In this paper, I explain a previously published three-dimensional algorithm for multiplying two two-dimensional matrices. The basic concept of this approach is to split the matrices into sub-matrices which are intelligently distributed across all of the available processes. Then, each process computes a smaller ma-trix multiplication subproblem. These intermediate results are combined to create the final answer. This algorithm takes ad-vantage of the parallel aspects of matrix multiplication while minimizing the required communication. A model has been generated to estimate the execution time of the algorithm given various necessary system parameters and the size of the input matrices. Finally, the results from the original paper are shown ...
Matrix multiplication (MM) is a computationally-intensive operation in many algorithms used in scien...
AbstractThis paper develops optimal algorithms to multiply an n × n symmetric tridiagonal matrix by:...
Proceedings of the 8th IEEE International Conference on Cluster Computing (Cluster 2006), October, 2...
These notes are based on a lecture given at the Toronto Student Seminar on February 2, 2012. The mat...
Effective arranging of numerical data and design of associated computational algorithms are importan...
Matrix multiplication is commonly used in scientific computation. Given matrices A = (aij ) of size ...
. A distributed algorithm with the same functionality as the single-processor level 3 BLAS operation...
We present lower bounds on the amount of communication that matrix multiplication algorithms must pe...
This paper develops an algorithm to multiply a px2 matrix by a 2xn matrix in $\lceil (3pn+max(n,p))/...
Some level-2 and level-3 Distributed Basic Linear Algebra Subroutines (DBLAS) that have been impleme...
Matrix multiplication is significant in a lot of scientific fields, such as mathematics, physics and...
In this paper, the index space of the (n×n)-matrix multiply-add problem C = C +A·B is represented as...
The main topic of this lecture is fast matrix multiplication. This topic is covered very well in tex...
This paper was produced as a result of my interest in metric multiplication of high ordered matrix. ...
In this thesis it is showed how an \(O(n^{4-\epsilon})\) algorithm for the cube multiplication probl...
Matrix multiplication (MM) is a computationally-intensive operation in many algorithms used in scien...
AbstractThis paper develops optimal algorithms to multiply an n × n symmetric tridiagonal matrix by:...
Proceedings of the 8th IEEE International Conference on Cluster Computing (Cluster 2006), October, 2...
These notes are based on a lecture given at the Toronto Student Seminar on February 2, 2012. The mat...
Effective arranging of numerical data and design of associated computational algorithms are importan...
Matrix multiplication is commonly used in scientific computation. Given matrices A = (aij ) of size ...
. A distributed algorithm with the same functionality as the single-processor level 3 BLAS operation...
We present lower bounds on the amount of communication that matrix multiplication algorithms must pe...
This paper develops an algorithm to multiply a px2 matrix by a 2xn matrix in $\lceil (3pn+max(n,p))/...
Some level-2 and level-3 Distributed Basic Linear Algebra Subroutines (DBLAS) that have been impleme...
Matrix multiplication is significant in a lot of scientific fields, such as mathematics, physics and...
In this paper, the index space of the (n×n)-matrix multiply-add problem C = C +A·B is represented as...
The main topic of this lecture is fast matrix multiplication. This topic is covered very well in tex...
This paper was produced as a result of my interest in metric multiplication of high ordered matrix. ...
In this thesis it is showed how an \(O(n^{4-\epsilon})\) algorithm for the cube multiplication probl...
Matrix multiplication (MM) is a computationally-intensive operation in many algorithms used in scien...
AbstractThis paper develops optimal algorithms to multiply an n × n symmetric tridiagonal matrix by:...
Proceedings of the 8th IEEE International Conference on Cluster Computing (Cluster 2006), October, 2...