36878064
A Compact Storage Scheme for Fast Wavelet-Based Subregion Retrieval
In an image browsing environment there is need for progressively viewing image subregions at various resolutions. We describe a storage scheme that accomplishes good image compression, while supporting fast image subregion retrieval. We evaluate analytically and experimentally the compression performance of our algorithm. We also provide results on the speed of the algorithm to demonstrate its effectiveness, and present an extension to a client/server environment.
16971481
Image compression for fast wavelet-based subregion retrieval
In an image browsing environment there is need for progressively viewing image subregions at various resolutions. We describe a storage scheme that accomplishes good image compression, while supporting fast image subregion retrieval. We evaluate analytically and experimentally the compression performance of our algorithm. We also provide results on the speed of the algorithm to demonstrate its effectiveness, and present an extension to a client/server environment.
8870978
Monte Carlo Techniques for Estimating the Fiedler Vector in Graph Applications
Determiningthe Fiedler vector of the Laplacian or adjacency matrices of graphs is the most computationally intensive component of several applications, such as graph partitioning, graph coloring, envelope reduction, and seriation. Often an approximation of the Fiedler vector is sufficient.We discuss issues involved in the use of Monte Carlo techniques for this purpose.
17105049
Data-Driven Time-Parallelization in the AFM Simulation of Proteins
Molecular dynamics is a popular technique to simulate the behavior of physical systems, with resolution at the atomic scale. One of its limitations is that an enormous computational effort is required to simulate to realistic time spans. Conventional parallelization strategies have limited effectiveness in dealing with this difficulty. We recently introduced a more scalable approach to parallelization, where data from prior, related, simulations are used to parallelize a simulation in the time domain. We demonstrated its effectiveness in nano-mechanics simulations. In this paper, we develop our approach so that it can be used in a soft-matter application involving the atomic force microscopy simulation of proteins. We obtain an order of magnitude improvement in performance when we combine time parallelization with conventional parallelization. The significance of this work lies in demonstrating the promise of data-driven time parallelization in soft-matter applications, which are more challenging than the hard-matter applications considered earlier.
10702922
Improved Algorithms via Approximations of Probability Distributions
We present two techniques for constructing sample spaces that approximate probability distributions. The first is a simple method for constructing the small-bias probability spaces introduced by Naor and Naor. We show how to efficiently combine this construction with the method of conditional probabilities to yield improved parallel algorithms for problems such as set discrepancy, finding large cuts in graphs, and finding large acyclic subgraphs. The second is a construction of small probability spaces approximating general independent distributions which are of smaller size than the constructions of Even, Goldreich, Luby, Nisan, and Veli?kovi?.
5089320
Better approximation guarantees for job-shop scheduling
Job-shop scheduling is a classical NP-hard problem. Shmoys, Stein, and Wein presented the first polynomial-time approximation algorithm for this problem that has a good (polylogarithmic) approximation guarantee. We improve the approximation guarantee of their work and present further improvements for some important NP-hard special cases of this problem (e.g., in the preemptive case where machines can suspend work on operations and later resume). We also present NC algorithms with improved approximation guarantees for some NP-hard special cases.
10183251
Approximating low-congestion routing and column-restricted packing problems
Abstract We contribute to a body of research asserting that the fractional and integral optima of column-sparse integer programs are “nearby”. This yields improved approximation algorithms for some generalizations of the knapsack problem, with applications to low-congestion routing in networks, file replication in distributed databases, and other packing problems.
150268
Integrating a periodic and recurrent tasks on fair-scheduled multiprocessors
We propose two server implementations for multiplexing aperiodic and recurrent real-time tasks in fair-scheduled multiprocessor systems. We also provide admission-control tests for scheduling hard aperiodic tasks. Further, we consider several complexities, most of which arise because of the parallelism available in multiprocessor systems, and present techniques to handle them. Finally, we present experimental results that demonstrate the effectiveness of our implementations.
2380498
Improved bounds and algorithms for hypergraph two-coloring
We show that for all large n, every n-uniform hypergraph with at most 0.7/spl radic/(n/lnn)/spl times/2/sup n/ edges can be two-colored. We, in fact, present fast algorithms that output a proper two-coloring with high probability for such hypergraphs. We also derandomize and parallelize these algorithms, to derive NC/sup 1/ versions of these results. This makes progress on a problem of Erdos (1963), improving the previous-best bound of n/sup 1/3-0(1)//spl times/2/sup n/ due to Beck (1978). We further generalize this to a "local" version, improving on one of the first applications of the Lovasz Local Lemma.