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The following page has been changed by udanax:
http://wiki.apache.org/hama/Architecture

==== The addition of multiple matrices ====
* https://issues.apache.org/jira/browse/HAMA154
 === Dense MatrixMatrix multiplication ===
+ === MatrixMatrix multiplication ===
+ ==== Dense Matrices multiplication ====
To mutliply two dense matrices A and B, We collect the blocks to 'collectionTable' firstly
using map/reduce. Rows are named as c(i, j) with sequential number ((N^2 * i) + ((j * N) +
k) to avoid duplicated records.
{{{
@@ 52, +53 @@
}}}
 Each row has a two sub matrices of a(i, k) and b(k, j) so that minimized data movement and
network cost. Finally, We multiply and sum sequentially.
+ Each row has a two sub matrices of a(i, k) and b(k, j) so that minimized data movement and
network cost.
{{{
Blocking jobs:
@@ 73, +74 @@
 ''If A stored on Hbase and we collect the B to A, Can we reduce the run time of blocking
job. Edward ''
+ ==== Sparse Matrices multiplication ====
+
+ * http://issues.apache.org/jira/browse/HAMA127
+
 === Find the maximum absolute row sum of matrix ===
+ === Find the maximum absolute row sum of dense/sparse matrix ===
Matrix.Norm.One is that find the maximum absolute row sum of matrix. Comparatively, it's
a good fit with !MapReduce model because doesn't need iterative jobs or table/file JOIN operations.
@@ 91, +96 @@
=== Compute the infinity norm ===
 It's a maximum absolute column sum of matrix.
+ It's a maximum absolute column sum of dense/sparse matrix.
{{{
i=n
@@ 103, +108 @@
 Reduce task sum the absolute values of column, select the one maximum one.
}}}
 === Compute the transpose of a matrix ===
+ === Compute the transpose of dense/sparse matrix ===
The transpose of a matrix is another matrix in which the rows and columns have been reversed.
The matrix must be square for this work.
@@ 129, +134 @@
 Reduce task sets the reversed values
}}}

 === Compute the determinant of matrix ===
+ === Compute the determinant of square matrix ===
* http://issues.apache.org/jira/browse/HAMA66
