Add to ORKGIn this paper we study the parallelization of CGLS, a basic iterative method for large and sparse least squares problems whose main idea is to organize the computation of conjugate gradient method to normal equations. A performance model of computation and communication phases with isoefficiency concept are used to analyze the qualitative scalability behavior of this method implemented on massively parallel distributed memory computers with two dimensional mesh communication scheme. Two different mappings of data to processors, namely simple stripe and cyclic stripe partitionings are compared by putting these communication times into the isoefficiency concept which models scalability aspects. Theoretically, the cyclic stripe partitioning is...
The implementation of accelerated conjugated gradients for the solution of large sparse systems of l...
For the solution of discretized ordinary or partial differential equations it is necessary to solve ...
Many large scale scientific simulations involve the time evolution of systems modelled as Partial Di...
In this paper we study the parallelization of PCGLS, a basic iterative method whose main idea is to ...
. In this paper we mainly focus on the study of the parallelization of PCGLS, a basic iterative meth...
In this paper we study the parallel aspects of PCGLS, a basic iterative method whose main idea is to...
Conjugate gradient (CG) methods to solve sparse systems of linear equations play an important role i...
Efficient iterative solution of large linear systems on grid computers is a complex problem. The ind...
The Conjugate Gradient (CG) algorithm is perhaps the best-known iterative technique to solve sparse ...
Conjugate gradient methods to solve sparse systems of linear equations and Lanczos algorithms for sp...
This paper describes a technique for constructing robust preconditioners for the CGLS method applied...
Many petascale and exascale scientific simulations involve the time evolution of systems modelled as...
This paper provides a comprehensive study and comparison of two state-of-the-art direct solvers for ...
: The parallel implementation of the Least Mean Square (LMS) and Recursive Least Square (RLS) adapt...
Graphics processing units (GPUs) are used as accelerators for algorithms in which the same instructi...
The implementation of accelerated conjugated gradients for the solution of large sparse systems of l...
For the solution of discretized ordinary or partial differential equations it is necessary to solve ...
Many large scale scientific simulations involve the time evolution of systems modelled as Partial Di...
In this paper we study the parallelization of PCGLS, a basic iterative method whose main idea is to ...
. In this paper we mainly focus on the study of the parallelization of PCGLS, a basic iterative meth...
In this paper we study the parallel aspects of PCGLS, a basic iterative method whose main idea is to...
Conjugate gradient (CG) methods to solve sparse systems of linear equations play an important role i...
Efficient iterative solution of large linear systems on grid computers is a complex problem. The ind...
The Conjugate Gradient (CG) algorithm is perhaps the best-known iterative technique to solve sparse ...
Conjugate gradient methods to solve sparse systems of linear equations and Lanczos algorithms for sp...
This paper describes a technique for constructing robust preconditioners for the CGLS method applied...
Many petascale and exascale scientific simulations involve the time evolution of systems modelled as...
This paper provides a comprehensive study and comparison of two state-of-the-art direct solvers for ...
: The parallel implementation of the Least Mean Square (LMS) and Recursive Least Square (RLS) adapt...
Graphics processing units (GPUs) are used as accelerators for algorithms in which the same instructi...
The implementation of accelerated conjugated gradients for the solution of large sparse systems of l...
For the solution of discretized ordinary or partial differential equations it is necessary to solve ...
Many large scale scientific simulations involve the time evolution of systems modelled as Partial Di...