AbstractThe problem of minimizing a weighted sum of Euclidean norms is considered. Applications include minimal-surface computations. A robust parallel algorithm, based upon a line-search Newton's method, is presented which takes full advantage of the structure of the problem in order to fully utilize vectorization and concurrency in the computations. The proposed method can achieve good performance, especially on a machine with an architecture that combines vector and parallel capabilities on a two-level shared memory structure such as that on the Alliant FX/8 system. Performance results are given on the Alliant to illustrate the efficiency of the algorithm
In this paper it is investigated which pivots may be processed simultaneously when solving a set of ...
A parallel method for globally minimizing a linear program with an additional reverse convex constra...
<p>Each thread block is assigned to compute the norm of one vector in . Each thread strides through...
AbstractThe problem of minimizing a weighted sum of Euclidean norms is considered. Applications incl...
10.1016/S0377-0427(01)00357-0Journal of Computational and Applied Mathematics1381127-15
We consider the ℓ ∞ -norm minimization problem, which has been investigated in various practical app...
Two issues in linear algebra algorithms for multicomputers are addressed. First, how tounify paralle...
An algorithm, designed to exploit the parallel computing or vector streaming (pipeline) capabilities...
This paper provides an introduction to algorithms for fundamental linear algebra problems on various...
This paper provides an introduction to algorithms for fundamental linear algebra problems on various...
AbstractWe study the problem of minimizing a sum of Euclidean norms. This nonsmooth optimization pro...
We present parallel algorithms for geometric problems on coarse grained multicomputers. More specifi...
Global optimization problems sometimes attain their extrema on infinite subsets of the search space,...
We give a parallel algorithm for the problem of computing the row minima of a totally monotone two-d...
Underdetermined systems of equations in which the minimum norm solution needs to be computed arise i...
In this paper it is investigated which pivots may be processed simultaneously when solving a set of ...
A parallel method for globally minimizing a linear program with an additional reverse convex constra...
<p>Each thread block is assigned to compute the norm of one vector in . Each thread strides through...
AbstractThe problem of minimizing a weighted sum of Euclidean norms is considered. Applications incl...
10.1016/S0377-0427(01)00357-0Journal of Computational and Applied Mathematics1381127-15
We consider the ℓ ∞ -norm minimization problem, which has been investigated in various practical app...
Two issues in linear algebra algorithms for multicomputers are addressed. First, how tounify paralle...
An algorithm, designed to exploit the parallel computing or vector streaming (pipeline) capabilities...
This paper provides an introduction to algorithms for fundamental linear algebra problems on various...
This paper provides an introduction to algorithms for fundamental linear algebra problems on various...
AbstractWe study the problem of minimizing a sum of Euclidean norms. This nonsmooth optimization pro...
We present parallel algorithms for geometric problems on coarse grained multicomputers. More specifi...
Global optimization problems sometimes attain their extrema on infinite subsets of the search space,...
We give a parallel algorithm for the problem of computing the row minima of a totally monotone two-d...
Underdetermined systems of equations in which the minimum norm solution needs to be computed arise i...
In this paper it is investigated which pivots may be processed simultaneously when solving a set of ...
A parallel method for globally minimizing a linear program with an additional reverse convex constra...
<p>Each thread block is assigned to compute the norm of one vector in . Each thread strides through...