The most effective algorithms of solving large sparse linear system are Block Wiedemann and Block Lanczos, sparse matrix-vector multiplication iterations is the main process of these algorithms, to achieve parallel computing of its process, we have established three different parallel algorithm models and analyzed the characteristic features of their computing and communication, and through the analysis and comparison of time-cost, we choose the optimal model. © 2013 IEEE
A model of a general class of asynchronous, iterative solution methods for linear systems is develop...
In this review paper, we consider some important developments and trends in algorithm design for t...
This book is primarily intended as a research monograph that could also be used in graduate courses ...
Sparse matrix computations play an important role in iterative methods to solve systems of equations...
The sparse matrix--vector multiplication is an important kernel, but is hard to efficiently execute ...
We identify the challenges that are special to parallel sparse matrix-matrix multiplication (PSpGEMM...
this paper. We would also like to thank Rolf Strebel for explanatory discussions on the subject of s...
We design and develop a work-efficient multithreaded algorithm for sparse matrix-sparse vector multi...
Parallel sparse matrix-matrix multiplication algorithms (PSpGEMM) spend most of their running time o...
Sparse matrix-vector multiplications are essential in the numerical resolution of partial differenti...
AbstractThe matrix-vector multiplication operation is the kernel of most numerical algorithms.Typica...
This paper describes two portable packages for general-purpose sparse matrix computations: SPARSKIT...
Vector computers have been extensively used for years in matrix algebra to treat with large dense ma...
The aim of this paper is to show an effective reorganization of the nonsymmetric block lanczos algo...
Paper at the Parallel Computing Conf. Verona (IT) Sep 1988Available from British Library Document Su...
A model of a general class of asynchronous, iterative solution methods for linear systems is develop...
In this review paper, we consider some important developments and trends in algorithm design for t...
This book is primarily intended as a research monograph that could also be used in graduate courses ...
Sparse matrix computations play an important role in iterative methods to solve systems of equations...
The sparse matrix--vector multiplication is an important kernel, but is hard to efficiently execute ...
We identify the challenges that are special to parallel sparse matrix-matrix multiplication (PSpGEMM...
this paper. We would also like to thank Rolf Strebel for explanatory discussions on the subject of s...
We design and develop a work-efficient multithreaded algorithm for sparse matrix-sparse vector multi...
Parallel sparse matrix-matrix multiplication algorithms (PSpGEMM) spend most of their running time o...
Sparse matrix-vector multiplications are essential in the numerical resolution of partial differenti...
AbstractThe matrix-vector multiplication operation is the kernel of most numerical algorithms.Typica...
This paper describes two portable packages for general-purpose sparse matrix computations: SPARSKIT...
Vector computers have been extensively used for years in matrix algebra to treat with large dense ma...
The aim of this paper is to show an effective reorganization of the nonsymmetric block lanczos algo...
Paper at the Parallel Computing Conf. Verona (IT) Sep 1988Available from British Library Document Su...
A model of a general class of asynchronous, iterative solution methods for linear systems is develop...
In this review paper, we consider some important developments and trends in algorithm design for t...
This book is primarily intended as a research monograph that could also be used in graduate courses ...