Dryad is a general-purpose distributed execution engine for coarse-grain data-parallel applications. A Dryad applica-tion combines computational “vertices ” with communica-tion “channels ” to form a dataflow graph. Dryad runs the application by executing the vertices of this graph on a set

, or fairing, to low-pass filtering. We describe a very simple surface signal low-pass filter algorithm that applies to surfaces of arbitrary topology. As opposed to other existing optimization-based fairing methods, which are computationally more expensive, this is a linear time and space complexity algorithm

A data structure is proposed to maintain a collection of vertex-disjoint trees under a sequence of two kinds of operations: a link operation that combines two trees into one by adding an edge, and a cut operation that divides one tree into two by deleting an edge. Each operation requires O(log n

The goal of DryadLINQ is to make distributed computing on large computer clusters simple enough for ordinary programmers. DryadLINQ combines two important pieces of Microsoft technology: the Dryad distributed execution engine and the.NET Language Integrated Query (LINQ). About this brief: We

of the corner. A new scale-space based approach that combines useful properties from the Laplacian and Beaudet's measure [Bea78] is then proposed in order to correct and detect exactly the corner position. An extension of this approach is then developed to solve the problem of trihedral vertex

DryadLINQ [7] is a system that facilitates the construc-tion of distributed execution plans for processing large amounts of data on clusters containing potentially thou-sands of computers. In this paper, we explore how to use DryadLINQ to perform basic matrix operations on large matrices. Dryad

. We augment the constructive techniques found in logic programming, which are also based on an extended Horn logic, to produce constructive techniques for reasoning about models and metamodels. These methods have a number of practical applications: At the meta-level, it can be decided if a (composite

Jacobian-free Newton-Krylov (JFNK) methods are synergistic combinations of Newton-type methods for superlinearly convergent solution of nonlinear equa-tions and Krylov subspace methods for solving the Newton correction equations. The link between the two methods is the Jacobian-vector product

Abstract not found

Abstract not found