. A block iterative method is used for solving linear least squares problems. The subproblems are solved asynchronously on a distributed memory multiprocessor. It is observed that an increased number of processors results in deteriorating rate of convergence. This deteriorating convergence is illustrated by numerical experiments. The deterioration of the convergence can be explained by contamination of the residual. Our purpose is to show that the residual is contaminated by old information. The issues investigated here are the effect of the number of processors, the role of essential neighbors, and synchronization. The characterization of old information remains an open problem. 1 Introduction In this paper, a block iterative me...
AbstractThree new iterative methods for the solution of the linear least squares problem with bound ...
This thesis proposes and analyzes several first-order methods for convex optimization, designed for ...
We present a novel iterative algorithm for approximating the linear least squares solution with low ...
Asynchronous methods for solving systems of linear equations have been researched since Chazan and M...
Elsner L, Neumann M. Monotonic sequences and rates of convergence of asynchronized iterative methods...
AbstractRecently, special attention has been given, in the mathematical literature, to the problems ...
AbstractIn a recent paper B. Vemmer and the authors investigated the effect of varying the number of...
Abstract cations, it is natural to consider distributed exe-We consider iterative algorithms of the ...
Elsner L, Neumann M, Vemmer B. The effect of the number of processors on the convergence of the para...
Summarization: The problem of accelerating the convergence rate of iterative schemes, as they apply ...
International audienceConvergence of classical parallel iterations is detected by performing a reduc...
We consider iterative algorithms of the form z:= f(z), executed by a parallel or distributed comput-...
AbstractCommunication costs are an important factor in the performance of massively parallel algorit...
Many recent problems in signal processing and machine learning such as compressed sensing, image res...
Asynchronous iterations arise naturally on parallel computers if one wants to minimize idle times. T...
AbstractThree new iterative methods for the solution of the linear least squares problem with bound ...
This thesis proposes and analyzes several first-order methods for convex optimization, designed for ...
We present a novel iterative algorithm for approximating the linear least squares solution with low ...
Asynchronous methods for solving systems of linear equations have been researched since Chazan and M...
Elsner L, Neumann M. Monotonic sequences and rates of convergence of asynchronized iterative methods...
AbstractRecently, special attention has been given, in the mathematical literature, to the problems ...
AbstractIn a recent paper B. Vemmer and the authors investigated the effect of varying the number of...
Abstract cations, it is natural to consider distributed exe-We consider iterative algorithms of the ...
Elsner L, Neumann M, Vemmer B. The effect of the number of processors on the convergence of the para...
Summarization: The problem of accelerating the convergence rate of iterative schemes, as they apply ...
International audienceConvergence of classical parallel iterations is detected by performing a reduc...
We consider iterative algorithms of the form z:= f(z), executed by a parallel or distributed comput-...
AbstractCommunication costs are an important factor in the performance of massively parallel algorit...
Many recent problems in signal processing and machine learning such as compressed sensing, image res...
Asynchronous iterations arise naturally on parallel computers if one wants to minimize idle times. T...
AbstractThree new iterative methods for the solution of the linear least squares problem with bound ...
This thesis proposes and analyzes several first-order methods for convex optimization, designed for ...
We present a novel iterative algorithm for approximating the linear least squares solution with low ...