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== Hbase Matrix Package for Map/Reducebased Parallel Matrix Computations ==
+ The matrix package will be useful for some of the largescale numeric analysis and data
mining which need the computation system of the Inverse Matrix for Data Mining related area
(e.g. linear regression, PCA, SVM, ..., etc).
+
 The current sharedmemory based parallel matrix solution provides a scalable and high performance
matrix operations, however, matrix resources can't be scalable. But, Using Hbase's Row,Column(Qualifier)
two dimensional space, we are able to store large sparse matrix. Also, The Autopartitioned
sparsity substructure will be efficiently managed and serviced by Hbase. Row or Column operations
can be done in linear time and algorithms such as structured Gaussian elimination or iterative
methods run in '''O(~the number of nonzero elements in the matrix~)''' time.
+ The current sharedmemory based parallel matrix solution provides a scalable and high performance
matrix operations, however, matrix resources can't be scalable. But, Using Hbase's Row,Column(Qualifier)
two dimensional space, we are able to store large sparse matrix. Also, The Autopartitioned
sparsity substructure will be efficiently managed and serviced by Hbase. Row or Column operations
can be done in linear time and algorithms such as structured Gaussian elimination or iterative
methods run in O(~the number of nonzero elements in the matrix/number of mappers (processors/cores)~)
time on Map/Reduce.
=== Initial Contributors ===
@@ 11, +13 @@
=== Applications ===
It can be support a broad variety of applications in the domain of Physics, Linear Algebra,
 [[BR]]Computational Fluid Dynamics, Relational Algebra, Statistics, Graphics Rendering and
others.
+ [[BR]]Computational Fluid Dynamics, Statistics, Graphics Rendering and others.
* Scientific simulation and modeling
* Matrixvector/matrixmatrix multiply
