10426404
Load balanced tree embeddings
Abstract When an n -processor architecture T is embedded into an m -processor architecture H with n > m and every processor of H is assigned at least ⌞n/m⌟ and at most [ n / m ] processors of T , the embedding has a balanced processor load. We present efficient embeddings with a balanced load for the case when both architectures are complete binary trees. We show that T can be embedded into H with a dilation of 1 and congestion of at most min{[ n / m ], 2 log n }. We also consider embeddings that achieve a balanced l/i load; i.e. every processor of H simulates at most [( n + 1)/2 m ] leaves and at most [( n − 1)/2 m ] interior processors of T . We present an embedding that achieves a balanced l/i load, a dilation of 2[log log m ] + 1 and a congestion of O(log n ). We show that every embedding strategy achieving a balanced l/i load must have a dilation of at least 3. We also consider the embedding problem when every edge of T has a weight associated with it.
41859107
Preconditioned Conjugate Gradient Solver for Large Sparse Systems on MPI
195611449
Scheduling tasks in multiprocessor systems using evolutionary strategies
Scheduling tasks in multiprocessor systems is a difficult problem. The paper describes a method based upon evolutionary strategies (using genetic algorithms) to aid in finding good task assignments. The technique is illustrated by scheduling a digital signal processing algorithm on a two processor distributed system.<<ETX>>
35215015
Coarse Grain Preconditioned Conjugate Gradient Solver for Large Sparse Systems
We explore a coarse grain parallel algorithm for the solution of large sparse linear systems with symmetric positive definite matrix, based on a preconditioned conjugate gradient method.
17006088
An Efficient MAP Classifier for Sensornets
The classification phase is computationally intensive and frequently recurs in tracking applications in sensor networks. Most related work uses traditional signal processing classifiers, such as Maximum A Posterior (MAP) classifier. Naive formulations of MAP are not feasible for resource constraint sensornet nodes. In this paper, we study computationally efficient methods for classification. We propose to use one-sided Jacobi iterations for eigen value decomposition of the covariance matrices, the inverse of which are needed in MAP classifier. We show that this technique greatly simplifies the execution of MAP classifier and makes it a feasible and efficient choice for sensornet applications.
6027825
Generalized compressed tree machines
Parallel machines interconnecting up to thousands of processors have been proposed and recently built. One of the earliest and the most prominent one is a complete binary tree machine. The authors propose a family of tree machines called generalized compressed tree machines. Generalized compressed tree machines may, in general, be viewed as a derivative of the complete binary tree networks.<<ETX>>
43248661
Online Transcoding of Web Pages for Mobile Devices
Accessing Internet from mobile devices such as PDAs and cell phones is becoming widespread. Since these devices do not have the same rendering capabilities as desktop computers, it is necessary for web contents to be transcoded for proper presentation on these types of devices. In this paper we propose an architecture for online transcoding of web documents. In the proposed system, a proxy fetches web pages on the client’s behalf, categorizes the contents into predefined domain-specific categories, and dynamically generates a hierarchical summary view of the relevant topics of the page based on domain specific knowledge. This hierarchical summary of information is then transmitted to the client. The architecture uses domain specific knowledge, but allows easy adaptation to different domains by plugging in rule sets specific to the domain. The system does not expect any adjustment in the existing WWW contents. Results for one test domain, News, are shown. The results indicate that the system can produce high precision transcoded pages online using domain specific knowledge with very little performance penalty.
26737462
The Parallel Complexity of Tree Embedding Problems
Abstract The question of the sequential complexity of various tree embedding problems arises in the recent work of Robertson and Seymour on graph miners; here we consider the parallel complexity of such problems. In particular, we present two CREW PRAM algorithms: an O (log 3 n ) time randomized algorithm for determining whether there is a topological embedding of one rooted tree in another and an O (log 2 n log log n ) time deterministic algorithm for determining whether or not a rooted tree with a degree constraint is a minor of a general rooted tree. These algorithms are two examples of a general technique that can be used for solving other problems on trees.
854648
Approximation algorithms for low-distortion embeddings into low-dimensional spaces
We present several approximation algorithms for the problem of embedding metric spaces into a line, and into the two-dimensional plane. Among other results, we give an O(√n)-approximation algorithm for the problem of finding a line embedding of a metric induced by a given unweighted graph, that minimizes the (standard) multiplicative distortion. We give an improved Õ(n1/3) approximation for the case of metrics generated by unweighted trees. This is the first result of this type.
575078
An Approach for Detecting Self-propagating Email Using Anomaly Detection
This paper develops a new approach for detecting self-propagating email viruses based on statistical anomaly detection. Our approach assumes that a key objective of an email virus attack is to eventually overwhelm mail servers and clients with a large volume of email traffic. Based on this assumption, the approach is designed to detect increases in traffic volume over what was observed during the training period. This paper describes our approach and the results of our simulation-based experiments in assessing the effectiveness of the approach in an intranet setting. Within the simulation setting, our results establish that the approach is effective in detecting attacks all of the time, with very few false alarms. In addition, attacks could be detected sufficiently early so that clean up efforts need to target only a fraction of the email clients in an intranet.
12588315
The Many Faces of Process Interaction Graphs: A Data Management Perspective
WE USE THE EXPRESSION “process interaction graph” (PIG) as a general purpose term to cover instances of network-like structures with specific semantics, including signal transduction networks, gene regulatory networks, metabolic pathways and so forth, because we believe that despite the differences in biological significance, they can be treated in a uniform data management framework. Aside from the fact that they are all graph-like entities, PIGs share a few common characteristics, such as follows: