of coupled physicalprocesses that occur on different temporal or spatialscales, is becoming an increasingly important area ofresearch in computational *** such problems can be comp...
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Multi-scale modeling, the simulation of coupled physicalprocesses that occur on different temporal or spatialscales, is becoming an increasingly important area ofresearch in computational *** such problems can be computationally intensive;however, because of the increasing availability of large computationalresources, their solution can be *** important multi-scale application is the numericalsimulation of *** combustion, three different physical processes governthe dynamics of the problem: fluid flow (which can beturbulent or laminar), chemical reactions, and heat transfer,with radiative heat transfer being a dominant *** objective of this thesis is to createefficient sequential and parallel algorithms andsoftware that improve accuracy and performance ofcombustion *** purpose of this work is to create clean, easy-to-usesoftware interfaces that can be readily used from both C/C++ and FORTRANapplications without significant changes to the original *** this thesis, we introduce two new software systems thatenable modeling of multi-scale phenomena in combustion applicationson single processor and distributed memory multiprocessorsystems and improve their accuracy and *** first system is called the Database On-Line forEfficient Function Approximation (DOLFA) for speeding upchemistry calculations in combustion applications.A second system, called Photon Monte Carlo (PMC),is used for solving the Radiative Transfer Equation (RTE)by calculating the radiative heat fluxes for the volume elementsof a computational *** PMC software system is capable of handling computational domains withcomplex enclosures and various radiation configurations.
The longest common subsequence problem is to find a substring that is common to two given strings and is at least as long as any other such string. If m and n are the lengths of the two strings (m&len), we obtain ...
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The longest common subsequence problem is to find a substring that is common to two given strings and is at least as long as any other such string. If m and n are the lengths of the two strings (m&len), we obtain O(log m) time parallel algorithm with mn processors and an O(log2 n) time optimal parallel algorithm. Serial complexity on decision tree model is Θ(mn).
The circuit value update problem is the problem of updating values in a representation of a combinational circuit when some of the inputs are changed. We assume for simplicity that each combinatorial element has bound...
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ISBN:
(纸本)9780897917179
The circuit value update problem is the problem of updating values in a representation of a combinational circuit when some of the inputs are changed. We assume for simplicity that each combinatorial element has bounded fan-in and fan-out and can be evaluated in constant time. This problem is easily solved on an ordinary serial computer in O(W + D) time, where W is the number of elements in the altered subcircuit and D is the subcircuit's embedded depth (its depth measured in the original circuit). In this paper, we show how to solve the circuit value update problem efficiently on a P-processor parallel computer. We give a straightforward synchronous, parallel algorithm that runs in O(W/P + D lg P) expected time. Our main contribution, however, is an optimistic, asynchronous, parallel algorithm that runs in O(W/P + D + lg W + lg P) expected time, where W and D are the size and embedded depth, respectively, of the 'volatile' subcircuit, the subcircuit of elements that have inputs which either change or glitch as a result of the update. To our knowledge, our analysis provides the first analytical bounds on the running time of an optimistic algorithm.
Using an exclusive-read and exclusive-write (EREW) parallel random-access memory (PRAM) model with a fixed number of processors, optimal parallel algorithms are presented for several problems on undirected graphs. The...
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Using an exclusive-read and exclusive-write (EREW) parallel random-access memory (PRAM) model with a fixed number of processors, optimal parallel algorithms are presented for several problems on undirected graphs. These problems include finding the connected components, a spanning forest, a fundamental cycle set, the bridges, and checking bipartiteness of a given graph. The algorithms for computing the connected components and a spanning forest are designed using the divide-and-conquer strategy and are used in turn to design efficient algorithms for the remaining three problems. Each of the algorithms achieves optimal speedup for dense as well as sparse graphs, and is optimally scalable up to a certain number of processors. A lower bound on the processor-(time)/sup 2/ product for each algorithm is derived. The input graph is represented by an unordered list of edges, and the use of simple and elegant data structures avoids memory read-conflicts or write-conflicts.< >
The problem of exactly summing n floating-point numbers is a fundamental problem that has many applications in large-scale simulations and computational geometry. Unfortunately, due to the round-off error in standard ...
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ISBN:
(纸本)9781450342100
The problem of exactly summing n floating-point numbers is a fundamental problem that has many applications in large-scale simulations and computational geometry. Unfortunately, due to the round-off error in standard floatingpoint operations, this problem becomes very challenging. Moreover, all existing solutions rely on sequential algorithms which cannot scale to the huge datasets that need to be processed. In this paper, we provide several efficient parallel algorithms for summing n floating point numbers, so as to produce a faithfully rounded floating-point representation of the sum. We present algorithms in PRAM, external-memory, and MapReduce models, and we also provide an experimental analysis of our MapReduce algorithms, due to their simplicity and practical efficiency.
We consider two difference schemes that describe the convective-diffusion transfer and settling of multifractional suspensions in coastal systems. The first is based on an explicit-implicit scheme with reduced cost of...
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Networks (or graphs) are an effective abstraction for representing many real-world complex systems. Analyzing various structural properties of and dynamics on such networks reveal valuable insights about the behavior ...
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Networks (or graphs) are an effective abstraction for representing many real-world complex systems. Analyzing various structural properties of and dynamics on such networks reveal valuable insights about the behavior of such systems. In today's data-rich world, we are deluged by the massive amount of heterogeneous data from various sources, such as the web, infrastructure, and online social media. Analyzing this huge amount of data may take a prohibitively long time and even may not fit into the main memory of a single processing unit, thus motivating the necessity of efficient parallel algorithms in various high-performance computing (HPC) platforms. In this dissertation, we present distributed and shared memory parallel algorithms for some important network analytic problems. First, we present distributed memory parallel algorithms for switching edges in a network. Edge switch is an operation on a network, where two edges are selected randomly, and one of their end vertices are swapped with each other. This operation is repeated either a given number of times or until a specified criterion is satisfied. It has diverse real-world applications such as in generating simple random networks with a given degree sequence and in modeling and studying various dynamic networks. One of the steps in our edge switch algorithm requires generating multinomial random variables in parallel. We also present the first non-trivial parallel algorithm for generating multinomial random variables. Next, we present efficient algorithms for assortative edge switch in a labeled network. Assuming each vertex has a label, an assortative edge switch operation imposes an extra constraint, i. e., two edges are randomly selected and one of their end vertices are swapped with each other if the labels of the end vertices of the edges remain the same as before. It can be used to study the effect of the network structural properties on dynamics over a network. Although the problem of assortative edge
In this paper a two year project whose principal goal is the development and implementation of efficient parallel algorithms for the computation of subsets of eigenvalues and associated eigenvectors of large, usually ...
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This paper presents efficient and portable implementations of two useful primitives in image processing algorithms, histogramming and connected components. Our general framework is a single-address space, distributed ...
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This paper presents efficient and portable implementations of two useful primitives in image processing algorithms, histogramming and connected components. Our general framework is a single-address space, distributed memory programming model. We use efficient techniques for distributing and coalescing data as well as efficient combinations of task and data parallelism. Our connected components algorithm uses a novel approach for parallel merging which performs drastically limited updating during iterative steps, and concludes with a total consistency update at the final step. The algorithms have been coded in Split-C and run on a variety of platforms. Our experimental results are consistent with the theoretical analysis and provide the best known execution times for these two primitives, even when compared with machine-specific implementations. More efficient implementations of Split-C will likely result in even faster execution times.
In the paper the new approach to design parallel algorithms for the modelling of the multi-scale non-stationary processes is proposed. Our technique is based on the explicit multi-level difference schemes with the loc...
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