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.
36642411
Parameterizing parallel multiplicative lagged-Fibonacci generators
Monte Carlo computations are commonly considered to be naturally parallel. However, one needs to exercise care in parallelizing the underlying pseudorandom number generator (PRNG) to avoid correlations within, and between, random number streams. PRNGs are normally parallelized using one of the following two paradigms: (i) cycle division and (ii) parameterization. Most of the popular PRNGs based on linear recurrences, such as linear congruential generators (LCGs), generalized feedback shift-register generators (GFSRs), and additive lagged-Fibonacci generators (ALFGs) have been parallelized using both these paradigms. While the (nonlinear) multiplicative lagged-Fibonacci generators (MLFG) is considered superior to the ALFG in quality, it had so far been parallelized only via the cycle division paradigm, which has its limitations. In this paper, we describe parallelization of the MLFG using parameterization, and discuss its implementation in the Scalable Parallel Random Number Generators (SPRNG) [ACM Trans. Math. Software 26 (2000) 436] parallel pseudorandom number generation software. We also present empirical results demonstrating the quality, and quantitatively compare the parallel ALFGs and MLFGs quality.
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.
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.
83148
Latency tolerance through parallelization of time in scientific applications
Summary form only given. Distributed computing environments, such as the grid, promise enormous raw computational power, but involve high communication overheads. It is therefore considered that they are ideally suited for "embarrassingly parallel" applications, such as Monte Carlo, and for certain applications where the loosely-coupled nature of the science involved in the simulations leads to a coarse grained computation. In a typical application, this is not feasible. We discuss our solution strategy, based on scalable functional decomposition, which can be used to keep the computation coarse grained, even on a large number of processors. Such decomposition can be attempted through a variety of means. We discuss the use of time parallelization to achieve this. We demonstrate results with a model problem, and then discuss its implementation for an important problem in nanomaterials simulation. We also show that this technique can be extended to make it inherently fault-tolerant.
15627466
Testing parallel random number generators
Monte Carlo computations are considered easy to parallelize. However, the results can be adversely affected by defects in the parallel pseudorandom number generator used. A parallel pseudorandom number generator must be tested for two types of correlations--(i) intra-stream correlation, as for any sequential generator, and (ii) inter-stream correlation for correlations between random number streams on different processes. Since bounds on these correlations are difficult to prove mathematically, large and thorough empirical tests are necessary. Many of the popular pseudorandom number generators in use today were tested when computational power was much lower, and hence they were evaluated with much smaller test sizes.This paper describes several tests of pseudorandom number generators, both statistical and application-based. We show defects in several popular generators. We describe the implementation of these tests in the SPRING [ACM Trans. Math. Software 26 (2000) 436; SPRNG--scalable parallel random number generators. SPRNG 1.0--http://www.ncsa.uiuc.edu/ Apps/SPRNG; SPRNG 2.0--http://sprng.cs.fsu.edu] test suite and also present results for the tests conducted on the SPRNG generators. These generators have passed some of the largest empirical random number tests.
9141341
Dependent rounding and its applications to approximation algorithms
We develop a new randomized rounding approach for fractional vectors defined on the edge-sets of bipartite graphs. We show various ways of combining this technique with other ideas, leading to improved (approximation) algorithms for various problems. These include:---low congestion multi-path routing;---richer random-graph models for graphs with a given degree-sequence;---improved approximation algorithms for: (i) throughput-maximization in broadcast scheduling, (ii) delay-minimization in broadcast scheduling, as well as (iii) capacitated vertex cover; and---fair scheduling of jobs on unrelated parallel machines.
11533466
Edge Domination on Bipartite Permutation Graphs and Cotriangulated Graphs
An edge dominating set D of graph G = (V, E) is a set of edges such that every edge not in D is adjacent to at least one edge in D. We develop polynomial time algorithms for finding a minimum edge dominating set for a cotriangulated graph and a bipartite permutation graph.
18165537
Application-layer broker for scalable Internet services with resource reservation
Scalability is a very important issue in providing Internet services, especially in view of the explosive growth in the number of Web users. When using the phrase Internet services, we consider text as well as multimedia presentations over the Internet, since accessing video and audio have become an integral part of the Web browsing activity. While this task of scalability can be considered as one of finding the best server or resource, the key issue of interest here is providing such a service in a transparent manner to the client. One such transparent approach is the Domain Name Server (DNS) proposed in [5]. This approach uses a modified DNS to distribute incoming client requests to different servers in a round-robin manner or based on a weighted classification. This allocation of client requests is done at the time of name-to-IP address translation carried out by the DNS. One limitation of this approach is that a translation request can go through a chain of intermediate DNSs that may cache the translation results. This caching might defeat the purpose of load balancing since an intermediate DNS can potentially allocate clients without the knowledge of the DNS in charge of load balancing. Another approach is to use a transparent front-end to forward requests to servers [4, 51. Cisco’s LocalDirector [4] is a product that uses address translation to forward requests to appropriate servers. The LocalDirector translates the headers of all data packets
18954
Approximation algorithms for the covering Steiner problem
The covering Steiner problem is a generalization of both the k-MST and the group Steiner problems: given an edge-weighted graph, with subsets of vertices called the groups, and a nonnegative integer value (called the requirement) for each group, the problem is to find a minimum-weight tree spanning at least the required number of vertices of every group. When all requirements are equal to 1, this becomes the group Steiner problem, while if there is only one group which contains all vertices of the graph the problem reduces to k-MST with k equal to the requirement of this unique group. We discuss two different (but equivalent) linear relaxations of the problem for the case when the given graph is a tree and construct polylogarithmic approximation algorithms based on randomized LP rounding of these relaxations. By using a probabilistic approximation of general metrics by tree metrics due to Bartal, our algorithms also solve the covering Steiner problem on general graphs with a further polylogarithmic worsening in the approximation ratio.
1554031
Chernoff-Hoeffding bounds for applications with limited independence
Chernoff-Hoeffding (CH) bounds are fundamental tools used in bounding the tail probabilities of the sums of bounded and independent random variables (r.v.'s). We present a simple technique that gives slightly better bounds than these and that more importantly requires only limited independence among the random variables, thereby importing a variety of standard results to the case of limited independence for free. Additional methods are also presented, and the aggregate results are sharp and provide a better understanding of the proof techniques behind these bounds. These results also yield improved bounds for various tail probability distributions and enable improved approximation algorithms for jobshop scheduling. The limited independence result implies that a reduced amount and weaker sources of randomness are sufficient for randomized algorithms whose analyses use the CH bounds, e.g., the analysis of randomized algorithms for random sampling and oblivious packet routing.